[VOTE] Accept Eagle into Apache Incubation

["Manoharan, Arun" <ar...@ebay.com>]

Hello Everyone,

Thanks for all the feedback on the Eagle Proposal.

I would like to call for a [VOTE] on Eagle joining the ASF as an incubation project.

The vote is open for 72 hours:

[ ] +1 accept Eagle in the Incubator
[ ] ±0
[ ] -1 (please give reason)

Eagle is a Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities and take actions in real time. Eagle supports a wide variety of policies on HDFS data and Hive. Eagle also provides machine learning models for detecting anomalous user behavior in Hadoop.

The proposal is available on the wiki here:
https://wiki.apache.org/incubator/EagleProposal

The text of the proposal is also available at the end of this email.

Thanks for your time and help.

Thanks,
Arun

<COPY of the proposal in text format>

Eagle

Abstract
Eagle is an Open Source Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities in hadoop and take actions.

Proposal
Eagle audits access to HDFS files, Hive and HBase tables in real time, enforces policies defined on sensitive data access and alerts or blocks user’s access to that sensitive data in real time. Eagle also creates user profiles based on the typical access behaviour for HDFS and Hive and sends alerts when anomalous behaviour is detected. Eagle can also import sensitive data information classified by external classification engines to help define its policies.

Overview of Eagle
Eagle has 3 main parts.
1.Data collection and storage - Eagle collects data from various hadoop logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
2.Data processing and policy engine - Eagle allows users to create policies based on various metadata properties on HDFS, Hive and HBase data.
3.Eagle services - Eagle services include policy manager, query service and the visualization component. Eagle provides intuitive user interface to administer Eagle and an alert dashboard to respond to real time alerts.

Data Collection and Storage:
Eagle provides programming API for extending Eagle to integrate any data source into Eagle policy evaluation framework. For example, Eagle hdfs audit monitoring collects data from Kafka which is populated from namenode log4j appender or from logstash agent. Eagle hive monitoring collects hive query logs from running job through YARN API, which is designed to be scalable and fault-tolerant. Eagle uses HBase as storage for storing metadata and metrics data, and also supports relational database through configuration change.

Data Processing and Policy Engine:
Processing Engine: Eagle provides stream processing API which is an abstraction of Apache Storm. It can also be extended to other streaming engines. This abstraction allows developers to assemble data transformation, filtering, external data join etc. without physically bound to a specific streaming platform. Eagle streaming API allows developers to easily integrate business logic with Eagle policy engine and internally Eagle framework compiles business logic execution DAG into program primitives of underlying stream infrastructure e.g. Apache Storm. For example, Eagle HDFS monitoring transforms audit log from Namenode to object and joins sensitivity metadata, security zone metadata which are generated from external programs or configured by user. Eagle hive monitoring filters running jobs to get hive query string and parses query string into object and then joins sensitivity metadata.
Alerting Framework: Eagle Alert Framework includes stream metadata API, scalable policy engine framework, extensible policy engine framework. Stream metadata API allows developers to declare event schema including what attributes constitute an event, what is the type for each attribute, and how to dynamically resolve attribute value in runtime when user configures policy. Scalable policy engine framework allows policies to be executed on different physical nodes in parallel. It is also used to define your own policy partitioner class. Policy engine framework together with streaming partitioning capability provided by all streaming platforms will make sure policies and events can be evaluated in a fully distributed way. Extensible policy engine framework allows developer to plugin a new policy engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports as first-class citizen.
Machine Learning module: Eagle provides capabilities to define user activity patterns or user profiles for Hadoop users based on the user behaviour in the platform. These user profiles are modeled using Machine Learning algorithms and used for detection of anomalous users activities. Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for generating user profile models. The model reads data from HDFS audit logs, preprocesses and aggregates data, and generates models using Spark programming APIs. Once models are generated, Eagle uses stream processing engine for near real-time anomaly detection to determine if any user’s activities are suspicious or not.

Eagle Services:
Query Service: Eagle provides SQL-like service API to support comprehensive computation for huge set of data on the fly, for e.g. comprehensive filtering, aggregation, histogram, sorting, top, arithmetical expression, pagination etc. HBase is the data storage which Eagle supports as first-class citizen, relational database is supported as well. For HBase storage, Eagle query framework compiles user provided SQL-like query into HBase native filter objects and execute it through HBase coprocessor on the fly.
Policy Manager: Eagle policy manager provides UI and Restful API for user to define policy with just a few clicks. It includes site management UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive resource browsing, alert dashboards etc.
Background
Data is one of the most important assets for today’s businesses, which makes data security one of the top priorities of today’s enterprises. Hadoop is widely used across different verticals as a big data repository to store this data in most modern enterprises.
At eBay we use hadoop platform extensively for our data processing needs. Our data in Hadoop is becoming bigger and bigger as our user base is seeing an exponential growth. Today there are variety of data sets available in Hadoop cluster for our users to consume. eBay has around 120 PB of data stored in HDFS across 6 different clusters and around 1800+ active hadoop users consuming data thru Hive, HBase and mapreduce jobs everyday to build applications using this data. With this astronomical growth of data there are also challenges in securing sensitive data and monitoring the access to this sensitive data. Today in large organizations HDFS is the defacto standard for storing big data. Data sets which includes and not limited to consumer sentiment, social media data, customer segmentation, web clicks, sensor data, geo-location and transaction data get stored in Hadoop for day to day business needs.
We at eBay want to make sure the sensitive data and data platforms are completely protected from security breaches. So we partnered very closely with our Information Security team to understand the requirements for Eagle to monitor sensitive data access on hadoop:
1.Ability to identify and stop security threats in real time
2.Scale for big data (Support PB scale and Billions of events)
3.Ability to create data access policies
4.Support multiple data sources like HDFS, HBase, Hive
5.Visualize alerts in real time
6.Ability to block malicious access in real time
We did not find any data access monitoring solution that available today and can provide the features and functionality that we need to monitor the data access in the hadoop ecosystem at our scale. Hence with an excellent team of world class developers and several users, we have been able to bring Eagle into production as well as open source it.

Rationale
In today’s world; data is an important asset for any company. Businesses are using data extensively to create amazing experiences for users. Data has to be protected and access to data should be secured from security breaches. Today Hadoop is not only used to store logs but also stores financial data, sensitive data sets, geographical data, user click stream data sets etc. which makes it more important to be protected from security breaches. To secure a data platform there are multiple things that need to happen. One is having a strong access control mechanism which today is provided by Apache Ranger and Apache Sentry. These tools provide the ability to provide fine grain access control mechanism to data sets on hadoop. But there is a big gap in terms of monitoring all the data access events and activities in order to securing the hadoop data platform. Together with strong access control, perimeter security and data access monitoring in place data in the hadoop clusters can be secured against breaches. We looked around and found following:
Existing data activity monitoring products are designed for traditional databases and data warehouse. Existing monitoring platforms cannot scale out to support fast growing data and petabyte scale. Few products in the industry are still very early in terms of supporting HDFS, Hive, HBase data access monitoring.
As mentioned in the background, the business requirement and urgency to secure the data from users with malicious intent drove eBay to invest in building a real time data access monitoring solution from scratch to offer real time alerts and remediation features for malicious data access.
With the power of open source distributed systems like Hadoop, Kafka and much more we were able to develop a data activity monitoring system that can scale, identify and stop malicious access in real time.
Eagle allows admins to create standard access policies and rules for monitoring HDFS, Hive and HBase data. Eagle also provides out of box machine learning models for modeling user profiles based on user access behaviour and use the model to alert on anomalies.

Current Status

Meritocracy
Eagle has been deployed in production at eBay for monitoring billions of events per day from HDFS and Hive operations. From the start; the product has been built with focus on high scalability and application extensibility in mind and Eagle has demonstrated great performance in responding to suspicious events instantly and great flexibility in defining policy.

Community
Eagle seeks to develop the developer and user communities during incubation.

Core Developers
Eagle is currently being designed and developed by engineers from eBay Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang, Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of these core developers have deep expertise in developing monitoring products for the Hadoop ecosystem.

Alignment
The ASF is a natural host for Eagle given that it is already the home of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data projects. Eagle leverages lot of Apache open-source products. Eagle was designed to offer real time insights into sensitive data access by actively monitoring the data access on various data sets in hadoop and an extensible alerting framework with a powerful policy engine. Eagle compliments the existing Hadoop platform area by providing a comprehensive monitoring and alerting solution for detecting sensitive data access threats based on preset policies and machine learning models for user behaviour analysis.

Known Risks

Orphaned Products
The core developers of Eagle team work full time on this project. There is no risk of Eagle getting orphaned since eBay is extensively using it in their production Hadoop clusters and have plans to go beyond hadoop. For example, currently there are 7 hadoop clusters and 2 of them are being monitored using Hadoop Eagle in production. We have plans to extend it to all hadoop clusters and eventually other data platforms. There are 10’s of policies onboarded and actively monitored with plans to onboard more use case. We are very confident that every hadoop cluster in the world will be monitored using Eagle for securing the hadoop ecosystem by actively monitoring for data access on sensitive data. We plan to extend and diversify this community further through Apache. We presented Eagle at the hadoop summit in china and garnered interest from different companies who use hadoop extensively.

Inexperience with Open Source
The core developers are all active users and followers of open source. They are already committers and contributors to the Eagle Github project. All have been involved with the source code that has been released under an open source license, and several of them also have experience developing code in an open source environment. Though the core set of Developers do not have Apache Open Source experience, there are plans to onboard individuals with Apache open source experience on to the project. Apache Kylin PMC members are also in the same ebay organization. We work very closely with Apache Ranger committers and are looking forward to find meaningful integrations to improve the security of hadoop platform.

Homogenous Developers
The core developers are from eBay. Today the problem of monitoring data activities to find and stop threats is a universal problem faced by all the businesses. Apache Incubation process encourages an open and diverse meritocratic community. Eagle intends to make every possible effort to build a diverse, vibrant and involved community and has already received substantial interest from various organizations.

Reliance on Salaried Developers
eBay invested in Eagle as the monitoring solution for Hadoop clusters and some of its key engineers are working full time on the project. In addition, since there is a growing need for securing sensitive data access we need a data activity monitoring solution for Hadoop, we look forward to other Apache developers and researchers to contribute to the project. Additional contributors, including Apache committers have plans to join this effort shortly. Also key to addressing the risk associated with relying on Salaried developers from a single entity is to increase the diversity of the contributors and actively lobby for Domain experts in the security space to contribute. Eagle intends to do this.

Relationships with Other Apache Products
Eagle has a strong relationship and dependency with Apache Hadoop, HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation community, could help with a closer collaboration among these projects and as well as others. An Excessive Fascination with the Apache Brand Eagle is proposing to enter incubation at Apache in order to help efforts to diversify the committer-base, not so much to capitalize on the Apache brand. The Eagle project is in production use already inside eBay, but is not expected to be an eBay product for external customers. As such, the Eagle project is not seeking to use the Apache brand as a marketing tool.

Documentation
Information about Eagle can be found at https://github.com/eBay/Eagle. The following link provide more information about Eagle http://goeagle.io<http://goeagle.io/>.

Initial Source
Eagle has been under development since 2014 by a team of engineers at eBay Inc. It is currently hosted on Github.com under an Apache license 2.0 at https://github.com/eBay/Eagle. Once in incubation we will be moving the code base to apache git library.

External Dependencies
Eagle has the following external dependencies.
Basic
•JDK 1.7+
•Scala 2.10.4
•Apache Maven
•JUnit
•Log4j
•Slf4j
•Apache Commons
•Apache Commons Math3
•Jackson
•Siddhi CEP engine

Hadoop
•Apache Hadoop
•Apache HBase
•Apache Hive
•Apache Zookeeper
•Apache Curator

Apache Spark
•Spark Core Library

REST Service
•Jersey

Query
•Antlr

Stream processing
•Apache Storm
•Apache Kafka

Web
•AngularJS
•jQuery
•Bootstrap V3
•Moment JS
•Admin LTE
•html5shiv
•respond
•Fastclick
•Date Range Picker
•Flot JS

Cryptography
Eagle will eventually support encryption on the wire. This is not one of the initial goals, and we do not expect Eagle to be a controlled export item due to the use of encryption. Eagle supports but does not require the Kerberos authentication mechanism to access secured Hadoop services.

Required Resources

Mailing List
•eagle-private for private PMC discussions
•eagle-dev for developers
•eagle-commits for all commits
•eagle-users for all eagle users

Subversion Directory
•Git is the preferred source control system.

Issue Tracking
•JIRA Eagle (Eagle)

Other Resources
The existing code already has unit tests so we will make use of existing Apache continuous testing infrastructure. The resulting load should not be very large.

Initial Committers
•Seshu Adunuthula <sadunuthula at ebay dot com>
•Arun Manoharan <armanoharan at ebay dot com>
•Edward Zhang <yonzhang at ebay dot com>
•Hao Chen <hchen9 at ebay dot com>
•Chaitali Gupta <cgupta at ebay dot com>
•Libin Sun <libsun at ebay dot com>
•Jilin Jiang <jiljiang at ebay dot com>
•Qingwen Zhao <qingwzhao at ebay dot com>
•Hemanth Dendukuri <hdendukuri at ebay dot com>
•Senthil Kumar <senthilkumar at ebay dot com>


Affiliations
The initial committers are employees of eBay Inc.

Sponsors

Champion
•Henry Saputra <hsaputra at apache dot org> - Apache IPMC member

Nominated Mentors
•Owen O’Malley < omalley at apache dot org > - Apache IPMC member, Hortonworks
•Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
•Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member, Hortonworks
•Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC member
•Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks

Sponsoring Entity
We are requesting the Incubator to sponsor this project.

Re: [VOTE] Accept Eagle into Apache Incubation

[Don Bosco Durai <bo...@apache.org>]

+1 non binding 
Bosco 



    _____________________________
From: Li Yang <li...@apache.org>
Sent: Sunday, October 25, 2015 8:13 PM
Subject: Re: [VOTE] Accept Eagle into Apache Incubation
To:  <ge...@incubator.apache.org>


+1 (non-binding)

On Mon, Oct 26, 2015 at 10:50 AM, hongbin ma <ma...@apache.org> wrote:

> +1 (non binding)
>
> On Mon, Oct 26, 2015 at 12:20 AM, Ralph Goers <ra...@dslextreme.com>
> wrote:
>
> > +1 (binding)
> >
> > Ralph
> >
> > > On Oct 23, 2015, at 7:11 AM, Manoharan, Arun <ar...@ebay.com>
> > wrote:
> > >
> > > Hello Everyone,
> > >
> > > Thanks for all the feedback on the Eagle Proposal.
> > >
> > > I would like to call for a [VOTE] on Eagle joining the ASF as an
> > incubation project.
> > >
> > > The vote is open for 72 hours:
> > >
> > > [ ] +1 accept Eagle in the Incubator
> > > [ ] ±0
> > > [ ] -1 (please give reason)
> > >
> > > Eagle is a Monitoring solution for Hadoop to instantly identify access
> > to sensitive data, recognize attacks, malicious activities and take
> actions
> > in real time. Eagle supports a wide variety of policies on HDFS data and
> > Hive. Eagle also provides machine learning models for detecting anomalous
> > user behavior in Hadoop.
> > >
> > > The proposal is available on the wiki here:
> > > https://wiki.apache.org/incubator/EagleProposal
> > >
> > > The text of the proposal is also available at the end of this email.
> > >
> > > Thanks for your time and help.
> > >
> > > Thanks,
> > > Arun
> > >
> > > <COPY of the proposal in text format>
> > >
> > > Eagle
> > >
> > > Abstract
> > > Eagle is an Open Source Monitoring solution for Hadoop to instantly
> > identify access to sensitive data, recognize attacks, malicious
> activities
> > in hadoop and take actions.
> > >
> > > Proposal
> > > Eagle audits access to HDFS files, Hive and HBase tables in real time,
> > enforces policies defined on sensitive data access and alerts or blocks
> > user’s access to that sensitive data in real time. Eagle also creates
> user
> > profiles based on the typical access behaviour for HDFS and Hive and
> sends
> > alerts when anomalous behaviour is detected. Eagle can also import
> > sensitive data information classified by external classification engines
> to
> > help define its policies.
> > >
> > > Overview of Eagle
> > > Eagle has 3 main parts.
> > > 1.Data collection and storage - Eagle collects data from various hadoop
> > logs in real time using Kafka/Yarn API and uses HDFS and HBase for
> storage.
> > > 2.Data processing and policy engine - Eagle allows users to create
> > policies based on various metadata properties on HDFS, Hive and HBase
> data.
> > > 3.Eagle services - Eagle services include policy manager, query service
> > and the visualization component. Eagle provides intuitive user interface
> to
> > administer Eagle and an alert dashboard to respond to real time alerts.
> > >
> > > Data Collection and Storage:
> > > Eagle provides programming API for extending Eagle to integrate any
> data
> > source into Eagle policy evaluation framework. For example, Eagle hdfs
> > audit monitoring collects data from Kafka which is populated from
> namenode
> > log4j appender or from logstash agent. Eagle hive monitoring collects
> hive
> > query logs from running job through YARN API, which is designed to be
> > scalable and fault-tolerant. Eagle uses HBase as storage for storing
> > metadata and metrics data, and also supports relational database through
> > configuration change.
> > >
> > > Data Processing and Policy Engine:
> > > Processing Engine: Eagle provides stream processing API which is an
> > abstraction of Apache Storm. It can also be extended to other streaming
> > engines. This abstraction allows developers to assemble data
> > transformation, filtering, external data join etc. without physically
> bound
> > to a specific streaming platform. Eagle streaming API allows developers
> to
> > easily integrate business logic with Eagle policy engine and internally
> > Eagle framework compiles business logic execution DAG into program
> > primitives of underlying stream infrastructure e.g. Apache Storm. For
> > example, Eagle HDFS monitoring transforms audit log from Namenode to
> object
> > and joins sensitivity metadata, security zone metadata which are
> generated
> > from external programs or configured by user. Eagle hive monitoring
> filters
> > running jobs to get hive query string and parses query string into object
> > and then joins sensitivity metadata.
> > > Alerting Framework: Eagle Alert Framework includes stream metadata API,
> > scalable policy engine framework, extensible policy engine framework.
> > Stream metadata API allows developers to declare event schema including
> > what attributes constitute an event, what is the type for each attribute,
> > and how to dynamically resolve attribute value in runtime when user
> > configures policy. Scalable policy engine framework allows policies to be
> > executed on different physical nodes in parallel. It is also used to
> define
> > your own policy partitioner class. Policy engine framework together with
> > streaming partitioning capability provided by all streaming platforms
> will
> > make sure policies and events can be evaluated in a fully distributed
> way.
> > Extensible policy engine framework allows developer to plugin a new
> policy
> > engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> > engine which Eagle supports as first-class citizen.
> > > Machine Learning module: Eagle provides capabilities to define user
> > activity patterns or user profiles for Hadoop users based on the user
> > behaviour in the platform. These user profiles are modeled using Machine
> > Learning algorithms and used for detection of anomalous users activities.
> > Eagle uses Eigen Value Decomposition, and Density Estimation algorithms
> for
> > generating user profile models. The model reads data from HDFS audit
> logs,
> > preprocesses and aggregates data, and generates models using Spark
> > programming APIs. Once models are generated, Eagle uses stream processing
> > engine for near real-time anomaly detection to determine if any user’s
> > activities are suspicious or not.
> > >
> > > Eagle Services:
> > > Query Service: Eagle provides SQL-like service API to support
> > comprehensive computation for huge set of data on the fly, for e.g.
> > comprehensive filtering, aggregation, histogram, sorting, top,
> arithmetical
> > expression, pagination etc. HBase is the data storage which Eagle
> supports
> > as first-class citizen, relational database is supported as well. For
> HBase
> > storage, Eagle query framework compiles user provided SQL-like query into
> > HBase native filter objects and execute it through HBase coprocessor on
> the
> > fly.
> > > Policy Manager: Eagle policy manager provides UI and Restful API for
> > user to define policy with just a few clicks. It includes site management
> > UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive
> > resource browsing, alert dashboards etc.
> > > Background
> > > Data is one of the most important assets for today’s businesses, which
> > makes data security one of the top priorities of today’s enterprises.
> > Hadoop is widely used across different verticals as a big data repository
> > to store this data in most modern enterprises.
> > > At eBay we use hadoop platform extensively for our data processing
> > needs. Our data in Hadoop is becoming bigger and bigger as our user base
> is
> > seeing an exponential growth. Today there are variety of data sets
> > available in Hadoop cluster for our users to consume. eBay has around 120
> > PB of data stored in HDFS across 6 different clusters and around 1800+
> > active hadoop users consuming data thru Hive, HBase and mapreduce jobs
> > everyday to build applications using this data. With this astronomical
> > growth of data there are also challenges in securing sensitive data and
> > monitoring the access to this sensitive data. Today in large
> organizations
> > HDFS is the defacto standard for storing big data. Data sets which
> includes
> > and not limited to consumer sentiment, social media data, customer
> > segmentation, web clicks, sensor data, geo-location and transaction data
> > get stored in Hadoop for day to day business needs.
> > > We at eBay want to make sure the sensitive data and data platforms are
> > completely protected from security breaches. So we partnered very closely
> > with our Information Security team to understand the requirements for
> Eagle
> > to monitor sensitive data access on hadoop:
> > > 1.Ability to identify and stop security threats in real time
> > > 2.Scale for big data (Support PB scale and Billions of events)
> > > 3.Ability to create data access policies
> > > 4.Support multiple data sources like HDFS, HBase, Hive
> > > 5.Visualize alerts in real time
> > > 6.Ability to block malicious access in real time
> > > We did not find any data access monitoring solution that available
> today
> > and can provide the features and functionality that we need to monitor
> the
> > data access in the hadoop ecosystem at our scale. Hence with an excellent
> > team of world class developers and several users, we have been able to
> > bring Eagle into production as well as open source it.
> > >
> > > Rationale
> > > In today’s world; data is an important asset for any company.
> Businesses
> > are using data extensively to create amazing experiences for users. Data
> > has to be protected and access to data should be secured from security
> > breaches. Today Hadoop is not only used to store logs but also stores
> > financial data, sensitive data sets, geographical data, user click stream
> > data sets etc. which makes it more important to be protected from
> security
> > breaches. To secure a data platform there are multiple things that need
> to
> > happen. One is having a strong access control mechanism which today is
> > provided by Apache Ranger and Apache Sentry. These tools provide the
> > ability to provide fine grain access control mechanism to data sets on
> > hadoop. But there is a big gap in terms of monitoring all the data access
> > events and activities in order to securing the hadoop data platform.
> > Together with strong access control, perimeter security and data access
> > monitoring in place data in the hadoop clusters can be secured against
> > breaches. We looked around and found following:
> > > Existing data activity monitoring products are designed for traditional
> > databases and data warehouse. Existing monitoring platforms cannot scale
> > out to support fast growing data and petabyte scale. Few products in the
> > industry are still very early in terms of supporting HDFS, Hive, HBase
> data
> > access monitoring.
> > > As mentioned in the background, the business requirement and urgency to
> > secure the data from users with malicious intent drove eBay to invest in
> > building a real time data access monitoring solution from scratch to
> offer
> > real time alerts and remediation features for malicious data access.
> > > With the power of open source distributed systems like Hadoop, Kafka
> and
> > much more we were able to develop a data activity monitoring system that
> > can scale, identify and stop malicious access in real time.
> > > Eagle allows admins to create standard access policies and rules for
> > monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> > machine learning models for modeling user profiles based on user access
> > behaviour and use the model to alert on anomalies.
> > >
> > > Current Status
> > >
> > > Meritocracy
> > > Eagle has been deployed in production at eBay for monitoring billions
> of
> > events per day from HDFS and Hive operations. From the start; the product
> > has been built with focus on high scalability and application
> extensibility
> > in mind and Eagle has demonstrated great performance in responding to
> > suspicious events instantly and great flexibility in defining policy.
> > >
> > > Community
> > > Eagle seeks to develop the developer and user communities during
> > incubation.
> > >
> > > Core Developers
> > > Eagle is currently being designed and developed by engineers from eBay
> > Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> > Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> > these core developers have deep expertise in developing monitoring
> products
> > for the Hadoop ecosystem.
> > >
> > > Alignment
> > > The ASF is a natural host for Eagle given that it is already the home
> of
> > Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> > projects. Eagle leverages lot of Apache open-source products. Eagle was
> > designed to offer real time insights into sensitive data access by
> actively
> > monitoring the data access on various data sets in hadoop and an
> extensible
> > alerting framework with a powerful policy engine. Eagle compliments the
> > existing Hadoop platform area by providing a comprehensive monitoring and
> > alerting solution for detecting sensitive data access threats based on
> > preset policies and machine learning models for user behaviour analysis.
> > >
> > > Known Risks
> > >
> > > Orphaned Products
> > > The core developers of Eagle team work full time on this project. There
> > is no risk of Eagle getting orphaned since eBay is extensively using it
> in
> > their production Hadoop clusters and have plans to go beyond hadoop. For
> > example, currently there are 7 hadoop clusters and 2 of them are being
> > monitored using Hadoop Eagle in production. We have plans to extend it to
> > all hadoop clusters and eventually other data platforms. There are 10’s
> of
> > policies onboarded and actively monitored with plans to onboard more use
> > case. We are very confident that every hadoop cluster in the world will
> be
> > monitored using Eagle for securing the hadoop ecosystem by actively
> > monitoring for data access on sensitive data. We plan to extend and
> > diversify this community further through Apache. We presented Eagle at
> the
> > hadoop summit in china and garnered interest from different companies who
> > use hadoop extensively.
> > >
> > > Inexperience with Open Source
> > > The core developers are all active users and followers of open source.
> > They are already committers and contributors to the Eagle Github project.
> > All have been involved with the source code that has been released under
> an
> > open source license, and several of them also have experience developing
> > code in an open source environment. Though the core set of Developers do
> > not have Apache Open Source experience, there are plans to onboard
> > individuals with Apache open source experience on to the project. Apache
> > Kylin PMC members are also in the same ebay organization. We work very
> > closely with Apache Ranger committers and are looking forward to find
> > meaningful integrations to improve the security of hadoop platform.
> > >
> > > Homogenous Developers
> > > The core developers are from eBay. Today the problem of monitoring data
> > activities to find and stop threats is a universal problem faced by all
> the
> > businesses. Apache Incubation process encourages an open and diverse
> > meritocratic community. Eagle intends to make every possible effort to
> > build a diverse, vibrant and involved community and has already received
> > substantial interest from various organizations.
> > >
> > > Reliance on Salaried Developers
> > > eBay invested in Eagle as the monitoring solution for Hadoop clusters
> > and some of its key engineers are working full time on the project. In
> > addition, since there is a growing need for securing sensitive data
> access
> > we need a data activity monitoring solution for Hadoop, we look forward
> to
> > other Apache developers and researchers to contribute to the project.
> > Additional contributors, including Apache committers have plans to join
> > this effort shortly. Also key to addressing the risk associated with
> > relying on Salaried developers from a single entity is to increase the
> > diversity of the contributors and actively lobby for Domain experts in
> the
> > security space to contribute. Eagle intends to do this.
> > >
> > > Relationships with Other Apache Products
> > > Eagle has a strong relationship and dependency with Apache Hadoop,
> > HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation
> community,
> > could help with a closer collaboration among these projects and as well
> as
> > others. An Excessive Fascination with the Apache Brand Eagle is proposing
> > to enter incubation at Apache in order to help efforts to diversify the
> > committer-base, not so much to capitalize on the Apache brand. The Eagle
> > project is in production use already inside eBay, but is not expected to
> be
> > an eBay product for external customers. As such, the Eagle project is not
> > seeking to use the Apache brand as a marketing tool.
> > >
> > > Documentation
> > > Information about Eagle can be found at https://github.com/eBay/Eagle.
> > The following link provide more information about Eagle
> http://goeagle.io<
> > http://goeagle.io/>.
> > >
> > > Initial Source
> > > Eagle has been under development since 2014 by a team of engineers at
> > eBay Inc. It is currently hosted on Github.com under an Apache license
> 2.0
> > at https://github.com/eBay/Eagle. Once in incubation we will be moving
> > the code base to apache git library.
> > >
> > > External Dependencies
> > > Eagle has the following external dependencies.
> > > Basic
> > > •JDK 1.7+
> > > •Scala 2.10.4
> > > •Apache Maven
> > > •JUnit
> > > •Log4j
> > > •Slf4j
> > > •Apache Commons
> > > •Apache Commons Math3
> > > •Jackson
> > > •Siddhi CEP engine
> > >
> > > Hadoop
> > > •Apache Hadoop
> > > •Apache HBase
> > > •Apache Hive
> > > •Apache Zookeeper
> > > •Apache Curator
> > >
> > > Apache Spark
> > > •Spark Core Library
> > >
> > > REST Service
> > > •Jersey
> > >
> > > Query
> > > •Antlr
> > >
> > > Stream processing
> > > •Apache Storm
> > > •Apache Kafka
> > >
> > > Web
> > > •AngularJS
> > > •jQuery
> > > •Bootstrap V3
> > > •Moment JS
> > > •Admin LTE
> > > •html5shiv
> > > •respond
> > > •Fastclick
> > > •Date Range Picker
> > > •Flot JS
> > >
> > > Cryptography
> > > Eagle will eventually support encryption on the wire. This is not one
> of
> > the initial goals, and we do not expect Eagle to be a controlled export
> > item due to the use of encryption. Eagle supports but does not require
> the
> > Kerberos authentication mechanism to access secured Hadoop services.
> > >
> > > Required Resources
> > >
> > > Mailing List
> > > •eagle-private for private PMC discussions
> > > •eagle-dev for developers
> > > •eagle-commits for all commits
> > > •eagle-users for all eagle users
> > >
> > > Subversion Directory
> > > •Git is the preferred source control system.
> > >
> > > Issue Tracking
> > > •JIRA Eagle (Eagle)
> > >
> > > Other Resources
> > > The existing code already has unit tests so we will make use of
> existing
> > Apache continuous testing infrastructure. The resulting load should not
> be
> > very large.
> > >
> > > Initial Committers
> > > •Seshu Adunuthula <sadunuthula at ebay dot com>
> > > •Arun Manoharan <armanoharan at ebay dot com>
> > > •Edward Zhang <yonzhang at ebay dot com>
> > > •Hao Chen <hchen9 at ebay dot com>
> > > •Chaitali Gupta <cgupta at ebay dot com>
> > > •Libin Sun <libsun at ebay dot com>
> > > •Jilin Jiang <jiljiang at ebay dot com>
> > > •Qingwen Zhao <qingwzhao at ebay dot com>
> > > •Hemanth Dendukuri <hdendukuri at ebay dot com>
> > > •Senthil Kumar <senthilkumar at ebay dot com>
> > >
> > >
> > > Affiliations
> > > The initial committers are employees of eBay Inc.
> > >
> > > Sponsors
> > >
> > > Champion
> > > •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > >
> > > Nominated Mentors
> > > •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> > Hortonworks
> > > •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > > •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> > Hortonworks
> > > •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> > member
> > > •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
> > Hortonworks
> > >
> > > Sponsoring Entity
> > > We are requesting the Incubator to sponsor this project.
> > >
> >
> >
> >
> > ---------------------------------------------------------------------
> > To unsubscribe, e-mail: general-unsubscribe@incubator.apache.org
> > For additional commands, e-mail: general-help@incubator.apache.org
> >
> >
>
>
> --
> Regards,
>
> *Bin Mahone | 马洪宾*
> Apache Kylin: http://kylin.io
> Github: https://github.com/binmahone
>

Re: [VOTE] Accept Eagle into Apache Incubation

[Li Yang <li...@apache.org>]

+1 (non-binding)

On Mon, Oct 26, 2015 at 10:50 AM, hongbin ma <ma...@apache.org> wrote:

> +1 (non binding)
>
> On Mon, Oct 26, 2015 at 12:20 AM, Ralph Goers <ra...@dslextreme.com>
> wrote:
>
> > +1 (binding)
> >
> > Ralph
> >
> > > On Oct 23, 2015, at 7:11 AM, Manoharan, Arun <ar...@ebay.com>
> > wrote:
> > >
> > > Hello Everyone,
> > >
> > > Thanks for all the feedback on the Eagle Proposal.
> > >
> > > I would like to call for a [VOTE] on Eagle joining the ASF as an
> > incubation project.
> > >
> > > The vote is open for 72 hours:
> > >
> > > [ ] +1 accept Eagle in the Incubator
> > > [ ] ±0
> > > [ ] -1 (please give reason)
> > >
> > > Eagle is a Monitoring solution for Hadoop to instantly identify access
> > to sensitive data, recognize attacks, malicious activities and take
> actions
> > in real time. Eagle supports a wide variety of policies on HDFS data and
> > Hive. Eagle also provides machine learning models for detecting anomalous
> > user behavior in Hadoop.
> > >
> > > The proposal is available on the wiki here:
> > > https://wiki.apache.org/incubator/EagleProposal
> > >
> > > The text of the proposal is also available at the end of this email.
> > >
> > > Thanks for your time and help.
> > >
> > > Thanks,
> > > Arun
> > >
> > > <COPY of the proposal in text format>
> > >
> > > Eagle
> > >
> > > Abstract
> > > Eagle is an Open Source Monitoring solution for Hadoop to instantly
> > identify access to sensitive data, recognize attacks, malicious
> activities
> > in hadoop and take actions.
> > >
> > > Proposal
> > > Eagle audits access to HDFS files, Hive and HBase tables in real time,
> > enforces policies defined on sensitive data access and alerts or blocks
> > user’s access to that sensitive data in real time. Eagle also creates
> user
> > profiles based on the typical access behaviour for HDFS and Hive and
> sends
> > alerts when anomalous behaviour is detected. Eagle can also import
> > sensitive data information classified by external classification engines
> to
> > help define its policies.
> > >
> > > Overview of Eagle
> > > Eagle has 3 main parts.
> > > 1.Data collection and storage - Eagle collects data from various hadoop
> > logs in real time using Kafka/Yarn API and uses HDFS and HBase for
> storage.
> > > 2.Data processing and policy engine - Eagle allows users to create
> > policies based on various metadata properties on HDFS, Hive and HBase
> data.
> > > 3.Eagle services - Eagle services include policy manager, query service
> > and the visualization component. Eagle provides intuitive user interface
> to
> > administer Eagle and an alert dashboard to respond to real time alerts.
> > >
> > > Data Collection and Storage:
> > > Eagle provides programming API for extending Eagle to integrate any
> data
> > source into Eagle policy evaluation framework. For example, Eagle hdfs
> > audit monitoring collects data from Kafka which is populated from
> namenode
> > log4j appender or from logstash agent. Eagle hive monitoring collects
> hive
> > query logs from running job through YARN API, which is designed to be
> > scalable and fault-tolerant. Eagle uses HBase as storage for storing
> > metadata and metrics data, and also supports relational database through
> > configuration change.
> > >
> > > Data Processing and Policy Engine:
> > > Processing Engine: Eagle provides stream processing API which is an
> > abstraction of Apache Storm. It can also be extended to other streaming
> > engines. This abstraction allows developers to assemble data
> > transformation, filtering, external data join etc. without physically
> bound
> > to a specific streaming platform. Eagle streaming API allows developers
> to
> > easily integrate business logic with Eagle policy engine and internally
> > Eagle framework compiles business logic execution DAG into program
> > primitives of underlying stream infrastructure e.g. Apache Storm. For
> > example, Eagle HDFS monitoring transforms audit log from Namenode to
> object
> > and joins sensitivity metadata, security zone metadata which are
> generated
> > from external programs or configured by user. Eagle hive monitoring
> filters
> > running jobs to get hive query string and parses query string into object
> > and then joins sensitivity metadata.
> > > Alerting Framework: Eagle Alert Framework includes stream metadata API,
> > scalable policy engine framework, extensible policy engine framework.
> > Stream metadata API allows developers to declare event schema including
> > what attributes constitute an event, what is the type for each attribute,
> > and how to dynamically resolve attribute value in runtime when user
> > configures policy. Scalable policy engine framework allows policies to be
> > executed on different physical nodes in parallel. It is also used to
> define
> > your own policy partitioner class. Policy engine framework together with
> > streaming partitioning capability provided by all streaming platforms
> will
> > make sure policies and events can be evaluated in a fully distributed
> way.
> > Extensible policy engine framework allows developer to plugin a new
> policy
> > engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> > engine which Eagle supports as first-class citizen.
> > > Machine Learning module: Eagle provides capabilities to define user
> > activity patterns or user profiles for Hadoop users based on the user
> > behaviour in the platform. These user profiles are modeled using Machine
> > Learning algorithms and used for detection of anomalous users activities.
> > Eagle uses Eigen Value Decomposition, and Density Estimation algorithms
> for
> > generating user profile models. The model reads data from HDFS audit
> logs,
> > preprocesses and aggregates data, and generates models using Spark
> > programming APIs. Once models are generated, Eagle uses stream processing
> > engine for near real-time anomaly detection to determine if any user’s
> > activities are suspicious or not.
> > >
> > > Eagle Services:
> > > Query Service: Eagle provides SQL-like service API to support
> > comprehensive computation for huge set of data on the fly, for e.g.
> > comprehensive filtering, aggregation, histogram, sorting, top,
> arithmetical
> > expression, pagination etc. HBase is the data storage which Eagle
> supports
> > as first-class citizen, relational database is supported as well. For
> HBase
> > storage, Eagle query framework compiles user provided SQL-like query into
> > HBase native filter objects and execute it through HBase coprocessor on
> the
> > fly.
> > > Policy Manager: Eagle policy manager provides UI and Restful API for
> > user to define policy with just a few clicks. It includes site management
> > UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive
> > resource browsing, alert dashboards etc.
> > > Background
> > > Data is one of the most important assets for today’s businesses, which
> > makes data security one of the top priorities of today’s enterprises.
> > Hadoop is widely used across different verticals as a big data repository
> > to store this data in most modern enterprises.
> > > At eBay we use hadoop platform extensively for our data processing
> > needs. Our data in Hadoop is becoming bigger and bigger as our user base
> is
> > seeing an exponential growth. Today there are variety of data sets
> > available in Hadoop cluster for our users to consume. eBay has around 120
> > PB of data stored in HDFS across 6 different clusters and around 1800+
> > active hadoop users consuming data thru Hive, HBase and mapreduce jobs
> > everyday to build applications using this data. With this astronomical
> > growth of data there are also challenges in securing sensitive data and
> > monitoring the access to this sensitive data. Today in large
> organizations
> > HDFS is the defacto standard for storing big data. Data sets which
> includes
> > and not limited to consumer sentiment, social media data, customer
> > segmentation, web clicks, sensor data, geo-location and transaction data
> > get stored in Hadoop for day to day business needs.
> > > We at eBay want to make sure the sensitive data and data platforms are
> > completely protected from security breaches. So we partnered very closely
> > with our Information Security team to understand the requirements for
> Eagle
> > to monitor sensitive data access on hadoop:
> > > 1.Ability to identify and stop security threats in real time
> > > 2.Scale for big data (Support PB scale and Billions of events)
> > > 3.Ability to create data access policies
> > > 4.Support multiple data sources like HDFS, HBase, Hive
> > > 5.Visualize alerts in real time
> > > 6.Ability to block malicious access in real time
> > > We did not find any data access monitoring solution that available
> today
> > and can provide the features and functionality that we need to monitor
> the
> > data access in the hadoop ecosystem at our scale. Hence with an excellent
> > team of world class developers and several users, we have been able to
> > bring Eagle into production as well as open source it.
> > >
> > > Rationale
> > > In today’s world; data is an important asset for any company.
> Businesses
> > are using data extensively to create amazing experiences for users. Data
> > has to be protected and access to data should be secured from security
> > breaches. Today Hadoop is not only used to store logs but also stores
> > financial data, sensitive data sets, geographical data, user click stream
> > data sets etc. which makes it more important to be protected from
> security
> > breaches. To secure a data platform there are multiple things that need
> to
> > happen. One is having a strong access control mechanism which today is
> > provided by Apache Ranger and Apache Sentry. These tools provide the
> > ability to provide fine grain access control mechanism to data sets on
> > hadoop. But there is a big gap in terms of monitoring all the data access
> > events and activities in order to securing the hadoop data platform.
> > Together with strong access control, perimeter security and data access
> > monitoring in place data in the hadoop clusters can be secured against
> > breaches. We looked around and found following:
> > > Existing data activity monitoring products are designed for traditional
> > databases and data warehouse. Existing monitoring platforms cannot scale
> > out to support fast growing data and petabyte scale. Few products in the
> > industry are still very early in terms of supporting HDFS, Hive, HBase
> data
> > access monitoring.
> > > As mentioned in the background, the business requirement and urgency to
> > secure the data from users with malicious intent drove eBay to invest in
> > building a real time data access monitoring solution from scratch to
> offer
> > real time alerts and remediation features for malicious data access.
> > > With the power of open source distributed systems like Hadoop, Kafka
> and
> > much more we were able to develop a data activity monitoring system that
> > can scale, identify and stop malicious access in real time.
> > > Eagle allows admins to create standard access policies and rules for
> > monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> > machine learning models for modeling user profiles based on user access
> > behaviour and use the model to alert on anomalies.
> > >
> > > Current Status
> > >
> > > Meritocracy
> > > Eagle has been deployed in production at eBay for monitoring billions
> of
> > events per day from HDFS and Hive operations. From the start; the product
> > has been built with focus on high scalability and application
> extensibility
> > in mind and Eagle has demonstrated great performance in responding to
> > suspicious events instantly and great flexibility in defining policy.
> > >
> > > Community
> > > Eagle seeks to develop the developer and user communities during
> > incubation.
> > >
> > > Core Developers
> > > Eagle is currently being designed and developed by engineers from eBay
> > Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> > Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> > these core developers have deep expertise in developing monitoring
> products
> > for the Hadoop ecosystem.
> > >
> > > Alignment
> > > The ASF is a natural host for Eagle given that it is already the home
> of
> > Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> > projects. Eagle leverages lot of Apache open-source products. Eagle was
> > designed to offer real time insights into sensitive data access by
> actively
> > monitoring the data access on various data sets in hadoop and an
> extensible
> > alerting framework with a powerful policy engine. Eagle compliments the
> > existing Hadoop platform area by providing a comprehensive monitoring and
> > alerting solution for detecting sensitive data access threats based on
> > preset policies and machine learning models for user behaviour analysis.
> > >
> > > Known Risks
> > >
> > > Orphaned Products
> > > The core developers of Eagle team work full time on this project. There
> > is no risk of Eagle getting orphaned since eBay is extensively using it
> in
> > their production Hadoop clusters and have plans to go beyond hadoop. For
> > example, currently there are 7 hadoop clusters and 2 of them are being
> > monitored using Hadoop Eagle in production. We have plans to extend it to
> > all hadoop clusters and eventually other data platforms. There are 10’s
> of
> > policies onboarded and actively monitored with plans to onboard more use
> > case. We are very confident that every hadoop cluster in the world will
> be
> > monitored using Eagle for securing the hadoop ecosystem by actively
> > monitoring for data access on sensitive data. We plan to extend and
> > diversify this community further through Apache. We presented Eagle at
> the
> > hadoop summit in china and garnered interest from different companies who
> > use hadoop extensively.
> > >
> > > Inexperience with Open Source
> > > The core developers are all active users and followers of open source.
> > They are already committers and contributors to the Eagle Github project.
> > All have been involved with the source code that has been released under
> an
> > open source license, and several of them also have experience developing
> > code in an open source environment. Though the core set of Developers do
> > not have Apache Open Source experience, there are plans to onboard
> > individuals with Apache open source experience on to the project. Apache
> > Kylin PMC members are also in the same ebay organization. We work very
> > closely with Apache Ranger committers and are looking forward to find
> > meaningful integrations to improve the security of hadoop platform.
> > >
> > > Homogenous Developers
> > > The core developers are from eBay. Today the problem of monitoring data
> > activities to find and stop threats is a universal problem faced by all
> the
> > businesses. Apache Incubation process encourages an open and diverse
> > meritocratic community. Eagle intends to make every possible effort to
> > build a diverse, vibrant and involved community and has already received
> > substantial interest from various organizations.
> > >
> > > Reliance on Salaried Developers
> > > eBay invested in Eagle as the monitoring solution for Hadoop clusters
> > and some of its key engineers are working full time on the project. In
> > addition, since there is a growing need for securing sensitive data
> access
> > we need a data activity monitoring solution for Hadoop, we look forward
> to
> > other Apache developers and researchers to contribute to the project.
> > Additional contributors, including Apache committers have plans to join
> > this effort shortly. Also key to addressing the risk associated with
> > relying on Salaried developers from a single entity is to increase the
> > diversity of the contributors and actively lobby for Domain experts in
> the
> > security space to contribute. Eagle intends to do this.
> > >
> > > Relationships with Other Apache Products
> > > Eagle has a strong relationship and dependency with Apache Hadoop,
> > HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation
> community,
> > could help with a closer collaboration among these projects and as well
> as
> > others. An Excessive Fascination with the Apache Brand Eagle is proposing
> > to enter incubation at Apache in order to help efforts to diversify the
> > committer-base, not so much to capitalize on the Apache brand. The Eagle
> > project is in production use already inside eBay, but is not expected to
> be
> > an eBay product for external customers. As such, the Eagle project is not
> > seeking to use the Apache brand as a marketing tool.
> > >
> > > Documentation
> > > Information about Eagle can be found at https://github.com/eBay/Eagle.
> > The following link provide more information about Eagle
> http://goeagle.io<
> > http://goeagle.io/>.
> > >
> > > Initial Source
> > > Eagle has been under development since 2014 by a team of engineers at
> > eBay Inc. It is currently hosted on Github.com under an Apache license
> 2.0
> > at https://github.com/eBay/Eagle. Once in incubation we will be moving
> > the code base to apache git library.
> > >
> > > External Dependencies
> > > Eagle has the following external dependencies.
> > > Basic
> > > •JDK 1.7+
> > > •Scala 2.10.4
> > > •Apache Maven
> > > •JUnit
> > > •Log4j
> > > •Slf4j
> > > •Apache Commons
> > > •Apache Commons Math3
> > > •Jackson
> > > •Siddhi CEP engine
> > >
> > > Hadoop
> > > •Apache Hadoop
> > > •Apache HBase
> > > •Apache Hive
> > > •Apache Zookeeper
> > > •Apache Curator
> > >
> > > Apache Spark
> > > •Spark Core Library
> > >
> > > REST Service
> > > •Jersey
> > >
> > > Query
> > > •Antlr
> > >
> > > Stream processing
> > > •Apache Storm
> > > •Apache Kafka
> > >
> > > Web
> > > •AngularJS
> > > •jQuery
> > > •Bootstrap V3
> > > •Moment JS
> > > •Admin LTE
> > > •html5shiv
> > > •respond
> > > •Fastclick
> > > •Date Range Picker
> > > •Flot JS
> > >
> > > Cryptography
> > > Eagle will eventually support encryption on the wire. This is not one
> of
> > the initial goals, and we do not expect Eagle to be a controlled export
> > item due to the use of encryption. Eagle supports but does not require
> the
> > Kerberos authentication mechanism to access secured Hadoop services.
> > >
> > > Required Resources
> > >
> > > Mailing List
> > > •eagle-private for private PMC discussions
> > > •eagle-dev for developers
> > > •eagle-commits for all commits
> > > •eagle-users for all eagle users
> > >
> > > Subversion Directory
> > > •Git is the preferred source control system.
> > >
> > > Issue Tracking
> > > •JIRA Eagle (Eagle)
> > >
> > > Other Resources
> > > The existing code already has unit tests so we will make use of
> existing
> > Apache continuous testing infrastructure. The resulting load should not
> be
> > very large.
> > >
> > > Initial Committers
> > > •Seshu Adunuthula <sadunuthula at ebay dot com>
> > > •Arun Manoharan <armanoharan at ebay dot com>
> > > •Edward Zhang <yonzhang at ebay dot com>
> > > •Hao Chen <hchen9 at ebay dot com>
> > > •Chaitali Gupta <cgupta at ebay dot com>
> > > •Libin Sun <libsun at ebay dot com>
> > > •Jilin Jiang <jiljiang at ebay dot com>
> > > •Qingwen Zhao <qingwzhao at ebay dot com>
> > > •Hemanth Dendukuri <hdendukuri at ebay dot com>
> > > •Senthil Kumar <senthilkumar at ebay dot com>
> > >
> > >
> > > Affiliations
> > > The initial committers are employees of eBay Inc.
> > >
> > > Sponsors
> > >
> > > Champion
> > > •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > >
> > > Nominated Mentors
> > > •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> > Hortonworks
> > > •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > > •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> > Hortonworks
> > > •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> > member
> > > •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
> > Hortonworks
> > >
> > > Sponsoring Entity
> > > We are requesting the Incubator to sponsor this project.
> > >
> >
> >
> >
> > ---------------------------------------------------------------------
> > To unsubscribe, e-mail: general-unsubscribe@incubator.apache.org
> > For additional commands, e-mail: general-help@incubator.apache.org
> >
> >
>
>
> --
> Regards,
>
> *Bin Mahone | 马洪宾*
> Apache Kylin: http://kylin.io
> Github: https://github.com/binmahone
>

Re: [VOTE] Accept Eagle into Apache Incubation

[hongbin ma <ma...@apache.org>]

+1 (non binding)

On Mon, Oct 26, 2015 at 12:20 AM, Ralph Goers <ra...@dslextreme.com>
wrote:

> +1 (binding)
>
> Ralph
>
> > On Oct 23, 2015, at 7:11 AM, Manoharan, Arun <ar...@ebay.com>
> wrote:
> >
> > Hello Everyone,
> >
> > Thanks for all the feedback on the Eagle Proposal.
> >
> > I would like to call for a [VOTE] on Eagle joining the ASF as an
> incubation project.
> >
> > The vote is open for 72 hours:
> >
> > [ ] +1 accept Eagle in the Incubator
> > [ ] ±0
> > [ ] -1 (please give reason)
> >
> > Eagle is a Monitoring solution for Hadoop to instantly identify access
> to sensitive data, recognize attacks, malicious activities and take actions
> in real time. Eagle supports a wide variety of policies on HDFS data and
> Hive. Eagle also provides machine learning models for detecting anomalous
> user behavior in Hadoop.
> >
> > The proposal is available on the wiki here:
> > https://wiki.apache.org/incubator/EagleProposal
> >
> > The text of the proposal is also available at the end of this email.
> >
> > Thanks for your time and help.
> >
> > Thanks,
> > Arun
> >
> > <COPY of the proposal in text format>
> >
> > Eagle
> >
> > Abstract
> > Eagle is an Open Source Monitoring solution for Hadoop to instantly
> identify access to sensitive data, recognize attacks, malicious activities
> in hadoop and take actions.
> >
> > Proposal
> > Eagle audits access to HDFS files, Hive and HBase tables in real time,
> enforces policies defined on sensitive data access and alerts or blocks
> user’s access to that sensitive data in real time. Eagle also creates user
> profiles based on the typical access behaviour for HDFS and Hive and sends
> alerts when anomalous behaviour is detected. Eagle can also import
> sensitive data information classified by external classification engines to
> help define its policies.
> >
> > Overview of Eagle
> > Eagle has 3 main parts.
> > 1.Data collection and storage - Eagle collects data from various hadoop
> logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> > 2.Data processing and policy engine - Eagle allows users to create
> policies based on various metadata properties on HDFS, Hive and HBase data.
> > 3.Eagle services - Eagle services include policy manager, query service
> and the visualization component. Eagle provides intuitive user interface to
> administer Eagle and an alert dashboard to respond to real time alerts.
> >
> > Data Collection and Storage:
> > Eagle provides programming API for extending Eagle to integrate any data
> source into Eagle policy evaluation framework. For example, Eagle hdfs
> audit monitoring collects data from Kafka which is populated from namenode
> log4j appender or from logstash agent. Eagle hive monitoring collects hive
> query logs from running job through YARN API, which is designed to be
> scalable and fault-tolerant. Eagle uses HBase as storage for storing
> metadata and metrics data, and also supports relational database through
> configuration change.
> >
> > Data Processing and Policy Engine:
> > Processing Engine: Eagle provides stream processing API which is an
> abstraction of Apache Storm. It can also be extended to other streaming
> engines. This abstraction allows developers to assemble data
> transformation, filtering, external data join etc. without physically bound
> to a specific streaming platform. Eagle streaming API allows developers to
> easily integrate business logic with Eagle policy engine and internally
> Eagle framework compiles business logic execution DAG into program
> primitives of underlying stream infrastructure e.g. Apache Storm. For
> example, Eagle HDFS monitoring transforms audit log from Namenode to object
> and joins sensitivity metadata, security zone metadata which are generated
> from external programs or configured by user. Eagle hive monitoring filters
> running jobs to get hive query string and parses query string into object
> and then joins sensitivity metadata.
> > Alerting Framework: Eagle Alert Framework includes stream metadata API,
> scalable policy engine framework, extensible policy engine framework.
> Stream metadata API allows developers to declare event schema including
> what attributes constitute an event, what is the type for each attribute,
> and how to dynamically resolve attribute value in runtime when user
> configures policy. Scalable policy engine framework allows policies to be
> executed on different physical nodes in parallel. It is also used to define
> your own policy partitioner class. Policy engine framework together with
> streaming partitioning capability provided by all streaming platforms will
> make sure policies and events can be evaluated in a fully distributed way.
> Extensible policy engine framework allows developer to plugin a new policy
> engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> engine which Eagle supports as first-class citizen.
> > Machine Learning module: Eagle provides capabilities to define user
> activity patterns or user profiles for Hadoop users based on the user
> behaviour in the platform. These user profiles are modeled using Machine
> Learning algorithms and used for detection of anomalous users activities.
> Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for
> generating user profile models. The model reads data from HDFS audit logs,
> preprocesses and aggregates data, and generates models using Spark
> programming APIs. Once models are generated, Eagle uses stream processing
> engine for near real-time anomaly detection to determine if any user’s
> activities are suspicious or not.
> >
> > Eagle Services:
> > Query Service: Eagle provides SQL-like service API to support
> comprehensive computation for huge set of data on the fly, for e.g.
> comprehensive filtering, aggregation, histogram, sorting, top, arithmetical
> expression, pagination etc. HBase is the data storage which Eagle supports
> as first-class citizen, relational database is supported as well. For HBase
> storage, Eagle query framework compiles user provided SQL-like query into
> HBase native filter objects and execute it through HBase coprocessor on the
> fly.
> > Policy Manager: Eagle policy manager provides UI and Restful API for
> user to define policy with just a few clicks. It includes site management
> UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive
> resource browsing, alert dashboards etc.
> > Background
> > Data is one of the most important assets for today’s businesses, which
> makes data security one of the top priorities of today’s enterprises.
> Hadoop is widely used across different verticals as a big data repository
> to store this data in most modern enterprises.
> > At eBay we use hadoop platform extensively for our data processing
> needs. Our data in Hadoop is becoming bigger and bigger as our user base is
> seeing an exponential growth. Today there are variety of data sets
> available in Hadoop cluster for our users to consume. eBay has around 120
> PB of data stored in HDFS across 6 different clusters and around 1800+
> active hadoop users consuming data thru Hive, HBase and mapreduce jobs
> everyday to build applications using this data. With this astronomical
> growth of data there are also challenges in securing sensitive data and
> monitoring the access to this sensitive data. Today in large organizations
> HDFS is the defacto standard for storing big data. Data sets which includes
> and not limited to consumer sentiment, social media data, customer
> segmentation, web clicks, sensor data, geo-location and transaction data
> get stored in Hadoop for day to day business needs.
> > We at eBay want to make sure the sensitive data and data platforms are
> completely protected from security breaches. So we partnered very closely
> with our Information Security team to understand the requirements for Eagle
> to monitor sensitive data access on hadoop:
> > 1.Ability to identify and stop security threats in real time
> > 2.Scale for big data (Support PB scale and Billions of events)
> > 3.Ability to create data access policies
> > 4.Support multiple data sources like HDFS, HBase, Hive
> > 5.Visualize alerts in real time
> > 6.Ability to block malicious access in real time
> > We did not find any data access monitoring solution that available today
> and can provide the features and functionality that we need to monitor the
> data access in the hadoop ecosystem at our scale. Hence with an excellent
> team of world class developers and several users, we have been able to
> bring Eagle into production as well as open source it.
> >
> > Rationale
> > In today’s world; data is an important asset for any company. Businesses
> are using data extensively to create amazing experiences for users. Data
> has to be protected and access to data should be secured from security
> breaches. Today Hadoop is not only used to store logs but also stores
> financial data, sensitive data sets, geographical data, user click stream
> data sets etc. which makes it more important to be protected from security
> breaches. To secure a data platform there are multiple things that need to
> happen. One is having a strong access control mechanism which today is
> provided by Apache Ranger and Apache Sentry. These tools provide the
> ability to provide fine grain access control mechanism to data sets on
> hadoop. But there is a big gap in terms of monitoring all the data access
> events and activities in order to securing the hadoop data platform.
> Together with strong access control, perimeter security and data access
> monitoring in place data in the hadoop clusters can be secured against
> breaches. We looked around and found following:
> > Existing data activity monitoring products are designed for traditional
> databases and data warehouse. Existing monitoring platforms cannot scale
> out to support fast growing data and petabyte scale. Few products in the
> industry are still very early in terms of supporting HDFS, Hive, HBase data
> access monitoring.
> > As mentioned in the background, the business requirement and urgency to
> secure the data from users with malicious intent drove eBay to invest in
> building a real time data access monitoring solution from scratch to offer
> real time alerts and remediation features for malicious data access.
> > With the power of open source distributed systems like Hadoop, Kafka and
> much more we were able to develop a data activity monitoring system that
> can scale, identify and stop malicious access in real time.
> > Eagle allows admins to create standard access policies and rules for
> monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> machine learning models for modeling user profiles based on user access
> behaviour and use the model to alert on anomalies.
> >
> > Current Status
> >
> > Meritocracy
> > Eagle has been deployed in production at eBay for monitoring billions of
> events per day from HDFS and Hive operations. From the start; the product
> has been built with focus on high scalability and application extensibility
> in mind and Eagle has demonstrated great performance in responding to
> suspicious events instantly and great flexibility in defining policy.
> >
> > Community
> > Eagle seeks to develop the developer and user communities during
> incubation.
> >
> > Core Developers
> > Eagle is currently being designed and developed by engineers from eBay
> Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> these core developers have deep expertise in developing monitoring products
> for the Hadoop ecosystem.
> >
> > Alignment
> > The ASF is a natural host for Eagle given that it is already the home of
> Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> projects. Eagle leverages lot of Apache open-source products. Eagle was
> designed to offer real time insights into sensitive data access by actively
> monitoring the data access on various data sets in hadoop and an extensible
> alerting framework with a powerful policy engine. Eagle compliments the
> existing Hadoop platform area by providing a comprehensive monitoring and
> alerting solution for detecting sensitive data access threats based on
> preset policies and machine learning models for user behaviour analysis.
> >
> > Known Risks
> >
> > Orphaned Products
> > The core developers of Eagle team work full time on this project. There
> is no risk of Eagle getting orphaned since eBay is extensively using it in
> their production Hadoop clusters and have plans to go beyond hadoop. For
> example, currently there are 7 hadoop clusters and 2 of them are being
> monitored using Hadoop Eagle in production. We have plans to extend it to
> all hadoop clusters and eventually other data platforms. There are 10’s of
> policies onboarded and actively monitored with plans to onboard more use
> case. We are very confident that every hadoop cluster in the world will be
> monitored using Eagle for securing the hadoop ecosystem by actively
> monitoring for data access on sensitive data. We plan to extend and
> diversify this community further through Apache. We presented Eagle at the
> hadoop summit in china and garnered interest from different companies who
> use hadoop extensively.
> >
> > Inexperience with Open Source
> > The core developers are all active users and followers of open source.
> They are already committers and contributors to the Eagle Github project.
> All have been involved with the source code that has been released under an
> open source license, and several of them also have experience developing
> code in an open source environment. Though the core set of Developers do
> not have Apache Open Source experience, there are plans to onboard
> individuals with Apache open source experience on to the project. Apache
> Kylin PMC members are also in the same ebay organization. We work very
> closely with Apache Ranger committers and are looking forward to find
> meaningful integrations to improve the security of hadoop platform.
> >
> > Homogenous Developers
> > The core developers are from eBay. Today the problem of monitoring data
> activities to find and stop threats is a universal problem faced by all the
> businesses. Apache Incubation process encourages an open and diverse
> meritocratic community. Eagle intends to make every possible effort to
> build a diverse, vibrant and involved community and has already received
> substantial interest from various organizations.
> >
> > Reliance on Salaried Developers
> > eBay invested in Eagle as the monitoring solution for Hadoop clusters
> and some of its key engineers are working full time on the project. In
> addition, since there is a growing need for securing sensitive data access
> we need a data activity monitoring solution for Hadoop, we look forward to
> other Apache developers and researchers to contribute to the project.
> Additional contributors, including Apache committers have plans to join
> this effort shortly. Also key to addressing the risk associated with
> relying on Salaried developers from a single entity is to increase the
> diversity of the contributors and actively lobby for Domain experts in the
> security space to contribute. Eagle intends to do this.
> >
> > Relationships with Other Apache Products
> > Eagle has a strong relationship and dependency with Apache Hadoop,
> HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation community,
> could help with a closer collaboration among these projects and as well as
> others. An Excessive Fascination with the Apache Brand Eagle is proposing
> to enter incubation at Apache in order to help efforts to diversify the
> committer-base, not so much to capitalize on the Apache brand. The Eagle
> project is in production use already inside eBay, but is not expected to be
> an eBay product for external customers. As such, the Eagle project is not
> seeking to use the Apache brand as a marketing tool.
> >
> > Documentation
> > Information about Eagle can be found at https://github.com/eBay/Eagle.
> The following link provide more information about Eagle http://goeagle.io<
> http://goeagle.io/>.
> >
> > Initial Source
> > Eagle has been under development since 2014 by a team of engineers at
> eBay Inc. It is currently hosted on Github.com under an Apache license 2.0
> at https://github.com/eBay/Eagle. Once in incubation we will be moving
> the code base to apache git library.
> >
> > External Dependencies
> > Eagle has the following external dependencies.
> > Basic
> > •JDK 1.7+
> > •Scala 2.10.4
> > •Apache Maven
> > •JUnit
> > •Log4j
> > •Slf4j
> > •Apache Commons
> > •Apache Commons Math3
> > •Jackson
> > •Siddhi CEP engine
> >
> > Hadoop
> > •Apache Hadoop
> > •Apache HBase
> > •Apache Hive
> > •Apache Zookeeper
> > •Apache Curator
> >
> > Apache Spark
> > •Spark Core Library
> >
> > REST Service
> > •Jersey
> >
> > Query
> > •Antlr
> >
> > Stream processing
> > •Apache Storm
> > •Apache Kafka
> >
> > Web
> > •AngularJS
> > •jQuery
> > •Bootstrap V3
> > •Moment JS
> > •Admin LTE
> > •html5shiv
> > •respond
> > •Fastclick
> > •Date Range Picker
> > •Flot JS
> >
> > Cryptography
> > Eagle will eventually support encryption on the wire. This is not one of
> the initial goals, and we do not expect Eagle to be a controlled export
> item due to the use of encryption. Eagle supports but does not require the
> Kerberos authentication mechanism to access secured Hadoop services.
> >
> > Required Resources
> >
> > Mailing List
> > •eagle-private for private PMC discussions
> > •eagle-dev for developers
> > •eagle-commits for all commits
> > •eagle-users for all eagle users
> >
> > Subversion Directory
> > •Git is the preferred source control system.
> >
> > Issue Tracking
> > •JIRA Eagle (Eagle)
> >
> > Other Resources
> > The existing code already has unit tests so we will make use of existing
> Apache continuous testing infrastructure. The resulting load should not be
> very large.
> >
> > Initial Committers
> > •Seshu Adunuthula <sadunuthula at ebay dot com>
> > •Arun Manoharan <armanoharan at ebay dot com>
> > •Edward Zhang <yonzhang at ebay dot com>
> > •Hao Chen <hchen9 at ebay dot com>
> > •Chaitali Gupta <cgupta at ebay dot com>
> > •Libin Sun <libsun at ebay dot com>
> > •Jilin Jiang <jiljiang at ebay dot com>
> > •Qingwen Zhao <qingwzhao at ebay dot com>
> > •Hemanth Dendukuri <hdendukuri at ebay dot com>
> > •Senthil Kumar <senthilkumar at ebay dot com>
> >
> >
> > Affiliations
> > The initial committers are employees of eBay Inc.
> >
> > Sponsors
> >
> > Champion
> > •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> >
> > Nominated Mentors
> > •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> Hortonworks
> > •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> Hortonworks
> > •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> member
> > •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
> Hortonworks
> >
> > Sponsoring Entity
> > We are requesting the Incubator to sponsor this project.
> >
>
>
>
> ---------------------------------------------------------------------
> To unsubscribe, e-mail: general-unsubscribe@incubator.apache.org
> For additional commands, e-mail: general-help@incubator.apache.org
>
>


-- 
Regards,

*Bin Mahone | 马洪宾*
Apache Kylin: http://kylin.io
Github: https://github.com/binmahone

Re: [VOTE] Accept Eagle into Apache Incubation

[Ralph Goers <ra...@dslextreme.com>]

+1 (binding)

Ralph

> On Oct 23, 2015, at 7:11 AM, Manoharan, Arun <ar...@ebay.com> wrote:
> 
> Hello Everyone,
> 
> Thanks for all the feedback on the Eagle Proposal.
> 
> I would like to call for a [VOTE] on Eagle joining the ASF as an incubation project.
> 
> The vote is open for 72 hours:
> 
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
> 
> Eagle is a Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities and take actions in real time. Eagle supports a wide variety of policies on HDFS data and Hive. Eagle also provides machine learning models for detecting anomalous user behavior in Hadoop.
> 
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
> 
> The text of the proposal is also available at the end of this email.
> 
> Thanks for your time and help.
> 
> Thanks,
> Arun
> 
> <COPY of the proposal in text format>
> 
> Eagle
> 
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities in hadoop and take actions.
> 
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time, enforces policies defined on sensitive data access and alerts or blocks user’s access to that sensitive data in real time. Eagle also creates user profiles based on the typical access behaviour for HDFS and Hive and sends alerts when anomalous behaviour is detected. Eagle can also import sensitive data information classified by external classification engines to help define its policies.
> 
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service and the visualization component. Eagle provides intuitive user interface to administer Eagle and an alert dashboard to respond to real time alerts.
> 
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data source into Eagle policy evaluation framework. For example, Eagle hdfs audit monitoring collects data from Kafka which is populated from namenode log4j appender or from logstash agent. Eagle hive monitoring collects hive query logs from running job through YARN API, which is designed to be scalable and fault-tolerant. Eagle uses HBase as storage for storing metadata and metrics data, and also supports relational database through configuration change.
> 
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an abstraction of Apache Storm. It can also be extended to other streaming engines. This abstraction allows developers to assemble data transformation, filtering, external data join etc. without physically bound to a specific streaming platform. Eagle streaming API allows developers to easily integrate business logic with Eagle policy engine and internally Eagle framework compiles business logic execution DAG into program primitives of underlying stream infrastructure e.g. Apache Storm. For example, Eagle HDFS monitoring transforms audit log from Namenode to object and joins sensitivity metadata, security zone metadata which are generated from external programs or configured by user. Eagle hive monitoring filters running jobs to get hive query string and parses query string into object and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API, scalable policy engine framework, extensible policy engine framework. Stream metadata API allows developers to declare event schema including what attributes constitute an event, what is the type for each attribute, and how to dynamically resolve attribute value in runtime when user configures policy. Scalable policy engine framework allows policies to be executed on different physical nodes in parallel. It is also used to define your own policy partitioner class. Policy engine framework together with streaming partitioning capability provided by all streaming platforms will make sure policies and events can be evaluated in a fully distributed way. Extensible policy engine framework allows developer to plugin a new policy engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user activity patterns or user profiles for Hadoop users based on the user behaviour in the platform. These user profiles are modeled using Machine Learning algorithms and used for detection of anomalous users activities. Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for generating user profile models. The model reads data from HDFS audit logs, preprocesses and aggregates data, and generates models using Spark programming APIs. Once models are generated, Eagle uses stream processing engine for near real-time anomaly detection to determine if any user’s activities are suspicious or not.
> 
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support comprehensive computation for huge set of data on the fly, for e.g. comprehensive filtering, aggregation, histogram, sorting, top, arithmetical expression, pagination etc. HBase is the data storage which Eagle supports as first-class citizen, relational database is supported as well. For HBase storage, Eagle query framework compiles user provided SQL-like query into HBase native filter objects and execute it through HBase coprocessor on the fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user to define policy with just a few clicks. It includes site management UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive resource browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which makes data security one of the top priorities of today’s enterprises. Hadoop is widely used across different verticals as a big data repository to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs. Our data in Hadoop is becoming bigger and bigger as our user base is seeing an exponential growth. Today there are variety of data sets available in Hadoop cluster for our users to consume. eBay has around 120 PB of data stored in HDFS across 6 different clusters and around 1800+ active hadoop users consuming data thru Hive, HBase and mapreduce jobs everyday to build applications using this data. With this astronomical growth of data there are also challenges in securing sensitive data and monitoring the access to this sensitive data. Today in large organizations HDFS is the defacto standard for storing big data. Data sets which includes and not limited to consumer sentiment, social media data, customer segmentation, web clicks, sensor data, geo-location and transaction data get stored in Hadoop for day to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are completely protected from security breaches. So we partnered very closely with our Information Security team to understand the requirements for Eagle to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today and can provide the features and functionality that we need to monitor the data access in the hadoop ecosystem at our scale. Hence with an excellent team of world class developers and several users, we have been able to bring Eagle into production as well as open source it.
> 
> Rationale
> In today’s world; data is an important asset for any company. Businesses are using data extensively to create amazing experiences for users. Data has to be protected and access to data should be secured from security breaches. Today Hadoop is not only used to store logs but also stores financial data, sensitive data sets, geographical data, user click stream data sets etc. which makes it more important to be protected from security breaches. To secure a data platform there are multiple things that need to happen. One is having a strong access control mechanism which today is provided by Apache Ranger and Apache Sentry. These tools provide the ability to provide fine grain access control mechanism to data sets on hadoop. But there is a big gap in terms of monitoring all the data access events and activities in order to securing the hadoop data platform. Together with strong access control, perimeter security and data access monitoring in place data in the hadoop clusters can be secured against breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional databases and data warehouse. Existing monitoring platforms cannot scale out to support fast growing data and petabyte scale. Few products in the industry are still very early in terms of supporting HDFS, Hive, HBase data access monitoring.
> As mentioned in the background, the business requirement and urgency to secure the data from users with malicious intent drove eBay to invest in building a real time data access monitoring solution from scratch to offer real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and much more we were able to develop a data activity monitoring system that can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for monitoring HDFS, Hive and HBase data. Eagle also provides out of box machine learning models for modeling user profiles based on user access behaviour and use the model to alert on anomalies.
> 
> Current Status
> 
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of events per day from HDFS and Hive operations. From the start; the product has been built with focus on high scalability and application extensibility in mind and Eagle has demonstrated great performance in responding to suspicious events instantly and great flexibility in defining policy.
> 
> Community
> Eagle seeks to develop the developer and user communities during incubation.
> 
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang, Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of these core developers have deep expertise in developing monitoring products for the Hadoop ecosystem.
> 
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data projects. Eagle leverages lot of Apache open-source products. Eagle was designed to offer real time insights into sensitive data access by actively monitoring the data access on various data sets in hadoop and an extensible alerting framework with a powerful policy engine. Eagle compliments the existing Hadoop platform area by providing a comprehensive monitoring and alerting solution for detecting sensitive data access threats based on preset policies and machine learning models for user behaviour analysis.
> 
> Known Risks
> 
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is no risk of Eagle getting orphaned since eBay is extensively using it in their production Hadoop clusters and have plans to go beyond hadoop. For example, currently there are 7 hadoop clusters and 2 of them are being monitored using Hadoop Eagle in production. We have plans to extend it to all hadoop clusters and eventually other data platforms. There are 10’s of policies onboarded and actively monitored with plans to onboard more use case. We are very confident that every hadoop cluster in the world will be monitored using Eagle for securing the hadoop ecosystem by actively monitoring for data access on sensitive data. We plan to extend and diversify this community further through Apache. We presented Eagle at the hadoop summit in china and garnered interest from different companies who use hadoop extensively.
> 
> Inexperience with Open Source
> The core developers are all active users and followers of open source. They are already committers and contributors to the Eagle Github project. All have been involved with the source code that has been released under an open source license, and several of them also have experience developing code in an open source environment. Though the core set of Developers do not have Apache Open Source experience, there are plans to onboard individuals with Apache open source experience on to the project. Apache Kylin PMC members are also in the same ebay organization. We work very closely with Apache Ranger committers and are looking forward to find meaningful integrations to improve the security of hadoop platform.
> 
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data activities to find and stop threats is a universal problem faced by all the businesses. Apache Incubation process encourages an open and diverse meritocratic community. Eagle intends to make every possible effort to build a diverse, vibrant and involved community and has already received substantial interest from various organizations.
> 
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and some of its key engineers are working full time on the project. In addition, since there is a growing need for securing sensitive data access we need a data activity monitoring solution for Hadoop, we look forward to other Apache developers and researchers to contribute to the project. Additional contributors, including Apache committers have plans to join this effort shortly. Also key to addressing the risk associated with relying on Salaried developers from a single entity is to increase the diversity of the contributors and actively lobby for Domain experts in the security space to contribute. Eagle intends to do this.
> 
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation community, could help with a closer collaboration among these projects and as well as others. An Excessive Fascination with the Apache Brand Eagle is proposing to enter incubation at Apache in order to help efforts to diversify the committer-base, not so much to capitalize on the Apache brand. The Eagle project is in production use already inside eBay, but is not expected to be an eBay product for external customers. As such, the Eagle project is not seeking to use the Apache brand as a marketing tool.
> 
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle. The following link provide more information about Eagle http://goeagle.io<http://goeagle.io/>.
> 
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay Inc. It is currently hosted on Github.com under an Apache license 2.0 at https://github.com/eBay/Eagle. Once in incubation we will be moving the code base to apache git library.
> 
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
> 
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
> 
> Apache Spark
> •Spark Core Library
> 
> REST Service
> •Jersey
> 
> Query
> •Antlr
> 
> Stream processing
> •Apache Storm
> •Apache Kafka
> 
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
> 
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of the initial goals, and we do not expect Eagle to be a controlled export item due to the use of encryption. Eagle supports but does not require the Kerberos authentication mechanism to access secured Hadoop services.
> 
> Required Resources
> 
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
> 
> Subversion Directory
> •Git is the preferred source control system.
> 
> Issue Tracking
> •JIRA Eagle (Eagle)
> 
> Other Resources
> The existing code already has unit tests so we will make use of existing Apache continuous testing infrastructure. The resulting load should not be very large.
> 
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
> 
> 
> Affiliations
> The initial committers are employees of eBay Inc.
> 
> Sponsors
> 
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> 
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member, Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member, Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
> 
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
> 



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Re: [VOTE] Accept Eagle into Apache Incubation

[Henry Saputra <he...@gmail.com>]

+1 (binding)

On Fri, Oct 23, 2015 at 7:11 AM, Manoharan, Arun <ar...@ebay.com> wrote:
> Hello Everyone,
>
> Thanks for all the feedback on the Eagle Proposal.
>
> I would like to call for a [VOTE] on Eagle joining the ASF as an incubation project.
>
> The vote is open for 72 hours:
>
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
>
> Eagle is a Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities and take actions in real time. Eagle supports a wide variety of policies on HDFS data and Hive. Eagle also provides machine learning models for detecting anomalous user behavior in Hadoop.
>
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
>
> The text of the proposal is also available at the end of this email.
>
> Thanks for your time and help.
>
> Thanks,
> Arun
>
> <COPY of the proposal in text format>
>
> Eagle
>
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities in hadoop and take actions.
>
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time, enforces policies defined on sensitive data access and alerts or blocks user’s access to that sensitive data in real time. Eagle also creates user profiles based on the typical access behaviour for HDFS and Hive and sends alerts when anomalous behaviour is detected. Eagle can also import sensitive data information classified by external classification engines to help define its policies.
>
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service and the visualization component. Eagle provides intuitive user interface to administer Eagle and an alert dashboard to respond to real time alerts.
>
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data source into Eagle policy evaluation framework. For example, Eagle hdfs audit monitoring collects data from Kafka which is populated from namenode log4j appender or from logstash agent. Eagle hive monitoring collects hive query logs from running job through YARN API, which is designed to be scalable and fault-tolerant. Eagle uses HBase as storage for storing metadata and metrics data, and also supports relational database through configuration change.
>
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an abstraction of Apache Storm. It can also be extended to other streaming engines. This abstraction allows developers to assemble data transformation, filtering, external data join etc. without physically bound to a specific streaming platform. Eagle streaming API allows developers to easily integrate business logic with Eagle policy engine and internally Eagle framework compiles business logic execution DAG into program primitives of underlying stream infrastructure e.g. Apache Storm. For example, Eagle HDFS monitoring transforms audit log from Namenode to object and joins sensitivity metadata, security zone metadata which are generated from external programs or configured by user. Eagle hive monitoring filters running jobs to get hive query string and parses query string into object and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API, scalable policy engine framework, extensible policy engine framework. Stream metadata API allows developers to declare event schema including what attributes constitute an event, what is the type for each attribute, and how to dynamically resolve attribute value in runtime when user configures policy. Scalable policy engine framework allows policies to be executed on different physical nodes in parallel. It is also used to define your own policy partitioner class. Policy engine framework together with streaming partitioning capability provided by all streaming platforms will make sure policies and events can be evaluated in a fully distributed way. Extensible policy engine framework allows developer to plugin a new policy engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user activity patterns or user profiles for Hadoop users based on the user behaviour in the platform. These user profiles are modeled using Machine Learning algorithms and used for detection of anomalous users activities. Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for generating user profile models. The model reads data from HDFS audit logs, preprocesses and aggregates data, and generates models using Spark programming APIs. Once models are generated, Eagle uses stream processing engine for near real-time anomaly detection to determine if any user’s activities are suspicious or not.
>
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support comprehensive computation for huge set of data on the fly, for e.g. comprehensive filtering, aggregation, histogram, sorting, top, arithmetical expression, pagination etc. HBase is the data storage which Eagle supports as first-class citizen, relational database is supported as well. For HBase storage, Eagle query framework compiles user provided SQL-like query into HBase native filter objects and execute it through HBase coprocessor on the fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user to define policy with just a few clicks. It includes site management UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive resource browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which makes data security one of the top priorities of today’s enterprises. Hadoop is widely used across different verticals as a big data repository to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs. Our data in Hadoop is becoming bigger and bigger as our user base is seeing an exponential growth. Today there are variety of data sets available in Hadoop cluster for our users to consume. eBay has around 120 PB of data stored in HDFS across 6 different clusters and around 1800+ active hadoop users consuming data thru Hive, HBase and mapreduce jobs everyday to build applications using this data. With this astronomical growth of data there are also challenges in securing sensitive data and monitoring the access to this sensitive data. Today in large organizations HDFS is the defacto standard for storing big data. Data sets which includes and not limited to consumer sentiment, social media data, customer segmentation, web clicks, sensor data, geo-location and transaction data get stored in Hadoop for day to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are completely protected from security breaches. So we partnered very closely with our Information Security team to understand the requirements for Eagle to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today and can provide the features and functionality that we need to monitor the data access in the hadoop ecosystem at our scale. Hence with an excellent team of world class developers and several users, we have been able to bring Eagle into production as well as open source it.
>
> Rationale
> In today’s world; data is an important asset for any company. Businesses are using data extensively to create amazing experiences for users. Data has to be protected and access to data should be secured from security breaches. Today Hadoop is not only used to store logs but also stores financial data, sensitive data sets, geographical data, user click stream data sets etc. which makes it more important to be protected from security breaches. To secure a data platform there are multiple things that need to happen. One is having a strong access control mechanism which today is provided by Apache Ranger and Apache Sentry. These tools provide the ability to provide fine grain access control mechanism to data sets on hadoop. But there is a big gap in terms of monitoring all the data access events and activities in order to securing the hadoop data platform. Together with strong access control, perimeter security and data access monitoring in place data in the hadoop clusters can be secured against breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional databases and data warehouse. Existing monitoring platforms cannot scale out to support fast growing data and petabyte scale. Few products in the industry are still very early in terms of supporting HDFS, Hive, HBase data access monitoring.
> As mentioned in the background, the business requirement and urgency to secure the data from users with malicious intent drove eBay to invest in building a real time data access monitoring solution from scratch to offer real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and much more we were able to develop a data activity monitoring system that can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for monitoring HDFS, Hive and HBase data. Eagle also provides out of box machine learning models for modeling user profiles based on user access behaviour and use the model to alert on anomalies.
>
> Current Status
>
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of events per day from HDFS and Hive operations. From the start; the product has been built with focus on high scalability and application extensibility in mind and Eagle has demonstrated great performance in responding to suspicious events instantly and great flexibility in defining policy.
>
> Community
> Eagle seeks to develop the developer and user communities during incubation.
>
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang, Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of these core developers have deep expertise in developing monitoring products for the Hadoop ecosystem.
>
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data projects. Eagle leverages lot of Apache open-source products. Eagle was designed to offer real time insights into sensitive data access by actively monitoring the data access on various data sets in hadoop and an extensible alerting framework with a powerful policy engine. Eagle compliments the existing Hadoop platform area by providing a comprehensive monitoring and alerting solution for detecting sensitive data access threats based on preset policies and machine learning models for user behaviour analysis.
>
> Known Risks
>
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is no risk of Eagle getting orphaned since eBay is extensively using it in their production Hadoop clusters and have plans to go beyond hadoop. For example, currently there are 7 hadoop clusters and 2 of them are being monitored using Hadoop Eagle in production. We have plans to extend it to all hadoop clusters and eventually other data platforms. There are 10’s of policies onboarded and actively monitored with plans to onboard more use case. We are very confident that every hadoop cluster in the world will be monitored using Eagle for securing the hadoop ecosystem by actively monitoring for data access on sensitive data. We plan to extend and diversify this community further through Apache. We presented Eagle at the hadoop summit in china and garnered interest from different companies who use hadoop extensively.
>
> Inexperience with Open Source
> The core developers are all active users and followers of open source. They are already committers and contributors to the Eagle Github project. All have been involved with the source code that has been released under an open source license, and several of them also have experience developing code in an open source environment. Though the core set of Developers do not have Apache Open Source experience, there are plans to onboard individuals with Apache open source experience on to the project. Apache Kylin PMC members are also in the same ebay organization. We work very closely with Apache Ranger committers and are looking forward to find meaningful integrations to improve the security of hadoop platform.
>
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data activities to find and stop threats is a universal problem faced by all the businesses. Apache Incubation process encourages an open and diverse meritocratic community. Eagle intends to make every possible effort to build a diverse, vibrant and involved community and has already received substantial interest from various organizations.
>
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and some of its key engineers are working full time on the project. In addition, since there is a growing need for securing sensitive data access we need a data activity monitoring solution for Hadoop, we look forward to other Apache developers and researchers to contribute to the project. Additional contributors, including Apache committers have plans to join this effort shortly. Also key to addressing the risk associated with relying on Salaried developers from a single entity is to increase the diversity of the contributors and actively lobby for Domain experts in the security space to contribute. Eagle intends to do this.
>
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation community, could help with a closer collaboration among these projects and as well as others. An Excessive Fascination with the Apache Brand Eagle is proposing to enter incubation at Apache in order to help efforts to diversify the committer-base, not so much to capitalize on the Apache brand. The Eagle project is in production use already inside eBay, but is not expected to be an eBay product for external customers. As such, the Eagle project is not seeking to use the Apache brand as a marketing tool.
>
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle. The following link provide more information about Eagle http://goeagle.io<http://goeagle.io/>.
>
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay Inc. It is currently hosted on Github.com under an Apache license 2.0 at https://github.com/eBay/Eagle. Once in incubation we will be moving the code base to apache git library.
>
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
>
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
>
> Apache Spark
> •Spark Core Library
>
> REST Service
> •Jersey
>
> Query
> •Antlr
>
> Stream processing
> •Apache Storm
> •Apache Kafka
>
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
>
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of the initial goals, and we do not expect Eagle to be a controlled export item due to the use of encryption. Eagle supports but does not require the Kerberos authentication mechanism to access secured Hadoop services.
>
> Required Resources
>
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
>
> Subversion Directory
> •Git is the preferred source control system.
>
> Issue Tracking
> •JIRA Eagle (Eagle)
>
> Other Resources
> The existing code already has unit tests so we will make use of existing Apache continuous testing infrastructure. The resulting load should not be very large.
>
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
>
>
> Affiliations
> The initial committers are employees of eBay Inc.
>
> Sponsors
>
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member, Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member, Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
>
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
>

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Re: [VOTE] Accept Eagle into Apache Incubation

["Zhang, Edward (GDI Hadoop)" <yo...@ebay.com>]

Thanks Henry very much. That is nice we got those mail lists so we can
communicate with community well.

Thanks
Edward Zhang

On 11/3/15, 16:46, "Henry Saputra" <he...@gmail.com> wrote:

>Follow up announcement, the Apache Eagle incubating mailing lists are
>now available:
>
>€ dev@eagle.incubator.apache.org (subscribe by sending email to
>dev-subscribe@eagle.incubator.apache.org)
>€ commits@eagle.incubator.apache.org (subscribe by sending email to
>commits-subscribe@eagle.incubator.apache.org)
>€ user@eagle.incubator.apache.org (subscribe by sending email to
>user-subscribe@eagle.incubator.apache.org)
>
>
>Thanks,
>
>Henry
>
>
>On Fri, Oct 23, 2015 at 7:11 AM, Manoharan, Arun <ar...@ebay.com>
>wrote:
>> Hello Everyone,
>>
>> Thanks for all the feedback on the Eagle Proposal.
>>
>> I would like to call for a [VOTE] on Eagle joining the ASF as an
>>incubation project.
>>
>> The vote is open for 72 hours:
>>
>> [ ] +1 accept Eagle in the Incubator
>> [ ] ±0
>> [ ] -1 (please give reason)
>>
>> Eagle is a Monitoring solution for Hadoop to instantly identify access
>>to sensitive data, recognize attacks, malicious activities and take
>>actions in real time. Eagle supports a wide variety of policies on HDFS
>>data and Hive. Eagle also provides machine learning models for detecting
>>anomalous user behavior in Hadoop.
>>
>> The proposal is available on the wiki here:
>> https://wiki.apache.org/incubator/EagleProposal
>>
>> The text of the proposal is also available at the end of this email.
>>
>> Thanks for your time and help.
>>
>> Thanks,
>> Arun
>>
>> <COPY of the proposal in text format>
>>
>> Eagle
>>
>> Abstract
>> Eagle is an Open Source Monitoring solution for Hadoop to instantly
>>identify access to sensitive data, recognize attacks, malicious
>>activities in hadoop and take actions.
>>
>> Proposal
>> Eagle audits access to HDFS files, Hive and HBase tables in real time,
>>enforces policies defined on sensitive data access and alerts or blocks
>>user¹s access to that sensitive data in real time. Eagle also creates
>>user profiles based on the typical access behaviour for HDFS and Hive
>>and sends alerts when anomalous behaviour is detected. Eagle can also
>>import sensitive data information classified by external classification
>>engines to help define its policies.
>>
>> Overview of Eagle
>> Eagle has 3 main parts.
>> 1.Data collection and storage - Eagle collects data from various hadoop
>>logs in real time using Kafka/Yarn API and uses HDFS and HBase for
>>storage.
>> 2.Data processing and policy engine - Eagle allows users to create
>>policies based on various metadata properties on HDFS, Hive and HBase
>>data.
>> 3.Eagle services - Eagle services include policy manager, query service
>>and the visualization component. Eagle provides intuitive user interface
>>to administer Eagle and an alert dashboard to respond to real time
>>alerts.
>>
>> Data Collection and Storage:
>> Eagle provides programming API for extending Eagle to integrate any
>>data source into Eagle policy evaluation framework. For example, Eagle
>>hdfs audit monitoring collects data from Kafka which is populated from
>>namenode log4j appender or from logstash agent. Eagle hive monitoring
>>collects hive query logs from running job through YARN API, which is
>>designed to be scalable and fault-tolerant. Eagle uses HBase as storage
>>for storing metadata and metrics data, and also supports relational
>>database through configuration change.
>>
>> Data Processing and Policy Engine:
>> Processing Engine: Eagle provides stream processing API which is an
>>abstraction of Apache Storm. It can also be extended to other streaming
>>engines. This abstraction allows developers to assemble data
>>transformation, filtering, external data join etc. without physically
>>bound to a specific streaming platform. Eagle streaming API allows
>>developers to easily integrate business logic with Eagle policy engine
>>and internally Eagle framework compiles business logic execution DAG
>>into program primitives of underlying stream infrastructure e.g. Apache
>>Storm. For example, Eagle HDFS monitoring transforms audit log from
>>Namenode to object and joins sensitivity metadata, security zone
>>metadata which are generated from external programs or configured by
>>user. Eagle hive monitoring filters running jobs to get hive query
>>string and parses query string into object and then joins sensitivity
>>metadata.
>> Alerting Framework: Eagle Alert Framework includes stream metadata API,
>>scalable policy engine framework, extensible policy engine framework.
>>Stream metadata API allows developers to declare event schema including
>>what attributes constitute an event, what is the type for each
>>attribute, and how to dynamically resolve attribute value in runtime
>>when user configures policy. Scalable policy engine framework allows
>>policies to be executed on different physical nodes in parallel. It is
>>also used to define your own policy partitioner class. Policy engine
>>framework together with streaming partitioning capability provided by
>>all streaming platforms will make sure policies and events can be
>>evaluated in a fully distributed way. Extensible policy engine framework
>>allows developer to plugin a new policy engine with a few lines of
>>codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports
>>as first-class citizen.
>> Machine Learning module: Eagle provides capabilities to define user
>>activity patterns or user profiles for Hadoop users based on the user
>>behaviour in the platform. These user profiles are modeled using Machine
>>Learning algorithms and used for detection of anomalous users
>>activities. Eagle uses Eigen Value Decomposition, and Density Estimation
>>algorithms for generating user profile models. The model reads data from
>>HDFS audit logs, preprocesses and aggregates data, and generates models
>>using Spark programming APIs. Once models are generated, Eagle uses
>>stream processing engine for near real-time anomaly detection to
>>determine if any user¹s activities are suspicious or not.
>>
>> Eagle Services:
>> Query Service: Eagle provides SQL-like service API to support
>>comprehensive computation for huge set of data on the fly, for e.g.
>>comprehensive filtering, aggregation, histogram, sorting, top,
>>arithmetical expression, pagination etc. HBase is the data storage which
>>Eagle supports as first-class citizen, relational database is supported
>>as well. For HBase storage, Eagle query framework compiles user provided
>>SQL-like query into HBase native filter objects and execute it through
>>HBase coprocessor on the fly.
>> Policy Manager: Eagle policy manager provides UI and Restful API for
>>user to define policy with just a few clicks. It includes site
>>management UI, policy editor, sensitivity metadata import, HDFS or Hive
>>sensitive resource browsing, alert dashboards etc.
>> Background
>> Data is one of the most important assets for today¹s businesses, which
>>makes data security one of the top priorities of today¹s enterprises.
>>Hadoop is widely used across different verticals as a big data
>>repository to store this data in most modern enterprises.
>> At eBay we use hadoop platform extensively for our data processing
>>needs. Our data in Hadoop is becoming bigger and bigger as our user base
>>is seeing an exponential growth. Today there are variety of data sets
>>available in Hadoop cluster for our users to consume. eBay has around
>>120 PB of data stored in HDFS across 6 different clusters and around
>>1800+ active hadoop users consuming data thru Hive, HBase and mapreduce
>>jobs everyday to build applications using this data. With this
>>astronomical growth of data there are also challenges in securing
>>sensitive data and monitoring the access to this sensitive data. Today
>>in large organizations HDFS is the defacto standard for storing big
>>data. Data sets which includes and not limited to consumer sentiment,
>>social media data, customer segmentation, web clicks, sensor data,
>>geo-location and transaction data get stored in Hadoop for day to day
>>business needs.
>> We at eBay want to make sure the sensitive data and data platforms are
>>completely protected from security breaches. So we partnered very
>>closely with our Information Security team to understand the
>>requirements for Eagle to monitor sensitive data access on hadoop:
>> 1.Ability to identify and stop security threats in real time
>> 2.Scale for big data (Support PB scale and Billions of events)
>> 3.Ability to create data access policies
>> 4.Support multiple data sources like HDFS, HBase, Hive
>> 5.Visualize alerts in real time
>> 6.Ability to block malicious access in real time
>> We did not find any data access monitoring solution that available
>>today and can provide the features and functionality that we need to
>>monitor the data access in the hadoop ecosystem at our scale. Hence with
>>an excellent team of world class developers and several users, we have
>>been able to bring Eagle into production as well as open source it.
>>
>> Rationale
>> In today¹s world; data is an important asset for any company.
>>Businesses are using data extensively to create amazing experiences for
>>users. Data has to be protected and access to data should be secured
>>from security breaches. Today Hadoop is not only used to store logs but
>>also stores financial data, sensitive data sets, geographical data, user
>>click stream data sets etc. which makes it more important to be
>>protected from security breaches. To secure a data platform there are
>>multiple things that need to happen. One is having a strong access
>>control mechanism which today is provided by Apache Ranger and Apache
>>Sentry. These tools provide the ability to provide fine grain access
>>control mechanism to data sets on hadoop. But there is a big gap in
>>terms of monitoring all the data access events and activities in order
>>to securing the hadoop data platform. Together with strong access
>>control, perimeter security and data access monitoring in place data in
>>the hadoop clusters can be secured against breaches. We looked around
>>and found following:
>> Existing data activity monitoring products are designed for traditional
>>databases and data warehouse. Existing monitoring platforms cannot scale
>>out to support fast growing data and petabyte scale. Few products in the
>>industry are still very early in terms of supporting HDFS, Hive, HBase
>>data access monitoring.
>> As mentioned in the background, the business requirement and urgency to
>>secure the data from users with malicious intent drove eBay to invest in
>>building a real time data access monitoring solution from scratch to
>>offer real time alerts and remediation features for malicious data
>>access.
>> With the power of open source distributed systems like Hadoop, Kafka
>>and much more we were able to develop a data activity monitoring system
>>that can scale, identify and stop malicious access in real time.
>> Eagle allows admins to create standard access policies and rules for
>>monitoring HDFS, Hive and HBase data. Eagle also provides out of box
>>machine learning models for modeling user profiles based on user access
>>behaviour and use the model to alert on anomalies.
>>
>> Current Status
>>
>> Meritocracy
>> Eagle has been deployed in production at eBay for monitoring billions
>>of events per day from HDFS and Hive operations. From the start; the
>>product has been built with focus on high scalability and application
>>extensibility in mind and Eagle has demonstrated great performance in
>>responding to suspicious events instantly and great flexibility in
>>defining policy.
>>
>> Community
>> Eagle seeks to develop the developer and user communities during
>>incubation.
>>
>> Core Developers
>> Eagle is currently being designed and developed by engineers from eBay
>>Inc. ­ Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
>>Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
>>these core developers have deep expertise in developing monitoring
>>products for the Hadoop ecosystem.
>>
>> Alignment
>> The ASF is a natural host for Eagle given that it is already the home
>>of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
>>projects. Eagle leverages lot of Apache open-source products. Eagle was
>>designed to offer real time insights into sensitive data access by
>>actively monitoring the data access on various data sets in hadoop and
>>an extensible alerting framework with a powerful policy engine. Eagle
>>compliments the existing Hadoop platform area by providing a
>>comprehensive monitoring and alerting solution for detecting sensitive
>>data access threats based on preset policies and machine learning models
>>for user behaviour analysis.
>>
>> Known Risks
>>
>> Orphaned Products
>> The core developers of Eagle team work full time on this project. There
>>is no risk of Eagle getting orphaned since eBay is extensively using it
>>in their production Hadoop clusters and have plans to go beyond hadoop.
>>For example, currently there are 7 hadoop clusters and 2 of them are
>>being monitored using Hadoop Eagle in production. We have plans to
>>extend it to all hadoop clusters and eventually other data platforms.
>>There are 10¹s of policies onboarded and actively monitored with plans
>>to onboard more use case. We are very confident that every hadoop
>>cluster in the world will be monitored using Eagle for securing the
>>hadoop ecosystem by actively monitoring for data access on sensitive
>>data. We plan to extend and diversify this community further through
>>Apache. We presented Eagle at the hadoop summit in china and garnered
>>interest from different companies who use hadoop extensively.
>>
>> Inexperience with Open Source
>> The core developers are all active users and followers of open source.
>>They are already committers and contributors to the Eagle Github
>>project. All have been involved with the source code that has been
>>released under an open source license, and several of them also have
>>experience developing code in an open source environment. Though the
>>core set of Developers do not have Apache Open Source experience, there
>>are plans to onboard individuals with Apache open source experience on
>>to the project. Apache Kylin PMC members are also in the same ebay
>>organization. We work very closely with Apache Ranger committers and are
>>looking forward to find meaningful integrations to improve the security
>>of hadoop platform.
>>
>> Homogenous Developers
>> The core developers are from eBay. Today the problem of monitoring data
>>activities to find and stop threats is a universal problem faced by all
>>the businesses. Apache Incubation process encourages an open and diverse
>>meritocratic community. Eagle intends to make every possible effort to
>>build a diverse, vibrant and involved community and has already received
>>substantial interest from various organizations.
>>
>> Reliance on Salaried Developers
>> eBay invested in Eagle as the monitoring solution for Hadoop clusters
>>and some of its key engineers are working full time on the project. In
>>addition, since there is a growing need for securing sensitive data
>>access we need a data activity monitoring solution for Hadoop, we look
>>forward to other Apache developers and researchers to contribute to the
>>project. Additional contributors, including Apache committers have plans
>>to join this effort shortly. Also key to addressing the risk associated
>>with relying on Salaried developers from a single entity is to increase
>>the diversity of the contributors and actively lobby for Domain experts
>>in the security space to contribute. Eagle intends to do this.
>>
>> Relationships with Other Apache Products
>> Eagle has a strong relationship and dependency with Apache Hadoop,
>>HBase, Spark, Kafka and Storm. Being part of Apache¹s Incubation
>>community, could help with a closer collaboration among these projects
>>and as well as others. An Excessive Fascination with the Apache Brand
>>Eagle is proposing to enter incubation at Apache in order to help
>>efforts to diversify the committer-base, not so much to capitalize on
>>the Apache brand. The Eagle project is in production use already inside
>>eBay, but is not expected to be an eBay product for external customers.
>>As such, the Eagle project is not seeking to use the Apache brand as a
>>marketing tool.
>>
>> Documentation
>> Information about Eagle can be found at https://github.com/eBay/Eagle.
>>The following link provide more information about Eagle
>>http://goeagle.io<http://goeagle.io/>.
>>
>> Initial Source
>> Eagle has been under development since 2014 by a team of engineers at
>>eBay Inc. It is currently hosted on Github.com under an Apache license
>>2.0 at https://github.com/eBay/Eagle. Once in incubation we will be
>>moving the code base to apache git library.
>>
>> External Dependencies
>> Eagle has the following external dependencies.
>> Basic
>> €JDK 1.7+
>> €Scala 2.10.4
>> €Apache Maven
>> €JUnit
>> €Log4j
>> €Slf4j
>> €Apache Commons
>> €Apache Commons Math3
>> €Jackson
>> €Siddhi CEP engine
>>
>> Hadoop
>> €Apache Hadoop
>> €Apache HBase
>> €Apache Hive
>> €Apache Zookeeper
>> €Apache Curator
>>
>> Apache Spark
>> €Spark Core Library
>>
>> REST Service
>> €Jersey
>>
>> Query
>> €Antlr
>>
>> Stream processing
>> €Apache Storm
>> €Apache Kafka
>>
>> Web
>> €AngularJS
>> €jQuery
>> €Bootstrap V3
>> €Moment JS
>> €Admin LTE
>> €html5shiv
>> €respond
>> €Fastclick
>> €Date Range Picker
>> €Flot JS
>>
>> Cryptography
>> Eagle will eventually support encryption on the wire. This is not one
>>of the initial goals, and we do not expect Eagle to be a controlled
>>export item due to the use of encryption. Eagle supports but does not
>>require the Kerberos authentication mechanism to access secured Hadoop
>>services.
>>
>> Required Resources
>>
>> Mailing List
>> €eagle-private for private PMC discussions
>> €eagle-dev for developers
>> €eagle-commits for all commits
>> €eagle-users for all eagle users
>>
>> Subversion Directory
>> €Git is the preferred source control system.
>>
>> Issue Tracking
>> €JIRA Eagle (Eagle)
>>
>> Other Resources
>> The existing code already has unit tests so we will make use of
>>existing Apache continuous testing infrastructure. The resulting load
>>should not be very large.
>>
>> Initial Committers
>> €Seshu Adunuthula <sadunuthula at ebay dot com>
>> €Arun Manoharan <armanoharan at ebay dot com>
>> €Edward Zhang <yonzhang at ebay dot com>
>> €Hao Chen <hchen9 at ebay dot com>
>> €Chaitali Gupta <cgupta at ebay dot com>
>> €Libin Sun <libsun at ebay dot com>
>> €Jilin Jiang <jiljiang at ebay dot com>
>> €Qingwen Zhao <qingwzhao at ebay dot com>
>> €Hemanth Dendukuri <hdendukuri at ebay dot com>
>> €Senthil Kumar <senthilkumar at ebay dot com>
>>
>>
>> Affiliations
>> The initial committers are employees of eBay Inc.
>>
>> Sponsors
>>
>> Champion
>> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>>
>> Nominated Mentors
>> €Owen O¹Malley < omalley at apache dot org > - Apache IPMC member,
>>Hortonworks
>> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>> €Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
>>Hortonworks
>> €Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
>>member
>> €Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
>>Hortonworks
>>
>> Sponsoring Entity
>> We are requesting the Incubator to sponsor this project.
>>
>
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>To unsubscribe, e-mail: general-unsubscribe@incubator.apache.org
>For additional commands, e-mail: general-help@incubator.apache.org
>


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Re: [VOTE] Accept Eagle into Apache Incubation

[Henry Saputra <he...@gmail.com>]

Follow up announcement, the Apache Eagle incubating mailing lists are
now available:

• dev@eagle.incubator.apache.org (subscribe by sending email to
dev-subscribe@eagle.incubator.apache.org)
• commits@eagle.incubator.apache.org (subscribe by sending email to
commits-subscribe@eagle.incubator.apache.org)
• user@eagle.incubator.apache.org (subscribe by sending email to
user-subscribe@eagle.incubator.apache.org)


Thanks,

Henry


On Fri, Oct 23, 2015 at 7:11 AM, Manoharan, Arun <ar...@ebay.com> wrote:
> Hello Everyone,
>
> Thanks for all the feedback on the Eagle Proposal.
>
> I would like to call for a [VOTE] on Eagle joining the ASF as an incubation project.
>
> The vote is open for 72 hours:
>
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
>
> Eagle is a Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities and take actions in real time. Eagle supports a wide variety of policies on HDFS data and Hive. Eagle also provides machine learning models for detecting anomalous user behavior in Hadoop.
>
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
>
> The text of the proposal is also available at the end of this email.
>
> Thanks for your time and help.
>
> Thanks,
> Arun
>
> <COPY of the proposal in text format>
>
> Eagle
>
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities in hadoop and take actions.
>
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time, enforces policies defined on sensitive data access and alerts or blocks user’s access to that sensitive data in real time. Eagle also creates user profiles based on the typical access behaviour for HDFS and Hive and sends alerts when anomalous behaviour is detected. Eagle can also import sensitive data information classified by external classification engines to help define its policies.
>
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service and the visualization component. Eagle provides intuitive user interface to administer Eagle and an alert dashboard to respond to real time alerts.
>
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data source into Eagle policy evaluation framework. For example, Eagle hdfs audit monitoring collects data from Kafka which is populated from namenode log4j appender or from logstash agent. Eagle hive monitoring collects hive query logs from running job through YARN API, which is designed to be scalable and fault-tolerant. Eagle uses HBase as storage for storing metadata and metrics data, and also supports relational database through configuration change.
>
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an abstraction of Apache Storm. It can also be extended to other streaming engines. This abstraction allows developers to assemble data transformation, filtering, external data join etc. without physically bound to a specific streaming platform. Eagle streaming API allows developers to easily integrate business logic with Eagle policy engine and internally Eagle framework compiles business logic execution DAG into program primitives of underlying stream infrastructure e.g. Apache Storm. For example, Eagle HDFS monitoring transforms audit log from Namenode to object and joins sensitivity metadata, security zone metadata which are generated from external programs or configured by user. Eagle hive monitoring filters running jobs to get hive query string and parses query string into object and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API, scalable policy engine framework, extensible policy engine framework. Stream metadata API allows developers to declare event schema including what attributes constitute an event, what is the type for each attribute, and how to dynamically resolve attribute value in runtime when user configures policy. Scalable policy engine framework allows policies to be executed on different physical nodes in parallel. It is also used to define your own policy partitioner class. Policy engine framework together with streaming partitioning capability provided by all streaming platforms will make sure policies and events can be evaluated in a fully distributed way. Extensible policy engine framework allows developer to plugin a new policy engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user activity patterns or user profiles for Hadoop users based on the user behaviour in the platform. These user profiles are modeled using Machine Learning algorithms and used for detection of anomalous users activities. Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for generating user profile models. The model reads data from HDFS audit logs, preprocesses and aggregates data, and generates models using Spark programming APIs. Once models are generated, Eagle uses stream processing engine for near real-time anomaly detection to determine if any user’s activities are suspicious or not.
>
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support comprehensive computation for huge set of data on the fly, for e.g. comprehensive filtering, aggregation, histogram, sorting, top, arithmetical expression, pagination etc. HBase is the data storage which Eagle supports as first-class citizen, relational database is supported as well. For HBase storage, Eagle query framework compiles user provided SQL-like query into HBase native filter objects and execute it through HBase coprocessor on the fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user to define policy with just a few clicks. It includes site management UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive resource browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which makes data security one of the top priorities of today’s enterprises. Hadoop is widely used across different verticals as a big data repository to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs. Our data in Hadoop is becoming bigger and bigger as our user base is seeing an exponential growth. Today there are variety of data sets available in Hadoop cluster for our users to consume. eBay has around 120 PB of data stored in HDFS across 6 different clusters and around 1800+ active hadoop users consuming data thru Hive, HBase and mapreduce jobs everyday to build applications using this data. With this astronomical growth of data there are also challenges in securing sensitive data and monitoring the access to this sensitive data. Today in large organizations HDFS is the defacto standard for storing big data. Data sets which includes and not limited to consumer sentiment, social media data, customer segmentation, web clicks, sensor data, geo-location and transaction data get stored in Hadoop for day to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are completely protected from security breaches. So we partnered very closely with our Information Security team to understand the requirements for Eagle to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today and can provide the features and functionality that we need to monitor the data access in the hadoop ecosystem at our scale. Hence with an excellent team of world class developers and several users, we have been able to bring Eagle into production as well as open source it.
>
> Rationale
> In today’s world; data is an important asset for any company. Businesses are using data extensively to create amazing experiences for users. Data has to be protected and access to data should be secured from security breaches. Today Hadoop is not only used to store logs but also stores financial data, sensitive data sets, geographical data, user click stream data sets etc. which makes it more important to be protected from security breaches. To secure a data platform there are multiple things that need to happen. One is having a strong access control mechanism which today is provided by Apache Ranger and Apache Sentry. These tools provide the ability to provide fine grain access control mechanism to data sets on hadoop. But there is a big gap in terms of monitoring all the data access events and activities in order to securing the hadoop data platform. Together with strong access control, perimeter security and data access monitoring in place data in the hadoop clusters can be secured against breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional databases and data warehouse. Existing monitoring platforms cannot scale out to support fast growing data and petabyte scale. Few products in the industry are still very early in terms of supporting HDFS, Hive, HBase data access monitoring.
> As mentioned in the background, the business requirement and urgency to secure the data from users with malicious intent drove eBay to invest in building a real time data access monitoring solution from scratch to offer real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and much more we were able to develop a data activity monitoring system that can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for monitoring HDFS, Hive and HBase data. Eagle also provides out of box machine learning models for modeling user profiles based on user access behaviour and use the model to alert on anomalies.
>
> Current Status
>
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of events per day from HDFS and Hive operations. From the start; the product has been built with focus on high scalability and application extensibility in mind and Eagle has demonstrated great performance in responding to suspicious events instantly and great flexibility in defining policy.
>
> Community
> Eagle seeks to develop the developer and user communities during incubation.
>
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang, Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of these core developers have deep expertise in developing monitoring products for the Hadoop ecosystem.
>
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data projects. Eagle leverages lot of Apache open-source products. Eagle was designed to offer real time insights into sensitive data access by actively monitoring the data access on various data sets in hadoop and an extensible alerting framework with a powerful policy engine. Eagle compliments the existing Hadoop platform area by providing a comprehensive monitoring and alerting solution for detecting sensitive data access threats based on preset policies and machine learning models for user behaviour analysis.
>
> Known Risks
>
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is no risk of Eagle getting orphaned since eBay is extensively using it in their production Hadoop clusters and have plans to go beyond hadoop. For example, currently there are 7 hadoop clusters and 2 of them are being monitored using Hadoop Eagle in production. We have plans to extend it to all hadoop clusters and eventually other data platforms. There are 10’s of policies onboarded and actively monitored with plans to onboard more use case. We are very confident that every hadoop cluster in the world will be monitored using Eagle for securing the hadoop ecosystem by actively monitoring for data access on sensitive data. We plan to extend and diversify this community further through Apache. We presented Eagle at the hadoop summit in china and garnered interest from different companies who use hadoop extensively.
>
> Inexperience with Open Source
> The core developers are all active users and followers of open source. They are already committers and contributors to the Eagle Github project. All have been involved with the source code that has been released under an open source license, and several of them also have experience developing code in an open source environment. Though the core set of Developers do not have Apache Open Source experience, there are plans to onboard individuals with Apache open source experience on to the project. Apache Kylin PMC members are also in the same ebay organization. We work very closely with Apache Ranger committers and are looking forward to find meaningful integrations to improve the security of hadoop platform.
>
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data activities to find and stop threats is a universal problem faced by all the businesses. Apache Incubation process encourages an open and diverse meritocratic community. Eagle intends to make every possible effort to build a diverse, vibrant and involved community and has already received substantial interest from various organizations.
>
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and some of its key engineers are working full time on the project. In addition, since there is a growing need for securing sensitive data access we need a data activity monitoring solution for Hadoop, we look forward to other Apache developers and researchers to contribute to the project. Additional contributors, including Apache committers have plans to join this effort shortly. Also key to addressing the risk associated with relying on Salaried developers from a single entity is to increase the diversity of the contributors and actively lobby for Domain experts in the security space to contribute. Eagle intends to do this.
>
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation community, could help with a closer collaboration among these projects and as well as others. An Excessive Fascination with the Apache Brand Eagle is proposing to enter incubation at Apache in order to help efforts to diversify the committer-base, not so much to capitalize on the Apache brand. The Eagle project is in production use already inside eBay, but is not expected to be an eBay product for external customers. As such, the Eagle project is not seeking to use the Apache brand as a marketing tool.
>
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle. The following link provide more information about Eagle http://goeagle.io<http://goeagle.io/>.
>
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay Inc. It is currently hosted on Github.com under an Apache license 2.0 at https://github.com/eBay/Eagle. Once in incubation we will be moving the code base to apache git library.
>
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
>
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
>
> Apache Spark
> •Spark Core Library
>
> REST Service
> •Jersey
>
> Query
> •Antlr
>
> Stream processing
> •Apache Storm
> •Apache Kafka
>
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
>
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of the initial goals, and we do not expect Eagle to be a controlled export item due to the use of encryption. Eagle supports but does not require the Kerberos authentication mechanism to access secured Hadoop services.
>
> Required Resources
>
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
>
> Subversion Directory
> •Git is the preferred source control system.
>
> Issue Tracking
> •JIRA Eagle (Eagle)
>
> Other Resources
> The existing code already has unit tests so we will make use of existing Apache continuous testing infrastructure. The resulting load should not be very large.
>
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
>
>
> Affiliations
> The initial committers are employees of eBay Inc.
>
> Sponsors
>
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member, Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member, Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
>
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
>

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Re: [VOTE] Accept Eagle into Apache Incubation

[Amareshwari Sriramdasu <am...@apache.org>]

+1 (binding)

On Fri, Oct 23, 2015 at 7:41 PM, Manoharan, Arun <ar...@ebay.com>
wrote:

> Hello Everyone,
>
> Thanks for all the feedback on the Eagle Proposal.
>
> I would like to call for a [VOTE] on Eagle joining the ASF as an
> incubation project.
>
> The vote is open for 72 hours:
>
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
>
> Eagle is a Monitoring solution for Hadoop to instantly identify access to
> sensitive data, recognize attacks, malicious activities and take actions in
> real time. Eagle supports a wide variety of policies on HDFS data and Hive.
> Eagle also provides machine learning models for detecting anomalous user
> behavior in Hadoop.
>
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
>
> The text of the proposal is also available at the end of this email.
>
> Thanks for your time and help.
>
> Thanks,
> Arun
>
> <COPY of the proposal in text format>
>
> Eagle
>
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly
> identify access to sensitive data, recognize attacks, malicious activities
> in hadoop and take actions.
>
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time,
> enforces policies defined on sensitive data access and alerts or blocks
> user’s access to that sensitive data in real time. Eagle also creates user
> profiles based on the typical access behaviour for HDFS and Hive and sends
> alerts when anomalous behaviour is detected. Eagle can also import
> sensitive data information classified by external classification engines to
> help define its policies.
>
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop
> logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create
> policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service
> and the visualization component. Eagle provides intuitive user interface to
> administer Eagle and an alert dashboard to respond to real time alerts.
>
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data
> source into Eagle policy evaluation framework. For example, Eagle hdfs
> audit monitoring collects data from Kafka which is populated from namenode
> log4j appender or from logstash agent. Eagle hive monitoring collects hive
> query logs from running job through YARN API, which is designed to be
> scalable and fault-tolerant. Eagle uses HBase as storage for storing
> metadata and metrics data, and also supports relational database through
> configuration change.
>
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an
> abstraction of Apache Storm. It can also be extended to other streaming
> engines. This abstraction allows developers to assemble data
> transformation, filtering, external data join etc. without physically bound
> to a specific streaming platform. Eagle streaming API allows developers to
> easily integrate business logic with Eagle policy engine and internally
> Eagle framework compiles business logic execution DAG into program
> primitives of underlying stream infrastructure e.g. Apache Storm. For
> example, Eagle HDFS monitoring transforms audit log from Namenode to object
> and joins sensitivity metadata, security zone metadata which are generated
> from external programs or configured by user. Eagle hive monitoring filters
> running jobs to get hive query string and parses query string into object
> and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API,
> scalable policy engine framework, extensible policy engine framework.
> Stream metadata API allows developers to declare event schema including
> what attributes constitute an event, what is the type for each attribute,
> and how to dynamically resolve attribute value in runtime when user
> configures policy. Scalable policy engine framework allows policies to be
> executed on different physical nodes in parallel. It is also used to define
> your own policy partitioner class. Policy engine framework together with
> streaming partitioning capability provided by all streaming platforms will
> make sure policies and events can be evaluated in a fully distributed way.
> Extensible policy engine framework allows developer to plugin a new policy
> engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user
> activity patterns or user profiles for Hadoop users based on the user
> behaviour in the platform. These user profiles are modeled using Machine
> Learning algorithms and used for detection of anomalous users activities.
> Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for
> generating user profile models. The model reads data from HDFS audit logs,
> preprocesses and aggregates data, and generates models using Spark
> programming APIs. Once models are generated, Eagle uses stream processing
> engine for near real-time anomaly detection to determine if any user’s
> activities are suspicious or not.
>
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support
> comprehensive computation for huge set of data on the fly, for e.g.
> comprehensive filtering, aggregation, histogram, sorting, top, arithmetical
> expression, pagination etc. HBase is the data storage which Eagle supports
> as first-class citizen, relational database is supported as well. For HBase
> storage, Eagle query framework compiles user provided SQL-like query into
> HBase native filter objects and execute it through HBase coprocessor on the
> fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user
> to define policy with just a few clicks. It includes site management UI,
> policy editor, sensitivity metadata import, HDFS or Hive sensitive resource
> browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which
> makes data security one of the top priorities of today’s enterprises.
> Hadoop is widely used across different verticals as a big data repository
> to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs.
> Our data in Hadoop is becoming bigger and bigger as our user base is seeing
> an exponential growth. Today there are variety of data sets available in
> Hadoop cluster for our users to consume. eBay has around 120 PB of data
> stored in HDFS across 6 different clusters and around 1800+ active hadoop
> users consuming data thru Hive, HBase and mapreduce jobs everyday to build
> applications using this data. With this astronomical growth of data there
> are also challenges in securing sensitive data and monitoring the access to
> this sensitive data. Today in large organizations HDFS is the defacto
> standard for storing big data. Data sets which includes and not limited to
> consumer sentiment, social media data, customer segmentation, web clicks,
> sensor data, geo-location and transaction data get stored in Hadoop for day
> to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are
> completely protected from security breaches. So we partnered very closely
> with our Information Security team to understand the requirements for Eagle
> to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today
> and can provide the features and functionality that we need to monitor the
> data access in the hadoop ecosystem at our scale. Hence with an excellent
> team of world class developers and several users, we have been able to
> bring Eagle into production as well as open source it.
>
> Rationale
> In today’s world; data is an important asset for any company. Businesses
> are using data extensively to create amazing experiences for users. Data
> has to be protected and access to data should be secured from security
> breaches. Today Hadoop is not only used to store logs but also stores
> financial data, sensitive data sets, geographical data, user click stream
> data sets etc. which makes it more important to be protected from security
> breaches. To secure a data platform there are multiple things that need to
> happen. One is having a strong access control mechanism which today is
> provided by Apache Ranger and Apache Sentry. These tools provide the
> ability to provide fine grain access control mechanism to data sets on
> hadoop. But there is a big gap in terms of monitoring all the data access
> events and activities in order to securing the hadoop data platform.
> Together with strong access control, perimeter security and data access
> monitoring in place data in the hadoop clusters can be secured against
> breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional
> databases and data warehouse. Existing monitoring platforms cannot scale
> out to support fast growing data and petabyte scale. Few products in the
> industry are still very early in terms of supporting HDFS, Hive, HBase data
> access monitoring.
> As mentioned in the background, the business requirement and urgency to
> secure the data from users with malicious intent drove eBay to invest in
> building a real time data access monitoring solution from scratch to offer
> real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and
> much more we were able to develop a data activity monitoring system that
> can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for
> monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> machine learning models for modeling user profiles based on user access
> behaviour and use the model to alert on anomalies.
>
> Current Status
>
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of
> events per day from HDFS and Hive operations. From the start; the product
> has been built with focus on high scalability and application extensibility
> in mind and Eagle has demonstrated great performance in responding to
> suspicious events instantly and great flexibility in defining policy.
>
> Community
> Eagle seeks to develop the developer and user communities during
> incubation.
>
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay
> Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> these core developers have deep expertise in developing monitoring products
> for the Hadoop ecosystem.
>
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of
> Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> projects. Eagle leverages lot of Apache open-source products. Eagle was
> designed to offer real time insights into sensitive data access by actively
> monitoring the data access on various data sets in hadoop and an extensible
> alerting framework with a powerful policy engine. Eagle compliments the
> existing Hadoop platform area by providing a comprehensive monitoring and
> alerting solution for detecting sensitive data access threats based on
> preset policies and machine learning models for user behaviour analysis.
>
> Known Risks
>
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is
> no risk of Eagle getting orphaned since eBay is extensively using it in
> their production Hadoop clusters and have plans to go beyond hadoop. For
> example, currently there are 7 hadoop clusters and 2 of them are being
> monitored using Hadoop Eagle in production. We have plans to extend it to
> all hadoop clusters and eventually other data platforms. There are 10’s of
> policies onboarded and actively monitored with plans to onboard more use
> case. We are very confident that every hadoop cluster in the world will be
> monitored using Eagle for securing the hadoop ecosystem by actively
> monitoring for data access on sensitive data. We plan to extend and
> diversify this community further through Apache. We presented Eagle at the
> hadoop summit in china and garnered interest from different companies who
> use hadoop extensively.
>
> Inexperience with Open Source
> The core developers are all active users and followers of open source.
> They are already committers and contributors to the Eagle Github project.
> All have been involved with the source code that has been released under an
> open source license, and several of them also have experience developing
> code in an open source environment. Though the core set of Developers do
> not have Apache Open Source experience, there are plans to onboard
> individuals with Apache open source experience on to the project. Apache
> Kylin PMC members are also in the same ebay organization. We work very
> closely with Apache Ranger committers and are looking forward to find
> meaningful integrations to improve the security of hadoop platform.
>
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data
> activities to find and stop threats is a universal problem faced by all the
> businesses. Apache Incubation process encourages an open and diverse
> meritocratic community. Eagle intends to make every possible effort to
> build a diverse, vibrant and involved community and has already received
> substantial interest from various organizations.
>
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and
> some of its key engineers are working full time on the project. In
> addition, since there is a growing need for securing sensitive data access
> we need a data activity monitoring solution for Hadoop, we look forward to
> other Apache developers and researchers to contribute to the project.
> Additional contributors, including Apache committers have plans to join
> this effort shortly. Also key to addressing the risk associated with
> relying on Salaried developers from a single entity is to increase the
> diversity of the contributors and actively lobby for Domain experts in the
> security space to contribute. Eagle intends to do this.
>
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase,
> Spark, Kafka and Storm. Being part of Apache’s Incubation community, could
> help with a closer collaboration among these projects and as well as
> others. An Excessive Fascination with the Apache Brand Eagle is proposing
> to enter incubation at Apache in order to help efforts to diversify the
> committer-base, not so much to capitalize on the Apache brand. The Eagle
> project is in production use already inside eBay, but is not expected to be
> an eBay product for external customers. As such, the Eagle project is not
> seeking to use the Apache brand as a marketing tool.
>
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle.
> The following link provide more information about Eagle http://goeagle.io<
> http://goeagle.io/>.
>
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay
> Inc. It is currently hosted on Github.com under an Apache license 2.0 at
> https://github.com/eBay/Eagle. Once in incubation we will be moving the
> code base to apache git library.
>
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
>
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
>
> Apache Spark
> •Spark Core Library
>
> REST Service
> •Jersey
>
> Query
> •Antlr
>
> Stream processing
> •Apache Storm
> •Apache Kafka
>
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
>
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of
> the initial goals, and we do not expect Eagle to be a controlled export
> item due to the use of encryption. Eagle supports but does not require the
> Kerberos authentication mechanism to access secured Hadoop services.
>
> Required Resources
>
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
>
> Subversion Directory
> •Git is the preferred source control system.
>
> Issue Tracking
> •JIRA Eagle (Eagle)
>
> Other Resources
> The existing code already has unit tests so we will make use of existing
> Apache continuous testing infrastructure. The resulting load should not be
> very large.
>
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
>
>
> Affiliations
> The initial committers are employees of eBay Inc.
>
> Sponsors
>
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
>
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
>
>

Re: [VOTE] Accept Eagle into Apache Incubation

[Luke Han <lu...@gmail.com>]

+1 (non-binding)


Best Regards!
---------------------

Luke Han

On Fri, Oct 23, 2015 at 11:26 PM, P. Taylor Goetz <pt...@gmail.com> wrote:

> +1 (binding)
>
> -Taylor
>
> > On Oct 23, 2015, at 10:11 AM, Manoharan, Arun <ar...@ebay.com>
> wrote:
> >
> > Hello Everyone,
> >
> > Thanks for all the feedback on the Eagle Proposal.
> >
> > I would like to call for a [VOTE] on Eagle joining the ASF as an
> incubation project.
> >
> > The vote is open for 72 hours:
> >
> > [ ] +1 accept Eagle in the Incubator
> > [ ] ±0
> > [ ] -1 (please give reason)
> >
> > Eagle is a Monitoring solution for Hadoop to instantly identify access
> to sensitive data, recognize attacks, malicious activities and take actions
> in real time. Eagle supports a wide variety of policies on HDFS data and
> Hive. Eagle also provides machine learning models for detecting anomalous
> user behavior in Hadoop.
> >
> > The proposal is available on the wiki here:
> > https://wiki.apache.org/incubator/EagleProposal
> >
> > The text of the proposal is also available at the end of this email.
> >
> > Thanks for your time and help.
> >
> > Thanks,
> > Arun
> >
> > <COPY of the proposal in text format>
> >
> > Eagle
> >
> > Abstract
> > Eagle is an Open Source Monitoring solution for Hadoop to instantly
> identify access to sensitive data, recognize attacks, malicious activities
> in hadoop and take actions.
> >
> > Proposal
> > Eagle audits access to HDFS files, Hive and HBase tables in real time,
> enforces policies defined on sensitive data access and alerts or blocks
> user’s access to that sensitive data in real time. Eagle also creates user
> profiles based on the typical access behaviour for HDFS and Hive and sends
> alerts when anomalous behaviour is detected. Eagle can also import
> sensitive data information classified by external classification engines to
> help define its policies.
> >
> > Overview of Eagle
> > Eagle has 3 main parts.
> > 1.Data collection and storage - Eagle collects data from various hadoop
> logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> > 2.Data processing and policy engine - Eagle allows users to create
> policies based on various metadata properties on HDFS, Hive and HBase data.
> > 3.Eagle services - Eagle services include policy manager, query service
> and the visualization component. Eagle provides intuitive user interface to
> administer Eagle and an alert dashboard to respond to real time alerts.
> >
> > Data Collection and Storage:
> > Eagle provides programming API for extending Eagle to integrate any data
> source into Eagle policy evaluation framework. For example, Eagle hdfs
> audit monitoring collects data from Kafka which is populated from namenode
> log4j appender or from logstash agent. Eagle hive monitoring collects hive
> query logs from running job through YARN API, which is designed to be
> scalable and fault-tolerant. Eagle uses HBase as storage for storing
> metadata and metrics data, and also supports relational database through
> configuration change.
> >
> > Data Processing and Policy Engine:
> > Processing Engine: Eagle provides stream processing API which is an
> abstraction of Apache Storm. It can also be extended to other streaming
> engines. This abstraction allows developers to assemble data
> transformation, filtering, external data join etc. without physically bound
> to a specific streaming platform. Eagle streaming API allows developers to
> easily integrate business logic with Eagle policy engine and internally
> Eagle framework compiles business logic execution DAG into program
> primitives of underlying stream infrastructure e.g. Apache Storm. For
> example, Eagle HDFS monitoring transforms audit log from Namenode to object
> and joins sensitivity metadata, security zone metadata which are generated
> from external programs or configured by user. Eagle hive monitoring filters
> running jobs to get hive query string and parses query string into object
> and then joins sensitivity metadata.
> > Alerting Framework: Eagle Alert Framework includes stream metadata API,
> scalable policy engine framework, extensible policy engine framework.
> Stream metadata API allows developers to declare event schema including
> what attributes constitute an event, what is the type for each attribute,
> and how to dynamically resolve attribute value in runtime when user
> configures policy. Scalable policy engine framework allows policies to be
> executed on different physical nodes in parallel. It is also used to define
> your own policy partitioner class. Policy engine framework together with
> streaming partitioning capability provided by all streaming platforms will
> make sure policies and events can be evaluated in a fully distributed way.
> Extensible policy engine framework allows developer to plugin a new policy
> engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> engine which Eagle supports as first-class citizen.
> > Machine Learning module: Eagle provides capabilities to define user
> activity patterns or user profiles for Hadoop users based on the user
> behaviour in the platform. These user profiles are modeled using Machine
> Learning algorithms and used for detection of anomalous users activities.
> Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for
> generating user profile models. The model reads data from HDFS audit logs,
> preprocesses and aggregates data, and generates models using Spark
> programming APIs. Once models are generated, Eagle uses stream processing
> engine for near real-time anomaly detection to determine if any user’s
> activities are suspicious or not.
> >
> > Eagle Services:
> > Query Service: Eagle provides SQL-like service API to support
> comprehensive computation for huge set of data on the fly, for e.g.
> comprehensive filtering, aggregation, histogram, sorting, top, arithmetical
> expression, pagination etc. HBase is the data storage which Eagle supports
> as first-class citizen, relational database is supported as well. For HBase
> storage, Eagle query framework compiles user provided SQL-like query into
> HBase native filter objects and execute it through HBase coprocessor on the
> fly.
> > Policy Manager: Eagle policy manager provides UI and Restful API for
> user to define policy with just a few clicks. It includes site management
> UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive
> resource browsing, alert dashboards etc.
> > Background
> > Data is one of the most important assets for today’s businesses, which
> makes data security one of the top priorities of today’s enterprises.
> Hadoop is widely used across different verticals as a big data repository
> to store this data in most modern enterprises.
> > At eBay we use hadoop platform extensively for our data processing
> needs. Our data in Hadoop is becoming bigger and bigger as our user base is
> seeing an exponential growth. Today there are variety of data sets
> available in Hadoop cluster for our users to consume. eBay has around 120
> PB of data stored in HDFS across 6 different clusters and around 1800+
> active hadoop users consuming data thru Hive, HBase and mapreduce jobs
> everyday to build applications using this data. With this astronomical
> growth of data there are also challenges in securing sensitive data and
> monitoring the access to this sensitive data. Today in large organizations
> HDFS is the defacto standard for storing big data. Data sets which includes
> and not limited to consumer sentiment, social media data, customer
> segmentation, web clicks, sensor data, geo-location and transaction data
> get stored in Hadoop for day to day business needs.
> > We at eBay want to make sure the sensitive data and data platforms are
> completely protected from security breaches. So we partnered very closely
> with our Information Security team to understand the requirements for Eagle
> to monitor sensitive data access on hadoop:
> > 1.Ability to identify and stop security threats in real time
> > 2.Scale for big data (Support PB scale and Billions of events)
> > 3.Ability to create data access policies
> > 4.Support multiple data sources like HDFS, HBase, Hive
> > 5.Visualize alerts in real time
> > 6.Ability to block malicious access in real time
> > We did not find any data access monitoring solution that available today
> and can provide the features and functionality that we need to monitor the
> data access in the hadoop ecosystem at our scale. Hence with an excellent
> team of world class developers and several users, we have been able to
> bring Eagle into production as well as open source it.
> >
> > Rationale
> > In today’s world; data is an important asset for any company. Businesses
> are using data extensively to create amazing experiences for users. Data
> has to be protected and access to data should be secured from security
> breaches. Today Hadoop is not only used to store logs but also stores
> financial data, sensitive data sets, geographical data, user click stream
> data sets etc. which makes it more important to be protected from security
> breaches. To secure a data platform there are multiple things that need to
> happen. One is having a strong access control mechanism which today is
> provided by Apache Ranger and Apache Sentry. These tools provide the
> ability to provide fine grain access control mechanism to data sets on
> hadoop. But there is a big gap in terms of monitoring all the data access
> events and activities in order to securing the hadoop data platform.
> Together with strong access control, perimeter security and data access
> monitoring in place data in the hadoop clusters can be secured against
> breaches. We looked around and found following:
> > Existing data activity monitoring products are designed for traditional
> databases and data warehouse. Existing monitoring platforms cannot scale
> out to support fast growing data and petabyte scale. Few products in the
> industry are still very early in terms of supporting HDFS, Hive, HBase data
> access monitoring.
> > As mentioned in the background, the business requirement and urgency to
> secure the data from users with malicious intent drove eBay to invest in
> building a real time data access monitoring solution from scratch to offer
> real time alerts and remediation features for malicious data access.
> > With the power of open source distributed systems like Hadoop, Kafka and
> much more we were able to develop a data activity monitoring system that
> can scale, identify and stop malicious access in real time.
> > Eagle allows admins to create standard access policies and rules for
> monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> machine learning models for modeling user profiles based on user access
> behaviour and use the model to alert on anomalies.
> >
> > Current Status
> >
> > Meritocracy
> > Eagle has been deployed in production at eBay for monitoring billions of
> events per day from HDFS and Hive operations. From the start; the product
> has been built with focus on high scalability and application extensibility
> in mind and Eagle has demonstrated great performance in responding to
> suspicious events instantly and great flexibility in defining policy.
> >
> > Community
> > Eagle seeks to develop the developer and user communities during
> incubation.
> >
> > Core Developers
> > Eagle is currently being designed and developed by engineers from eBay
> Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> these core developers have deep expertise in developing monitoring products
> for the Hadoop ecosystem.
> >
> > Alignment
> > The ASF is a natural host for Eagle given that it is already the home of
> Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> projects. Eagle leverages lot of Apache open-source products. Eagle was
> designed to offer real time insights into sensitive data access by actively
> monitoring the data access on various data sets in hadoop and an extensible
> alerting framework with a powerful policy engine. Eagle compliments the
> existing Hadoop platform area by providing a comprehensive monitoring and
> alerting solution for detecting sensitive data access threats based on
> preset policies and machine learning models for user behaviour analysis.
> >
> > Known Risks
> >
> > Orphaned Products
> > The core developers of Eagle team work full time on this project. There
> is no risk of Eagle getting orphaned since eBay is extensively using it in
> their production Hadoop clusters and have plans to go beyond hadoop. For
> example, currently there are 7 hadoop clusters and 2 of them are being
> monitored using Hadoop Eagle in production. We have plans to extend it to
> all hadoop clusters and eventually other data platforms. There are 10’s of
> policies onboarded and actively monitored with plans to onboard more use
> case. We are very confident that every hadoop cluster in the world will be
> monitored using Eagle for securing the hadoop ecosystem by actively
> monitoring for data access on sensitive data. We plan to extend and
> diversify this community further through Apache. We presented Eagle at the
> hadoop summit in china and garnered interest from different companies who
> use hadoop extensively.
> >
> > Inexperience with Open Source
> > The core developers are all active users and followers of open source.
> They are already committers and contributors to the Eagle Github project.
> All have been involved with the source code that has been released under an
> open source license, and several of them also have experience developing
> code in an open source environment. Though the core set of Developers do
> not have Apache Open Source experience, there are plans to onboard
> individuals with Apache open source experience on to the project. Apache
> Kylin PMC members are also in the same ebay organization. We work very
> closely with Apache Ranger committers and are looking forward to find
> meaningful integrations to improve the security of hadoop platform.
> >
> > Homogenous Developers
> > The core developers are from eBay. Today the problem of monitoring data
> activities to find and stop threats is a universal problem faced by all the
> businesses. Apache Incubation process encourages an open and diverse
> meritocratic community. Eagle intends to make every possible effort to
> build a diverse, vibrant and involved community and has already received
> substantial interest from various organizations.
> >
> > Reliance on Salaried Developers
> > eBay invested in Eagle as the monitoring solution for Hadoop clusters
> and some of its key engineers are working full time on the project. In
> addition, since there is a growing need for securing sensitive data access
> we need a data activity monitoring solution for Hadoop, we look forward to
> other Apache developers and researchers to contribute to the project.
> Additional contributors, including Apache committers have plans to join
> this effort shortly. Also key to addressing the risk associated with
> relying on Salaried developers from a single entity is to increase the
> diversity of the contributors and actively lobby for Domain experts in the
> security space to contribute. Eagle intends to do this.
> >
> > Relationships with Other Apache Products
> > Eagle has a strong relationship and dependency with Apache Hadoop,
> HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation community,
> could help with a closer collaboration among these projects and as well as
> others. An Excessive Fascination with the Apache Brand Eagle is proposing
> to enter incubation at Apache in order to help efforts to diversify the
> committer-base, not so much to capitalize on the Apache brand. The Eagle
> project is in production use already inside eBay, but is not expected to be
> an eBay product for external customers. As such, the Eagle project is not
> seeking to use the Apache brand as a marketing tool.
> >
> > Documentation
> > Information about Eagle can be found at https://github.com/eBay/Eagle.
> The following link provide more information about Eagle http://goeagle.io<
> http://goeagle.io/>.
> >
> > Initial Source
> > Eagle has been under development since 2014 by a team of engineers at
> eBay Inc. It is currently hosted on Github.com under an Apache license 2.0
> at https://github.com/eBay/Eagle. Once in incubation we will be moving
> the code base to apache git library.
> >
> > External Dependencies
> > Eagle has the following external dependencies.
> > Basic
> > •JDK 1.7+
> > •Scala 2.10.4
> > •Apache Maven
> > •JUnit
> > •Log4j
> > •Slf4j
> > •Apache Commons
> > •Apache Commons Math3
> > •Jackson
> > •Siddhi CEP engine
> >
> > Hadoop
> > •Apache Hadoop
> > •Apache HBase
> > •Apache Hive
> > •Apache Zookeeper
> > •Apache Curator
> >
> > Apache Spark
> > •Spark Core Library
> >
> > REST Service
> > •Jersey
> >
> > Query
> > •Antlr
> >
> > Stream processing
> > •Apache Storm
> > •Apache Kafka
> >
> > Web
> > •AngularJS
> > •jQuery
> > •Bootstrap V3
> > •Moment JS
> > •Admin LTE
> > •html5shiv
> > •respond
> > •Fastclick
> > •Date Range Picker
> > •Flot JS
> >
> > Cryptography
> > Eagle will eventually support encryption on the wire. This is not one of
> the initial goals, and we do not expect Eagle to be a controlled export
> item due to the use of encryption. Eagle supports but does not require the
> Kerberos authentication mechanism to access secured Hadoop services.
> >
> > Required Resources
> >
> > Mailing List
> > •eagle-private for private PMC discussions
> > •eagle-dev for developers
> > •eagle-commits for all commits
> > •eagle-users for all eagle users
> >
> > Subversion Directory
> > •Git is the preferred source control system.
> >
> > Issue Tracking
> > •JIRA Eagle (Eagle)
> >
> > Other Resources
> > The existing code already has unit tests so we will make use of existing
> Apache continuous testing infrastructure. The resulting load should not be
> very large.
> >
> > Initial Committers
> > •Seshu Adunuthula <sadunuthula at ebay dot com>
> > •Arun Manoharan <armanoharan at ebay dot com>
> > •Edward Zhang <yonzhang at ebay dot com>
> > •Hao Chen <hchen9 at ebay dot com>
> > •Chaitali Gupta <cgupta at ebay dot com>
> > •Libin Sun <libsun at ebay dot com>
> > •Jilin Jiang <jiljiang at ebay dot com>
> > •Qingwen Zhao <qingwzhao at ebay dot com>
> > •Hemanth Dendukuri <hdendukuri at ebay dot com>
> > •Senthil Kumar <senthilkumar at ebay dot com>
> >
> >
> > Affiliations
> > The initial committers are employees of eBay Inc.
> >
> > Sponsors
> >
> > Champion
> > •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> >
> > Nominated Mentors
> > •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> Hortonworks
> > •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> Hortonworks
> > •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> member
> > •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
> Hortonworks
> >
> > Sponsoring Entity
> > We are requesting the Incubator to sponsor this project.
> >
>
>

Re: [VOTE] Accept Eagle into Apache Incubation

[Libin Sun <ab...@gmail.com>]

+1 (non-binding)

2015-10-23 23:50 GMT+08:00 Owen O'Malley <om...@apache.org>:

> +1 (binding)
>
> On Fri, Oct 23, 2015 at 8:42 AM, wp chun <wp...@hotmail.com> wrote:
>
> > +1
> > wp_chun@hotmail.com
> > >
> > > On 10/23/15, 11:26 PM, "P. Taylor Goetz" <pt...@gmail.com> wrote:
> > >
> > > >+1 (binding)
> > > >
> > > >-Taylor
> > > >
> > > >> On Oct 23, 2015, at 10:11 AM, Manoharan, Arun <armanoharan@ebay.com
> >
> > > >>wrote:
> > > >>
> > > >> Hello Everyone,
> > > >>
> > > >> Thanks for all the feedback on the Eagle Proposal.
> > > >>
> > > >> I would like to call for a [VOTE] on Eagle joining the ASF as an
> > > >>incubation project.
> > > >>
> > > >> The vote is open for 72 hours:
> > > >>
> > > >> [ ] +1 accept Eagle in the Incubator
> > > >> [ ] ±0
> > > >> [ ] -1 (please give reason)
> > > >>
> > > >> Eagle is a Monitoring solution for Hadoop to instantly identify
> access
> > > >>to sensitive data, recognize attacks, malicious activities and take
> > > >>actions in real time. Eagle supports a wide variety of policies on
> HDFS
> > > >>data and Hive. Eagle also provides machine learning models for
> > detecting
> > > >>anomalous user behavior in Hadoop.
> > > >>
> > > >> The proposal is available on the wiki here:
> > > >> https://wiki.apache.org/incubator/EagleProposal
> > > >>
> > > >> The text of the proposal is also available at the end of this email.
> > > >>
> > > >> Thanks for your time and help.
> > > >>
> > > >> Thanks,
> > > >> Arun
> > > >>
> > > >> <COPY of the proposal in text format>
> > > >>
> > > >> Eagle
> > > >>
> > > >> Abstract
> > > >> Eagle is an Open Source Monitoring solution for Hadoop to instantly
> > > >>identify access to sensitive data, recognize attacks, malicious
> > > >>activities in hadoop and take actions.
> > > >>
> > > >> Proposal
> > > >> Eagle audits access to HDFS files, Hive and HBase tables in real
> time,
> > > >>enforces policies defined on sensitive data access and alerts or
> blocks
> > > >>user¹s access to that sensitive data in real time. Eagle also creates
> > > >>user profiles based on the typical access behaviour for HDFS and Hive
> > > >>and sends alerts when anomalous behaviour is detected. Eagle can also
> > > >>import sensitive data information classified by external
> classification
> > > >>engines to help define its policies.
> > > >>
> > > >> Overview of Eagle
> > > >> Eagle has 3 main parts.
> > > >> 1.Data collection and storage - Eagle collects data from various
> > hadoop
> > > >>logs in real time using Kafka/Yarn API and uses HDFS and HBase for
> > > >>storage.
> > > >> 2.Data processing and policy engine - Eagle allows users to create
> > > >>policies based on various metadata properties on HDFS, Hive and HBase
> > > >>data.
> > > >> 3.Eagle services - Eagle services include policy manager, query
> > service
> > > >>and the visualization component. Eagle provides intuitive user
> > interface
> > > >>to administer Eagle and an alert dashboard to respond to real time
> > > >>alerts.
> > > >>
> > > >> Data Collection and Storage:
> > > >> Eagle provides programming API for extending Eagle to integrate any
> > > >>data source into Eagle policy evaluation framework. For example,
> Eagle
> > > >>hdfs audit monitoring collects data from Kafka which is populated
> from
> > > >>namenode log4j appender or from logstash agent. Eagle hive monitoring
> > > >>collects hive query logs from running job through YARN API, which is
> > > >>designed to be scalable and fault-tolerant. Eagle uses HBase as
> storage
> > > >>for storing metadata and metrics data, and also supports relational
> > > >>database through configuration change.
> > > >>
> > > >> Data Processing and Policy Engine:
> > > >> Processing Engine: Eagle provides stream processing API which is an
> > > >>abstraction of Apache Storm. It can also be extended to other
> streaming
> > > >>engines. This abstraction allows developers to assemble data
> > > >>transformation, filtering, external data join etc. without physically
> > > >>bound to a specific streaming platform. Eagle streaming API allows
> > > >>developers to easily integrate business logic with Eagle policy
> engine
> > > >>and internally Eagle framework compiles business logic execution DAG
> > > >>into program primitives of underlying stream infrastructure e.g.
> Apache
> > > >>Storm. For example, Eagle HDFS monitoring transforms audit log from
> > > >>Namenode to object and joins sensitivity metadata, security zone
> > > >>metadata which are generated from external programs or configured by
> > > >>user. Eagle hive monitoring filters running jobs to get hive query
> > > >>string and parses query string into object and then joins sensitivity
> > > >>metadata.
> > > >> Alerting Framework: Eagle Alert Framework includes stream metadata
> > API,
> > > >>scalable policy engine framework, extensible policy engine framework.
> > > >>Stream metadata API allows developers to declare event schema
> including
> > > >>what attributes constitute an event, what is the type for each
> > > >>attribute, and how to dynamically resolve attribute value in runtime
> > > >>when user configures policy. Scalable policy engine framework allows
> > > >>policies to be executed on different physical nodes in parallel. It
> is
> > > >>also used to define your own policy partitioner class. Policy engine
> > > >>framework together with streaming partitioning capability provided by
> > > >>all streaming platforms will make sure policies and events can be
> > > >>evaluated in a fully distributed way. Extensible policy engine
> > framework
> > > >>allows developer to plugin a new policy engine with a few lines of
> > > >>codes. WSO2 Siddhi CEP engine is the policy engine which Eagle
> supports
> > > >>as first-class citizen.
> > > >> Machine Learning module: Eagle provides capabilities to define user
> > > >>activity patterns or user profiles for Hadoop users based on the user
> > > >>behaviour in the platform. These user profiles are modeled using
> > Machine
> > > >>Learning algorithms and used for detection of anomalous users
> > > >>activities. Eagle uses Eigen Value Decomposition, and Density
> > Estimation
> > > >>algorithms for generating user profile models. The model reads data
> > from
> > > >>HDFS audit logs, preprocesses and aggregates data, and generates
> models
> > > >>using Spark programming APIs. Once models are generated, Eagle uses
> > > >>stream processing engine for near real-time anomaly detection to
> > > >>determine if any user¹s activities are suspicious or not.
> > > >>
> > > >> Eagle Services:
> > > >> Query Service: Eagle provides SQL-like service API to support
> > > >>comprehensive computation for huge set of data on the fly, for e.g.
> > > >>comprehensive filtering, aggregation, histogram, sorting, top,
> > > >>arithmetical expression, pagination etc. HBase is the data storage
> > which
> > > >>Eagle supports as first-class citizen, relational database is
> supported
> > > >>as well. For HBase storage, Eagle query framework compiles user
> > provided
> > > >>SQL-like query into HBase native filter objects and execute it
> through
> > > >>HBase coprocessor on the fly.
> > > >> Policy Manager: Eagle policy manager provides UI and Restful API for
> > > >>user to define policy with just a few clicks. It includes site
> > > >>management UI, policy editor, sensitivity metadata import, HDFS or
> Hive
> > > >>sensitive resource browsing, alert dashboards etc.
> > > >> Background
> > > >> Data is one of the most important assets for today¹s businesses,
> which
> > > >>makes data security one of the top priorities of today¹s enterprises.
> > > >>Hadoop is widely used across different verticals as a big data
> > > >>repository to store this data in most modern enterprises.
> > > >> At eBay we use hadoop platform extensively for our data processing
> > > >>needs. Our data in Hadoop is becoming bigger and bigger as our user
> > base
> > > >>is seeing an exponential growth. Today there are variety of data sets
> > > >>available in Hadoop cluster for our users to consume. eBay has around
> > > >>120 PB of data stored in HDFS across 6 different clusters and around
> > > >>1800+ active hadoop users consuming data thru Hive, HBase and
> mapreduce
> > > >>jobs everyday to build applications using this data. With this
> > > >>astronomical growth of data there are also challenges in securing
> > > >>sensitive data and monitoring the access to this sensitive data.
> Today
> > > >>in large organizations HDFS is the defacto standard for storing big
> > > >>data. Data sets which includes and not limited to consumer sentiment,
> > > >>social media data, customer segmentation, web clicks, sensor data,
> > > >>geo-location and transaction data get stored in Hadoop for day to day
> > > >>business needs.
> > > >> We at eBay want to make sure the sensitive data and data platforms
> are
> > > >>completely protected from security breaches. So we partnered very
> > > >>closely with our Information Security team to understand the
> > > >>requirements for Eagle to monitor sensitive data access on hadoop:
> > > >> 1.Ability to identify and stop security threats in real time
> > > >> 2.Scale for big data (Support PB scale and Billions of events)
> > > >> 3.Ability to create data access policies
> > > >> 4.Support multiple data sources like HDFS, HBase, Hive
> > > >> 5.Visualize alerts in real time
> > > >> 6.Ability to block malicious access in real time
> > > >> We did not find any data access monitoring solution that available
> > > >>today and can provide the features and functionality that we need to
> > > >>monitor the data access in the hadoop ecosystem at our scale. Hence
> > with
> > > >>an excellent team of world class developers and several users, we
> have
> > > >>been able to bring Eagle into production as well as open source it.
> > > >>
> > > >> Rationale
> > > >> In today¹s world; data is an important asset for any company.
> > > >>Businesses are using data extensively to create amazing experiences
> for
> > > >>users. Data has to be protected and access to data should be secured
> > > >>from security breaches. Today Hadoop is not only used to store logs
> but
> > > >>also stores financial data, sensitive data sets, geographical data,
> > user
> > > >>click stream data sets etc. which makes it more important to be
> > > >>protected from security breaches. To secure a data platform there are
> > > >>multiple things that need to happen. One is having a strong access
> > > >>control mechanism which today is provided by Apache Ranger and Apache
> > > >>Sentry. These tools provide the ability to provide fine grain access
> > > >>control mechanism to data sets on hadoop. But there is a big gap in
> > > >>terms of monitoring all the data access events and activities in
> order
> > > >>to securing the hadoop data platform. Together with strong access
> > > >>control, perimeter security and data access monitoring in place data
> in
> > > >>the hadoop clusters can be secured against breaches. We looked around
> > > >>and found following:
> > > >> Existing data activity monitoring products are designed for
> > traditional
> > > >>databases and data warehouse. Existing monitoring platforms cannot
> > scale
> > > >>out to support fast growing data and petabyte scale. Few products in
> > the
> > > >>industry are still very early in terms of supporting HDFS, Hive,
> HBase
> > > >>data access monitoring.
> > > >> As mentioned in the background, the business requirement and urgency
> > to
> > > >>secure the data from users with malicious intent drove eBay to invest
> > in
> > > >>building a real time data access monitoring solution from scratch to
> > > >>offer real time alerts and remediation features for malicious data
> > > >>access.
> > > >> With the power of open source distributed systems like Hadoop, Kafka
> > > >>and much more we were able to develop a data activity monitoring
> system
> > > >>that can scale, identify and stop malicious access in real time.
> > > >> Eagle allows admins to create standard access policies and rules for
> > > >>monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> > > >>machine learning models for modeling user profiles based on user
> access
> > > >>behaviour and use the model to alert on anomalies.
> > > >>
> > > >> Current Status
> > > >>
> > > >> Meritocracy
> > > >> Eagle has been deployed in production at eBay for monitoring
> billions
> > > >>of events per day from HDFS and Hive operations. From the start; the
> > > >>product has been built with focus on high scalability and application
> > > >>extensibility in mind and Eagle has demonstrated great performance in
> > > >>responding to suspicious events instantly and great flexibility in
> > > >>defining policy.
> > > >>
> > > >> Community
> > > >> Eagle seeks to develop the developer and user communities during
> > > >>incubation.
> > > >>
> > > >> Core Developers
> > > >> Eagle is currently being designed and developed by engineers from
> eBay
> > > >>Inc. ­ Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin
> Jiang,
> > > >>Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All
> of
> > > >>these core developers have deep expertise in developing monitoring
> > > >>products for the Hadoop ecosystem.
> > > >>
> > > >> Alignment
> > > >> The ASF is a natural host for Eagle given that it is already the
> home
> > > >>of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big
> data
> > > >>projects. Eagle leverages lot of Apache open-source products. Eagle
> was
> > > >>designed to offer real time insights into sensitive data access by
> > > >>actively monitoring the data access on various data sets in hadoop
> and
> > > >>an extensible alerting framework with a powerful policy engine. Eagle
> > > >>compliments the existing Hadoop platform area by providing a
> > > >>comprehensive monitoring and alerting solution for detecting
> sensitive
> > > >>data access threats based on preset policies and machine learning
> > models
> > > >>for user behaviour analysis.
> > > >>
> > > >> Known Risks
> > > >>
> > > >> Orphaned Products
> > > >> The core developers of Eagle team work full time on this project.
> > There
> > > >>is no risk of Eagle getting orphaned since eBay is extensively using
> it
> > > >>in their production Hadoop clusters and have plans to go beyond
> hadoop.
> > > >>For example, currently there are 7 hadoop clusters and 2 of them are
> > > >>being monitored using Hadoop Eagle in production. We have plans to
> > > >>extend it to all hadoop clusters and eventually other data platforms.
> > > >>There are 10¹s of policies onboarded and actively monitored with
> plans
> > > >>to onboard more use case. We are very confident that every hadoop
> > > >>cluster in the world will be monitored using Eagle for securing the
> > > >>hadoop ecosystem by actively monitoring for data access on sensitive
> > > >>data. We plan to extend and diversify this community further through
> > > >>Apache. We presented Eagle at the hadoop summit in china and garnered
> > > >>interest from different companies who use hadoop extensively.
> > > >>
> > > >> Inexperience with Open Source
> > > >> The core developers are all active users and followers of open
> source.
> > > >>They are already committers and contributors to the Eagle Github
> > > >>project. All have been involved with the source code that has been
> > > >>released under an open source license, and several of them also have
> > > >>experience developing code in an open source environment. Though the
> > > >>core set of Developers do not have Apache Open Source experience,
> there
> > > >>are plans to onboard individuals with Apache open source experience
> on
> > > >>to the project. Apache Kylin PMC members are also in the same ebay
> > > >>organization. We work very closely with Apache Ranger committers and
> > are
> > > >>looking forward to find meaningful integrations to improve the
> security
> > > >>of hadoop platform.
> > > >>
> > > >> Homogenous Developers
> > > >> The core developers are from eBay. Today the problem of monitoring
> > data
> > > >>activities to find and stop threats is a universal problem faced by
> all
> > > >>the businesses. Apache Incubation process encourages an open and
> > diverse
> > > >>meritocratic community. Eagle intends to make every possible effort
> to
> > > >>build a diverse, vibrant and involved community and has already
> > received
> > > >>substantial interest from various organizations.
> > > >>
> > > >> Reliance on Salaried Developers
> > > >> eBay invested in Eagle as the monitoring solution for Hadoop
> clusters
> > > >>and some of its key engineers are working full time on the project.
> In
> > > >>addition, since there is a growing need for securing sensitive data
> > > >>access we need a data activity monitoring solution for Hadoop, we
> look
> > > >>forward to other Apache developers and researchers to contribute to
> the
> > > >>project. Additional contributors, including Apache committers have
> > plans
> > > >>to join this effort shortly. Also key to addressing the risk
> associated
> > > >>with relying on Salaried developers from a single entity is to
> increase
> > > >>the diversity of the contributors and actively lobby for Domain
> experts
> > > >>in the security space to contribute. Eagle intends to do this.
> > > >>
> > > >> Relationships with Other Apache Products
> > > >> Eagle has a strong relationship and dependency with Apache Hadoop,
> > > >>HBase, Spark, Kafka and Storm. Being part of Apache¹s Incubation
> > > >>community, could help with a closer collaboration among these
> projects
> > > >>and as well as others. An Excessive Fascination with the Apache Brand
> > > >>Eagle is proposing to enter incubation at Apache in order to help
> > > >>efforts to diversify the committer-base, not so much to capitalize on
> > > >>the Apache brand. The Eagle project is in production use already
> inside
> > > >>eBay, but is not expected to be an eBay product for external
> customers.
> > > >>As such, the Eagle project is not seeking to use the Apache brand as
> a
> > > >>marketing tool.
> > > >>
> > > >> Documentation
> > > >> Information about Eagle can be found at
> https://github.com/eBay/Eagle
> > .
> > > >>The following link provide more information about Eagle
> > > >>http://goeagle.io<http://goeagle.io/>.
> > > >>
> > > >> Initial Source
> > > >> Eagle has been under development since 2014 by a team of engineers
> at
> > > >>eBay Inc. It is currently hosted on Github.com under an Apache
> license
> > > >>2.0 at https://github.com/eBay/Eagle. Once in incubation we will be
> > > >>moving the code base to apache git library.
> > > >>
> > > >> External Dependencies
> > > >> Eagle has the following external dependencies.
> > > >> Basic
> > > >> €JDK 1.7+
> > > >> €Scala 2.10.4
> > > >> €Apache Maven
> > > >> €JUnit
> > > >> €Log4j
> > > >> €Slf4j
> > > >> €Apache Commons
> > > >> €Apache Commons Math3
> > > >> €Jackson
> > > >> €Siddhi CEP engine
> > > >>
> > > >> Hadoop
> > > >> €Apache Hadoop
> > > >> €Apache HBase
> > > >> €Apache Hive
> > > >> €Apache Zookeeper
> > > >> €Apache Curator
> > > >>
> > > >> Apache Spark
> > > >> €Spark Core Library
> > > >>
> > > >> REST Service
> > > >> €Jersey
> > > >>
> > > >> Query
> > > >> €Antlr
> > > >>
> > > >> Stream processing
> > > >> €Apache Storm
> > > >> €Apache Kafka
> > > >>
> > > >> Web
> > > >> €AngularJS
> > > >> €jQuery
> > > >> €Bootstrap V3
> > > >> €Moment JS
> > > >> €Admin LTE
> > > >> €html5shiv
> > > >> €respond
> > > >> €Fastclick
> > > >> €Date Range Picker
> > > >> €Flot JS
> > > >>
> > > >> Cryptography
> > > >> Eagle will eventually support encryption on the wire. This is not
> one
> > > >>of the initial goals, and we do not expect Eagle to be a controlled
> > > >>export item due to the use of encryption. Eagle supports but does not
> > > >>require the Kerberos authentication mechanism to access secured
> Hadoop
> > > >>services.
> > > >>
> > > >> Required Resources
> > > >>
> > > >> Mailing List
> > > >> €eagle-private for private PMC discussions
> > > >> €eagle-dev for developers
> > > >> €eagle-commits for all commits
> > > >> €eagle-users for all eagle users
> > > >>
> > > >> Subversion Directory
> > > >> €Git is the preferred source control system.
> > > >>
> > > >> Issue Tracking
> > > >> €JIRA Eagle (Eagle)
> > > >>
> > > >> Other Resources
> > > >> The existing code already has unit tests so we will make use of
> > > >>existing Apache continuous testing infrastructure. The resulting load
> > > >>should not be very large.
> > > >>
> > > >> Initial Committers
> > > >> €Seshu Adunuthula <sadunuthula at ebay dot com>
> > > >> €Arun Manoharan <armanoharan at ebay dot com>
> > > >> €Edward Zhang <yonzhang at ebay dot com>
> > > >> €Hao Chen <hchen9 at ebay dot com>
> > > >> €Chaitali Gupta <cgupta at ebay dot com>
> > > >> €Libin Sun <libsun at ebay dot com>
> > > >> €Jilin Jiang <jiljiang at ebay dot com>
> > > >> €Qingwen Zhao <qingwzhao at ebay dot com>
> > > >> €Hemanth Dendukuri <hdendukuri at ebay dot com>
> > > >> €Senthil Kumar <senthilkumar at ebay dot com>
> > > >>
> > > >>
> > > >> Affiliations
> > > >> The initial committers are employees of eBay Inc.
> > > >>
> > > >> Sponsors
> > > >>
> > > >> Champion
> > > >> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > > >>
> > > >> Nominated Mentors
> > > >> €Owen O¹Malley < omalley at apache dot org > - Apache IPMC member,
> > > >>Hortonworks
> > > >> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > > >> €Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> > > >>Hortonworks
> > > >> €Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache
> IPMC
> > > >>member
> > > >> €Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
> > > >>Hortonworks
> > > >>
> > > >> Sponsoring Entity
> > > >> We are requesting the Incubator to sponsor this project.
> > > >>
> > > >
> > >
> >
> >
>

Re: [VOTE] Accept Eagle into Apache Incubation

[Owen O'Malley <om...@apache.org>]

+1 (binding)

On Fri, Oct 23, 2015 at 8:42 AM, wp chun <wp...@hotmail.com> wrote:

> +1
> wp_chun@hotmail.com
> >
> > On 10/23/15, 11:26 PM, "P. Taylor Goetz" <pt...@gmail.com> wrote:
> >
> > >+1 (binding)
> > >
> > >-Taylor
> > >
> > >> On Oct 23, 2015, at 10:11 AM, Manoharan, Arun <ar...@ebay.com>
> > >>wrote:
> > >>
> > >> Hello Everyone,
> > >>
> > >> Thanks for all the feedback on the Eagle Proposal.
> > >>
> > >> I would like to call for a [VOTE] on Eagle joining the ASF as an
> > >>incubation project.
> > >>
> > >> The vote is open for 72 hours:
> > >>
> > >> [ ] +1 accept Eagle in the Incubator
> > >> [ ] ±0
> > >> [ ] -1 (please give reason)
> > >>
> > >> Eagle is a Monitoring solution for Hadoop to instantly identify access
> > >>to sensitive data, recognize attacks, malicious activities and take
> > >>actions in real time. Eagle supports a wide variety of policies on HDFS
> > >>data and Hive. Eagle also provides machine learning models for
> detecting
> > >>anomalous user behavior in Hadoop.
> > >>
> > >> The proposal is available on the wiki here:
> > >> https://wiki.apache.org/incubator/EagleProposal
> > >>
> > >> The text of the proposal is also available at the end of this email.
> > >>
> > >> Thanks for your time and help.
> > >>
> > >> Thanks,
> > >> Arun
> > >>
> > >> <COPY of the proposal in text format>
> > >>
> > >> Eagle
> > >>
> > >> Abstract
> > >> Eagle is an Open Source Monitoring solution for Hadoop to instantly
> > >>identify access to sensitive data, recognize attacks, malicious
> > >>activities in hadoop and take actions.
> > >>
> > >> Proposal
> > >> Eagle audits access to HDFS files, Hive and HBase tables in real time,
> > >>enforces policies defined on sensitive data access and alerts or blocks
> > >>user¹s access to that sensitive data in real time. Eagle also creates
> > >>user profiles based on the typical access behaviour for HDFS and Hive
> > >>and sends alerts when anomalous behaviour is detected. Eagle can also
> > >>import sensitive data information classified by external classification
> > >>engines to help define its policies.
> > >>
> > >> Overview of Eagle
> > >> Eagle has 3 main parts.
> > >> 1.Data collection and storage - Eagle collects data from various
> hadoop
> > >>logs in real time using Kafka/Yarn API and uses HDFS and HBase for
> > >>storage.
> > >> 2.Data processing and policy engine - Eagle allows users to create
> > >>policies based on various metadata properties on HDFS, Hive and HBase
> > >>data.
> > >> 3.Eagle services - Eagle services include policy manager, query
> service
> > >>and the visualization component. Eagle provides intuitive user
> interface
> > >>to administer Eagle and an alert dashboard to respond to real time
> > >>alerts.
> > >>
> > >> Data Collection and Storage:
> > >> Eagle provides programming API for extending Eagle to integrate any
> > >>data source into Eagle policy evaluation framework. For example, Eagle
> > >>hdfs audit monitoring collects data from Kafka which is populated from
> > >>namenode log4j appender or from logstash agent. Eagle hive monitoring
> > >>collects hive query logs from running job through YARN API, which is
> > >>designed to be scalable and fault-tolerant. Eagle uses HBase as storage
> > >>for storing metadata and metrics data, and also supports relational
> > >>database through configuration change.
> > >>
> > >> Data Processing and Policy Engine:
> > >> Processing Engine: Eagle provides stream processing API which is an
> > >>abstraction of Apache Storm. It can also be extended to other streaming
> > >>engines. This abstraction allows developers to assemble data
> > >>transformation, filtering, external data join etc. without physically
> > >>bound to a specific streaming platform. Eagle streaming API allows
> > >>developers to easily integrate business logic with Eagle policy engine
> > >>and internally Eagle framework compiles business logic execution DAG
> > >>into program primitives of underlying stream infrastructure e.g. Apache
> > >>Storm. For example, Eagle HDFS monitoring transforms audit log from
> > >>Namenode to object and joins sensitivity metadata, security zone
> > >>metadata which are generated from external programs or configured by
> > >>user. Eagle hive monitoring filters running jobs to get hive query
> > >>string and parses query string into object and then joins sensitivity
> > >>metadata.
> > >> Alerting Framework: Eagle Alert Framework includes stream metadata
> API,
> > >>scalable policy engine framework, extensible policy engine framework.
> > >>Stream metadata API allows developers to declare event schema including
> > >>what attributes constitute an event, what is the type for each
> > >>attribute, and how to dynamically resolve attribute value in runtime
> > >>when user configures policy. Scalable policy engine framework allows
> > >>policies to be executed on different physical nodes in parallel. It is
> > >>also used to define your own policy partitioner class. Policy engine
> > >>framework together with streaming partitioning capability provided by
> > >>all streaming platforms will make sure policies and events can be
> > >>evaluated in a fully distributed way. Extensible policy engine
> framework
> > >>allows developer to plugin a new policy engine with a few lines of
> > >>codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports
> > >>as first-class citizen.
> > >> Machine Learning module: Eagle provides capabilities to define user
> > >>activity patterns or user profiles for Hadoop users based on the user
> > >>behaviour in the platform. These user profiles are modeled using
> Machine
> > >>Learning algorithms and used for detection of anomalous users
> > >>activities. Eagle uses Eigen Value Decomposition, and Density
> Estimation
> > >>algorithms for generating user profile models. The model reads data
> from
> > >>HDFS audit logs, preprocesses and aggregates data, and generates models
> > >>using Spark programming APIs. Once models are generated, Eagle uses
> > >>stream processing engine for near real-time anomaly detection to
> > >>determine if any user¹s activities are suspicious or not.
> > >>
> > >> Eagle Services:
> > >> Query Service: Eagle provides SQL-like service API to support
> > >>comprehensive computation for huge set of data on the fly, for e.g.
> > >>comprehensive filtering, aggregation, histogram, sorting, top,
> > >>arithmetical expression, pagination etc. HBase is the data storage
> which
> > >>Eagle supports as first-class citizen, relational database is supported
> > >>as well. For HBase storage, Eagle query framework compiles user
> provided
> > >>SQL-like query into HBase native filter objects and execute it through
> > >>HBase coprocessor on the fly.
> > >> Policy Manager: Eagle policy manager provides UI and Restful API for
> > >>user to define policy with just a few clicks. It includes site
> > >>management UI, policy editor, sensitivity metadata import, HDFS or Hive
> > >>sensitive resource browsing, alert dashboards etc.
> > >> Background
> > >> Data is one of the most important assets for today¹s businesses, which
> > >>makes data security one of the top priorities of today¹s enterprises.
> > >>Hadoop is widely used across different verticals as a big data
> > >>repository to store this data in most modern enterprises.
> > >> At eBay we use hadoop platform extensively for our data processing
> > >>needs. Our data in Hadoop is becoming bigger and bigger as our user
> base
> > >>is seeing an exponential growth. Today there are variety of data sets
> > >>available in Hadoop cluster for our users to consume. eBay has around
> > >>120 PB of data stored in HDFS across 6 different clusters and around
> > >>1800+ active hadoop users consuming data thru Hive, HBase and mapreduce
> > >>jobs everyday to build applications using this data. With this
> > >>astronomical growth of data there are also challenges in securing
> > >>sensitive data and monitoring the access to this sensitive data. Today
> > >>in large organizations HDFS is the defacto standard for storing big
> > >>data. Data sets which includes and not limited to consumer sentiment,
> > >>social media data, customer segmentation, web clicks, sensor data,
> > >>geo-location and transaction data get stored in Hadoop for day to day
> > >>business needs.
> > >> We at eBay want to make sure the sensitive data and data platforms are
> > >>completely protected from security breaches. So we partnered very
> > >>closely with our Information Security team to understand the
> > >>requirements for Eagle to monitor sensitive data access on hadoop:
> > >> 1.Ability to identify and stop security threats in real time
> > >> 2.Scale for big data (Support PB scale and Billions of events)
> > >> 3.Ability to create data access policies
> > >> 4.Support multiple data sources like HDFS, HBase, Hive
> > >> 5.Visualize alerts in real time
> > >> 6.Ability to block malicious access in real time
> > >> We did not find any data access monitoring solution that available
> > >>today and can provide the features and functionality that we need to
> > >>monitor the data access in the hadoop ecosystem at our scale. Hence
> with
> > >>an excellent team of world class developers and several users, we have
> > >>been able to bring Eagle into production as well as open source it.
> > >>
> > >> Rationale
> > >> In today¹s world; data is an important asset for any company.
> > >>Businesses are using data extensively to create amazing experiences for
> > >>users. Data has to be protected and access to data should be secured
> > >>from security breaches. Today Hadoop is not only used to store logs but
> > >>also stores financial data, sensitive data sets, geographical data,
> user
> > >>click stream data sets etc. which makes it more important to be
> > >>protected from security breaches. To secure a data platform there are
> > >>multiple things that need to happen. One is having a strong access
> > >>control mechanism which today is provided by Apache Ranger and Apache
> > >>Sentry. These tools provide the ability to provide fine grain access
> > >>control mechanism to data sets on hadoop. But there is a big gap in
> > >>terms of monitoring all the data access events and activities in order
> > >>to securing the hadoop data platform. Together with strong access
> > >>control, perimeter security and data access monitoring in place data in
> > >>the hadoop clusters can be secured against breaches. We looked around
> > >>and found following:
> > >> Existing data activity monitoring products are designed for
> traditional
> > >>databases and data warehouse. Existing monitoring platforms cannot
> scale
> > >>out to support fast growing data and petabyte scale. Few products in
> the
> > >>industry are still very early in terms of supporting HDFS, Hive, HBase
> > >>data access monitoring.
> > >> As mentioned in the background, the business requirement and urgency
> to
> > >>secure the data from users with malicious intent drove eBay to invest
> in
> > >>building a real time data access monitoring solution from scratch to
> > >>offer real time alerts and remediation features for malicious data
> > >>access.
> > >> With the power of open source distributed systems like Hadoop, Kafka
> > >>and much more we were able to develop a data activity monitoring system
> > >>that can scale, identify and stop malicious access in real time.
> > >> Eagle allows admins to create standard access policies and rules for
> > >>monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> > >>machine learning models for modeling user profiles based on user access
> > >>behaviour and use the model to alert on anomalies.
> > >>
> > >> Current Status
> > >>
> > >> Meritocracy
> > >> Eagle has been deployed in production at eBay for monitoring billions
> > >>of events per day from HDFS and Hive operations. From the start; the
> > >>product has been built with focus on high scalability and application
> > >>extensibility in mind and Eagle has demonstrated great performance in
> > >>responding to suspicious events instantly and great flexibility in
> > >>defining policy.
> > >>
> > >> Community
> > >> Eagle seeks to develop the developer and user communities during
> > >>incubation.
> > >>
> > >> Core Developers
> > >> Eagle is currently being designed and developed by engineers from eBay
> > >>Inc. ­ Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> > >>Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> > >>these core developers have deep expertise in developing monitoring
> > >>products for the Hadoop ecosystem.
> > >>
> > >> Alignment
> > >> The ASF is a natural host for Eagle given that it is already the home
> > >>of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> > >>projects. Eagle leverages lot of Apache open-source products. Eagle was
> > >>designed to offer real time insights into sensitive data access by
> > >>actively monitoring the data access on various data sets in hadoop and
> > >>an extensible alerting framework with a powerful policy engine. Eagle
> > >>compliments the existing Hadoop platform area by providing a
> > >>comprehensive monitoring and alerting solution for detecting sensitive
> > >>data access threats based on preset policies and machine learning
> models
> > >>for user behaviour analysis.
> > >>
> > >> Known Risks
> > >>
> > >> Orphaned Products
> > >> The core developers of Eagle team work full time on this project.
> There
> > >>is no risk of Eagle getting orphaned since eBay is extensively using it
> > >>in their production Hadoop clusters and have plans to go beyond hadoop.
> > >>For example, currently there are 7 hadoop clusters and 2 of them are
> > >>being monitored using Hadoop Eagle in production. We have plans to
> > >>extend it to all hadoop clusters and eventually other data platforms.
> > >>There are 10¹s of policies onboarded and actively monitored with plans
> > >>to onboard more use case. We are very confident that every hadoop
> > >>cluster in the world will be monitored using Eagle for securing the
> > >>hadoop ecosystem by actively monitoring for data access on sensitive
> > >>data. We plan to extend and diversify this community further through
> > >>Apache. We presented Eagle at the hadoop summit in china and garnered
> > >>interest from different companies who use hadoop extensively.
> > >>
> > >> Inexperience with Open Source
> > >> The core developers are all active users and followers of open source.
> > >>They are already committers and contributors to the Eagle Github
> > >>project. All have been involved with the source code that has been
> > >>released under an open source license, and several of them also have
> > >>experience developing code in an open source environment. Though the
> > >>core set of Developers do not have Apache Open Source experience, there
> > >>are plans to onboard individuals with Apache open source experience on
> > >>to the project. Apache Kylin PMC members are also in the same ebay
> > >>organization. We work very closely with Apache Ranger committers and
> are
> > >>looking forward to find meaningful integrations to improve the security
> > >>of hadoop platform.
> > >>
> > >> Homogenous Developers
> > >> The core developers are from eBay. Today the problem of monitoring
> data
> > >>activities to find and stop threats is a universal problem faced by all
> > >>the businesses. Apache Incubation process encourages an open and
> diverse
> > >>meritocratic community. Eagle intends to make every possible effort to
> > >>build a diverse, vibrant and involved community and has already
> received
> > >>substantial interest from various organizations.
> > >>
> > >> Reliance on Salaried Developers
> > >> eBay invested in Eagle as the monitoring solution for Hadoop clusters
> > >>and some of its key engineers are working full time on the project. In
> > >>addition, since there is a growing need for securing sensitive data
> > >>access we need a data activity monitoring solution for Hadoop, we look
> > >>forward to other Apache developers and researchers to contribute to the
> > >>project. Additional contributors, including Apache committers have
> plans
> > >>to join this effort shortly. Also key to addressing the risk associated
> > >>with relying on Salaried developers from a single entity is to increase
> > >>the diversity of the contributors and actively lobby for Domain experts
> > >>in the security space to contribute. Eagle intends to do this.
> > >>
> > >> Relationships with Other Apache Products
> > >> Eagle has a strong relationship and dependency with Apache Hadoop,
> > >>HBase, Spark, Kafka and Storm. Being part of Apache¹s Incubation
> > >>community, could help with a closer collaboration among these projects
> > >>and as well as others. An Excessive Fascination with the Apache Brand
> > >>Eagle is proposing to enter incubation at Apache in order to help
> > >>efforts to diversify the committer-base, not so much to capitalize on
> > >>the Apache brand. The Eagle project is in production use already inside
> > >>eBay, but is not expected to be an eBay product for external customers.
> > >>As such, the Eagle project is not seeking to use the Apache brand as a
> > >>marketing tool.
> > >>
> > >> Documentation
> > >> Information about Eagle can be found at https://github.com/eBay/Eagle
> .
> > >>The following link provide more information about Eagle
> > >>http://goeagle.io<http://goeagle.io/>.
> > >>
> > >> Initial Source
> > >> Eagle has been under development since 2014 by a team of engineers at
> > >>eBay Inc. It is currently hosted on Github.com under an Apache license
> > >>2.0 at https://github.com/eBay/Eagle. Once in incubation we will be
> > >>moving the code base to apache git library.
> > >>
> > >> External Dependencies
> > >> Eagle has the following external dependencies.
> > >> Basic
> > >> €JDK 1.7+
> > >> €Scala 2.10.4
> > >> €Apache Maven
> > >> €JUnit
> > >> €Log4j
> > >> €Slf4j
> > >> €Apache Commons
> > >> €Apache Commons Math3
> > >> €Jackson
> > >> €Siddhi CEP engine
> > >>
> > >> Hadoop
> > >> €Apache Hadoop
> > >> €Apache HBase
> > >> €Apache Hive
> > >> €Apache Zookeeper
> > >> €Apache Curator
> > >>
> > >> Apache Spark
> > >> €Spark Core Library
> > >>
> > >> REST Service
> > >> €Jersey
> > >>
> > >> Query
> > >> €Antlr
> > >>
> > >> Stream processing
> > >> €Apache Storm
> > >> €Apache Kafka
> > >>
> > >> Web
> > >> €AngularJS
> > >> €jQuery
> > >> €Bootstrap V3
> > >> €Moment JS
> > >> €Admin LTE
> > >> €html5shiv
> > >> €respond
> > >> €Fastclick
> > >> €Date Range Picker
> > >> €Flot JS
> > >>
> > >> Cryptography
> > >> Eagle will eventually support encryption on the wire. This is not one
> > >>of the initial goals, and we do not expect Eagle to be a controlled
> > >>export item due to the use of encryption. Eagle supports but does not
> > >>require the Kerberos authentication mechanism to access secured Hadoop
> > >>services.
> > >>
> > >> Required Resources
> > >>
> > >> Mailing List
> > >> €eagle-private for private PMC discussions
> > >> €eagle-dev for developers
> > >> €eagle-commits for all commits
> > >> €eagle-users for all eagle users
> > >>
> > >> Subversion Directory
> > >> €Git is the preferred source control system.
> > >>
> > >> Issue Tracking
> > >> €JIRA Eagle (Eagle)
> > >>
> > >> Other Resources
> > >> The existing code already has unit tests so we will make use of
> > >>existing Apache continuous testing infrastructure. The resulting load
> > >>should not be very large.
> > >>
> > >> Initial Committers
> > >> €Seshu Adunuthula <sadunuthula at ebay dot com>
> > >> €Arun Manoharan <armanoharan at ebay dot com>
> > >> €Edward Zhang <yonzhang at ebay dot com>
> > >> €Hao Chen <hchen9 at ebay dot com>
> > >> €Chaitali Gupta <cgupta at ebay dot com>
> > >> €Libin Sun <libsun at ebay dot com>
> > >> €Jilin Jiang <jiljiang at ebay dot com>
> > >> €Qingwen Zhao <qingwzhao at ebay dot com>
> > >> €Hemanth Dendukuri <hdendukuri at ebay dot com>
> > >> €Senthil Kumar <senthilkumar at ebay dot com>
> > >>
> > >>
> > >> Affiliations
> > >> The initial committers are employees of eBay Inc.
> > >>
> > >> Sponsors
> > >>
> > >> Champion
> > >> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > >>
> > >> Nominated Mentors
> > >> €Owen O¹Malley < omalley at apache dot org > - Apache IPMC member,
> > >>Hortonworks
> > >> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> > >> €Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> > >>Hortonworks
> > >> €Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> > >>member
> > >> €Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
> > >>Hortonworks
> > >>
> > >> Sponsoring Entity
> > >> We are requesting the Incubator to sponsor this project.
> > >>
> > >
> >
>
>

RE: [VOTE] Accept Eagle into Apache Incubation

[wp chun <wp...@hotmail.com>]

+1
wp_chun@hotmail.com
> 
> On 10/23/15, 11:26 PM, "P. Taylor Goetz" <pt...@gmail.com> wrote:
> 
> >+1 (binding)
> >
> >-Taylor
> >
> >> On Oct 23, 2015, at 10:11 AM, Manoharan, Arun <ar...@ebay.com>
> >>wrote:
> >> 
> >> Hello Everyone,
> >> 
> >> Thanks for all the feedback on the Eagle Proposal.
> >> 
> >> I would like to call for a [VOTE] on Eagle joining the ASF as an
> >>incubation project.
> >> 
> >> The vote is open for 72 hours:
> >> 
> >> [ ] +1 accept Eagle in the Incubator
> >> [ ] ±0
> >> [ ] -1 (please give reason)
> >> 
> >> Eagle is a Monitoring solution for Hadoop to instantly identify access
> >>to sensitive data, recognize attacks, malicious activities and take
> >>actions in real time. Eagle supports a wide variety of policies on HDFS
> >>data and Hive. Eagle also provides machine learning models for detecting
> >>anomalous user behavior in Hadoop.
> >> 
> >> The proposal is available on the wiki here:
> >> https://wiki.apache.org/incubator/EagleProposal
> >> 
> >> The text of the proposal is also available at the end of this email.
> >> 
> >> Thanks for your time and help.
> >> 
> >> Thanks,
> >> Arun
> >> 
> >> <COPY of the proposal in text format>
> >> 
> >> Eagle
> >> 
> >> Abstract
> >> Eagle is an Open Source Monitoring solution for Hadoop to instantly
> >>identify access to sensitive data, recognize attacks, malicious
> >>activities in hadoop and take actions.
> >> 
> >> Proposal
> >> Eagle audits access to HDFS files, Hive and HBase tables in real time,
> >>enforces policies defined on sensitive data access and alerts or blocks
> >>user¹s access to that sensitive data in real time. Eagle also creates
> >>user profiles based on the typical access behaviour for HDFS and Hive
> >>and sends alerts when anomalous behaviour is detected. Eagle can also
> >>import sensitive data information classified by external classification
> >>engines to help define its policies.
> >> 
> >> Overview of Eagle
> >> Eagle has 3 main parts.
> >> 1.Data collection and storage - Eagle collects data from various hadoop
> >>logs in real time using Kafka/Yarn API and uses HDFS and HBase for
> >>storage.
> >> 2.Data processing and policy engine - Eagle allows users to create
> >>policies based on various metadata properties on HDFS, Hive and HBase
> >>data.
> >> 3.Eagle services - Eagle services include policy manager, query service
> >>and the visualization component. Eagle provides intuitive user interface
> >>to administer Eagle and an alert dashboard to respond to real time
> >>alerts.
> >> 
> >> Data Collection and Storage:
> >> Eagle provides programming API for extending Eagle to integrate any
> >>data source into Eagle policy evaluation framework. For example, Eagle
> >>hdfs audit monitoring collects data from Kafka which is populated from
> >>namenode log4j appender or from logstash agent. Eagle hive monitoring
> >>collects hive query logs from running job through YARN API, which is
> >>designed to be scalable and fault-tolerant. Eagle uses HBase as storage
> >>for storing metadata and metrics data, and also supports relational
> >>database through configuration change.
> >> 
> >> Data Processing and Policy Engine:
> >> Processing Engine: Eagle provides stream processing API which is an
> >>abstraction of Apache Storm. It can also be extended to other streaming
> >>engines. This abstraction allows developers to assemble data
> >>transformation, filtering, external data join etc. without physically
> >>bound to a specific streaming platform. Eagle streaming API allows
> >>developers to easily integrate business logic with Eagle policy engine
> >>and internally Eagle framework compiles business logic execution DAG
> >>into program primitives of underlying stream infrastructure e.g. Apache
> >>Storm. For example, Eagle HDFS monitoring transforms audit log from
> >>Namenode to object and joins sensitivity metadata, security zone
> >>metadata which are generated from external programs or configured by
> >>user. Eagle hive monitoring filters running jobs to get hive query
> >>string and parses query string into object and then joins sensitivity
> >>metadata.
> >> Alerting Framework: Eagle Alert Framework includes stream metadata API,
> >>scalable policy engine framework, extensible policy engine framework.
> >>Stream metadata API allows developers to declare event schema including
> >>what attributes constitute an event, what is the type for each
> >>attribute, and how to dynamically resolve attribute value in runtime
> >>when user configures policy. Scalable policy engine framework allows
> >>policies to be executed on different physical nodes in parallel. It is
> >>also used to define your own policy partitioner class. Policy engine
> >>framework together with streaming partitioning capability provided by
> >>all streaming platforms will make sure policies and events can be
> >>evaluated in a fully distributed way. Extensible policy engine framework
> >>allows developer to plugin a new policy engine with a few lines of
> >>codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports
> >>as first-class citizen.
> >> Machine Learning module: Eagle provides capabilities to define user
> >>activity patterns or user profiles for Hadoop users based on the user
> >>behaviour in the platform. These user profiles are modeled using Machine
> >>Learning algorithms and used for detection of anomalous users
> >>activities. Eagle uses Eigen Value Decomposition, and Density Estimation
> >>algorithms for generating user profile models. The model reads data from
> >>HDFS audit logs, preprocesses and aggregates data, and generates models
> >>using Spark programming APIs. Once models are generated, Eagle uses
> >>stream processing engine for near real-time anomaly detection to
> >>determine if any user¹s activities are suspicious or not.
> >> 
> >> Eagle Services:
> >> Query Service: Eagle provides SQL-like service API to support
> >>comprehensive computation for huge set of data on the fly, for e.g.
> >>comprehensive filtering, aggregation, histogram, sorting, top,
> >>arithmetical expression, pagination etc. HBase is the data storage which
> >>Eagle supports as first-class citizen, relational database is supported
> >>as well. For HBase storage, Eagle query framework compiles user provided
> >>SQL-like query into HBase native filter objects and execute it through
> >>HBase coprocessor on the fly.
> >> Policy Manager: Eagle policy manager provides UI and Restful API for
> >>user to define policy with just a few clicks. It includes site
> >>management UI, policy editor, sensitivity metadata import, HDFS or Hive
> >>sensitive resource browsing, alert dashboards etc.
> >> Background
> >> Data is one of the most important assets for today¹s businesses, which
> >>makes data security one of the top priorities of today¹s enterprises.
> >>Hadoop is widely used across different verticals as a big data
> >>repository to store this data in most modern enterprises.
> >> At eBay we use hadoop platform extensively for our data processing
> >>needs. Our data in Hadoop is becoming bigger and bigger as our user base
> >>is seeing an exponential growth. Today there are variety of data sets
> >>available in Hadoop cluster for our users to consume. eBay has around
> >>120 PB of data stored in HDFS across 6 different clusters and around
> >>1800+ active hadoop users consuming data thru Hive, HBase and mapreduce
> >>jobs everyday to build applications using this data. With this
> >>astronomical growth of data there are also challenges in securing
> >>sensitive data and monitoring the access to this sensitive data. Today
> >>in large organizations HDFS is the defacto standard for storing big
> >>data. Data sets which includes and not limited to consumer sentiment,
> >>social media data, customer segmentation, web clicks, sensor data,
> >>geo-location and transaction data get stored in Hadoop for day to day
> >>business needs.
> >> We at eBay want to make sure the sensitive data and data platforms are
> >>completely protected from security breaches. So we partnered very
> >>closely with our Information Security team to understand the
> >>requirements for Eagle to monitor sensitive data access on hadoop:
> >> 1.Ability to identify and stop security threats in real time
> >> 2.Scale for big data (Support PB scale and Billions of events)
> >> 3.Ability to create data access policies
> >> 4.Support multiple data sources like HDFS, HBase, Hive
> >> 5.Visualize alerts in real time
> >> 6.Ability to block malicious access in real time
> >> We did not find any data access monitoring solution that available
> >>today and can provide the features and functionality that we need to
> >>monitor the data access in the hadoop ecosystem at our scale. Hence with
> >>an excellent team of world class developers and several users, we have
> >>been able to bring Eagle into production as well as open source it.
> >> 
> >> Rationale
> >> In today¹s world; data is an important asset for any company.
> >>Businesses are using data extensively to create amazing experiences for
> >>users. Data has to be protected and access to data should be secured
> >>from security breaches. Today Hadoop is not only used to store logs but
> >>also stores financial data, sensitive data sets, geographical data, user
> >>click stream data sets etc. which makes it more important to be
> >>protected from security breaches. To secure a data platform there are
> >>multiple things that need to happen. One is having a strong access
> >>control mechanism which today is provided by Apache Ranger and Apache
> >>Sentry. These tools provide the ability to provide fine grain access
> >>control mechanism to data sets on hadoop. But there is a big gap in
> >>terms of monitoring all the data access events and activities in order
> >>to securing the hadoop data platform. Together with strong access
> >>control, perimeter security and data access monitoring in place data in
> >>the hadoop clusters can be secured against breaches. We looked around
> >>and found following:
> >> Existing data activity monitoring products are designed for traditional
> >>databases and data warehouse. Existing monitoring platforms cannot scale
> >>out to support fast growing data and petabyte scale. Few products in the
> >>industry are still very early in terms of supporting HDFS, Hive, HBase
> >>data access monitoring.
> >> As mentioned in the background, the business requirement and urgency to
> >>secure the data from users with malicious intent drove eBay to invest in
> >>building a real time data access monitoring solution from scratch to
> >>offer real time alerts and remediation features for malicious data
> >>access.
> >> With the power of open source distributed systems like Hadoop, Kafka
> >>and much more we were able to develop a data activity monitoring system
> >>that can scale, identify and stop malicious access in real time.
> >> Eagle allows admins to create standard access policies and rules for
> >>monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> >>machine learning models for modeling user profiles based on user access
> >>behaviour and use the model to alert on anomalies.
> >> 
> >> Current Status
> >> 
> >> Meritocracy
> >> Eagle has been deployed in production at eBay for monitoring billions
> >>of events per day from HDFS and Hive operations. From the start; the
> >>product has been built with focus on high scalability and application
> >>extensibility in mind and Eagle has demonstrated great performance in
> >>responding to suspicious events instantly and great flexibility in
> >>defining policy.
> >> 
> >> Community
> >> Eagle seeks to develop the developer and user communities during
> >>incubation.
> >> 
> >> Core Developers
> >> Eagle is currently being designed and developed by engineers from eBay
> >>Inc. ­ Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> >>Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> >>these core developers have deep expertise in developing monitoring
> >>products for the Hadoop ecosystem.
> >> 
> >> Alignment
> >> The ASF is a natural host for Eagle given that it is already the home
> >>of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> >>projects. Eagle leverages lot of Apache open-source products. Eagle was
> >>designed to offer real time insights into sensitive data access by
> >>actively monitoring the data access on various data sets in hadoop and
> >>an extensible alerting framework with a powerful policy engine. Eagle
> >>compliments the existing Hadoop platform area by providing a
> >>comprehensive monitoring and alerting solution for detecting sensitive
> >>data access threats based on preset policies and machine learning models
> >>for user behaviour analysis.
> >> 
> >> Known Risks
> >> 
> >> Orphaned Products
> >> The core developers of Eagle team work full time on this project. There
> >>is no risk of Eagle getting orphaned since eBay is extensively using it
> >>in their production Hadoop clusters and have plans to go beyond hadoop.
> >>For example, currently there are 7 hadoop clusters and 2 of them are
> >>being monitored using Hadoop Eagle in production. We have plans to
> >>extend it to all hadoop clusters and eventually other data platforms.
> >>There are 10¹s of policies onboarded and actively monitored with plans
> >>to onboard more use case. We are very confident that every hadoop
> >>cluster in the world will be monitored using Eagle for securing the
> >>hadoop ecosystem by actively monitoring for data access on sensitive
> >>data. We plan to extend and diversify this community further through
> >>Apache. We presented Eagle at the hadoop summit in china and garnered
> >>interest from different companies who use hadoop extensively.
> >> 
> >> Inexperience with Open Source
> >> The core developers are all active users and followers of open source.
> >>They are already committers and contributors to the Eagle Github
> >>project. All have been involved with the source code that has been
> >>released under an open source license, and several of them also have
> >>experience developing code in an open source environment. Though the
> >>core set of Developers do not have Apache Open Source experience, there
> >>are plans to onboard individuals with Apache open source experience on
> >>to the project. Apache Kylin PMC members are also in the same ebay
> >>organization. We work very closely with Apache Ranger committers and are
> >>looking forward to find meaningful integrations to improve the security
> >>of hadoop platform.
> >> 
> >> Homogenous Developers
> >> The core developers are from eBay. Today the problem of monitoring data
> >>activities to find and stop threats is a universal problem faced by all
> >>the businesses. Apache Incubation process encourages an open and diverse
> >>meritocratic community. Eagle intends to make every possible effort to
> >>build a diverse, vibrant and involved community and has already received
> >>substantial interest from various organizations.
> >> 
> >> Reliance on Salaried Developers
> >> eBay invested in Eagle as the monitoring solution for Hadoop clusters
> >>and some of its key engineers are working full time on the project. In
> >>addition, since there is a growing need for securing sensitive data
> >>access we need a data activity monitoring solution for Hadoop, we look
> >>forward to other Apache developers and researchers to contribute to the
> >>project. Additional contributors, including Apache committers have plans
> >>to join this effort shortly. Also key to addressing the risk associated
> >>with relying on Salaried developers from a single entity is to increase
> >>the diversity of the contributors and actively lobby for Domain experts
> >>in the security space to contribute. Eagle intends to do this.
> >> 
> >> Relationships with Other Apache Products
> >> Eagle has a strong relationship and dependency with Apache Hadoop,
> >>HBase, Spark, Kafka and Storm. Being part of Apache¹s Incubation
> >>community, could help with a closer collaboration among these projects
> >>and as well as others. An Excessive Fascination with the Apache Brand
> >>Eagle is proposing to enter incubation at Apache in order to help
> >>efforts to diversify the committer-base, not so much to capitalize on
> >>the Apache brand. The Eagle project is in production use already inside
> >>eBay, but is not expected to be an eBay product for external customers.
> >>As such, the Eagle project is not seeking to use the Apache brand as a
> >>marketing tool.
> >> 
> >> Documentation
> >> Information about Eagle can be found at https://github.com/eBay/Eagle.
> >>The following link provide more information about Eagle
> >>http://goeagle.io<http://goeagle.io/>.
> >> 
> >> Initial Source
> >> Eagle has been under development since 2014 by a team of engineers at
> >>eBay Inc. It is currently hosted on Github.com under an Apache license
> >>2.0 at https://github.com/eBay/Eagle. Once in incubation we will be
> >>moving the code base to apache git library.
> >> 
> >> External Dependencies
> >> Eagle has the following external dependencies.
> >> Basic
> >> €JDK 1.7+
> >> €Scala 2.10.4
> >> €Apache Maven
> >> €JUnit
> >> €Log4j
> >> €Slf4j
> >> €Apache Commons
> >> €Apache Commons Math3
> >> €Jackson
> >> €Siddhi CEP engine
> >> 
> >> Hadoop
> >> €Apache Hadoop
> >> €Apache HBase
> >> €Apache Hive
> >> €Apache Zookeeper
> >> €Apache Curator
> >> 
> >> Apache Spark
> >> €Spark Core Library
> >> 
> >> REST Service
> >> €Jersey
> >> 
> >> Query
> >> €Antlr
> >> 
> >> Stream processing
> >> €Apache Storm
> >> €Apache Kafka
> >> 
> >> Web
> >> €AngularJS
> >> €jQuery
> >> €Bootstrap V3
> >> €Moment JS
> >> €Admin LTE
> >> €html5shiv
> >> €respond
> >> €Fastclick
> >> €Date Range Picker
> >> €Flot JS
> >> 
> >> Cryptography
> >> Eagle will eventually support encryption on the wire. This is not one
> >>of the initial goals, and we do not expect Eagle to be a controlled
> >>export item due to the use of encryption. Eagle supports but does not
> >>require the Kerberos authentication mechanism to access secured Hadoop
> >>services.
> >> 
> >> Required Resources
> >> 
> >> Mailing List
> >> €eagle-private for private PMC discussions
> >> €eagle-dev for developers
> >> €eagle-commits for all commits
> >> €eagle-users for all eagle users
> >> 
> >> Subversion Directory
> >> €Git is the preferred source control system.
> >> 
> >> Issue Tracking
> >> €JIRA Eagle (Eagle)
> >> 
> >> Other Resources
> >> The existing code already has unit tests so we will make use of
> >>existing Apache continuous testing infrastructure. The resulting load
> >>should not be very large.
> >> 
> >> Initial Committers
> >> €Seshu Adunuthula <sadunuthula at ebay dot com>
> >> €Arun Manoharan <armanoharan at ebay dot com>
> >> €Edward Zhang <yonzhang at ebay dot com>
> >> €Hao Chen <hchen9 at ebay dot com>
> >> €Chaitali Gupta <cgupta at ebay dot com>
> >> €Libin Sun <libsun at ebay dot com>
> >> €Jilin Jiang <jiljiang at ebay dot com>
> >> €Qingwen Zhao <qingwzhao at ebay dot com>
> >> €Hemanth Dendukuri <hdendukuri at ebay dot com>
> >> €Senthil Kumar <senthilkumar at ebay dot com>
> >> 
> >> 
> >> Affiliations
> >> The initial committers are employees of eBay Inc.
> >> 
> >> Sponsors
> >> 
> >> Champion
> >> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> >> 
> >> Nominated Mentors
> >> €Owen O¹Malley < omalley at apache dot org > - Apache IPMC member,
> >>Hortonworks
> >> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> >> €Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> >>Hortonworks
> >> €Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> >>member
> >> €Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
> >>Hortonworks
> >> 
> >> Sponsoring Entity
> >> We are requesting the Incubator to sponsor this project.
> >> 
> >
> 
 		 	   		  

Re: [VOTE] Accept Eagle into Apache Incubation

["P. Taylor Goetz" <pt...@gmail.com>]

+1 (binding)

-Taylor

> On Oct 23, 2015, at 10:11 AM, Manoharan, Arun <ar...@ebay.com> wrote:
> 
> Hello Everyone,
> 
> Thanks for all the feedback on the Eagle Proposal.
> 
> I would like to call for a [VOTE] on Eagle joining the ASF as an incubation project.
> 
> The vote is open for 72 hours:
> 
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
> 
> Eagle is a Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities and take actions in real time. Eagle supports a wide variety of policies on HDFS data and Hive. Eagle also provides machine learning models for detecting anomalous user behavior in Hadoop.
> 
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
> 
> The text of the proposal is also available at the end of this email.
> 
> Thanks for your time and help.
> 
> Thanks,
> Arun
> 
> <COPY of the proposal in text format>
> 
> Eagle
> 
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities in hadoop and take actions.
> 
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time, enforces policies defined on sensitive data access and alerts or blocks user’s access to that sensitive data in real time. Eagle also creates user profiles based on the typical access behaviour for HDFS and Hive and sends alerts when anomalous behaviour is detected. Eagle can also import sensitive data information classified by external classification engines to help define its policies.
> 
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service and the visualization component. Eagle provides intuitive user interface to administer Eagle and an alert dashboard to respond to real time alerts.
> 
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data source into Eagle policy evaluation framework. For example, Eagle hdfs audit monitoring collects data from Kafka which is populated from namenode log4j appender or from logstash agent. Eagle hive monitoring collects hive query logs from running job through YARN API, which is designed to be scalable and fault-tolerant. Eagle uses HBase as storage for storing metadata and metrics data, and also supports relational database through configuration change.
> 
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an abstraction of Apache Storm. It can also be extended to other streaming engines. This abstraction allows developers to assemble data transformation, filtering, external data join etc. without physically bound to a specific streaming platform. Eagle streaming API allows developers to easily integrate business logic with Eagle policy engine and internally Eagle framework compiles business logic execution DAG into program primitives of underlying stream infrastructure e.g. Apache Storm. For example, Eagle HDFS monitoring transforms audit log from Namenode to object and joins sensitivity metadata, security zone metadata which are generated from external programs or configured by user. Eagle hive monitoring filters running jobs to get hive query string and parses query string into object and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API, scalable policy engine framework, extensible policy engine framework. Stream metadata API allows developers to declare event schema including what attributes constitute an event, what is the type for each attribute, and how to dynamically resolve attribute value in runtime when user configures policy. Scalable policy engine framework allows policies to be executed on different physical nodes in parallel. It is also used to define your own policy partitioner class. Policy engine framework together with streaming partitioning capability provided by all streaming platforms will make sure policies and events can be evaluated in a fully distributed way. Extensible policy engine framework allows developer to plugin a new policy engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user activity patterns or user profiles for Hadoop users based on the user behaviour in the platform. These user profiles are modeled using Machine Learning algorithms and used for detection of anomalous users activities. Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for generating user profile models. The model reads data from HDFS audit logs, preprocesses and aggregates data, and generates models using Spark programming APIs. Once models are generated, Eagle uses stream processing engine for near real-time anomaly detection to determine if any user’s activities are suspicious or not.
> 
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support comprehensive computation for huge set of data on the fly, for e.g. comprehensive filtering, aggregation, histogram, sorting, top, arithmetical expression, pagination etc. HBase is the data storage which Eagle supports as first-class citizen, relational database is supported as well. For HBase storage, Eagle query framework compiles user provided SQL-like query into HBase native filter objects and execute it through HBase coprocessor on the fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user to define policy with just a few clicks. It includes site management UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive resource browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which makes data security one of the top priorities of today’s enterprises. Hadoop is widely used across different verticals as a big data repository to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs. Our data in Hadoop is becoming bigger and bigger as our user base is seeing an exponential growth. Today there are variety of data sets available in Hadoop cluster for our users to consume. eBay has around 120 PB of data stored in HDFS across 6 different clusters and around 1800+ active hadoop users consuming data thru Hive, HBase and mapreduce jobs everyday to build applications using this data. With this astronomical growth of data there are also challenges in securing sensitive data and monitoring the access to this sensitive data. Today in large organizations HDFS is the defacto standard for storing big data. Data sets which includes and not limited to consumer sentiment, social media data, customer segmentation, web clicks, sensor data, geo-location and transaction data get stored in Hadoop for day to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are completely protected from security breaches. So we partnered very closely with our Information Security team to understand the requirements for Eagle to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today and can provide the features and functionality that we need to monitor the data access in the hadoop ecosystem at our scale. Hence with an excellent team of world class developers and several users, we have been able to bring Eagle into production as well as open source it.
> 
> Rationale
> In today’s world; data is an important asset for any company. Businesses are using data extensively to create amazing experiences for users. Data has to be protected and access to data should be secured from security breaches. Today Hadoop is not only used to store logs but also stores financial data, sensitive data sets, geographical data, user click stream data sets etc. which makes it more important to be protected from security breaches. To secure a data platform there are multiple things that need to happen. One is having a strong access control mechanism which today is provided by Apache Ranger and Apache Sentry. These tools provide the ability to provide fine grain access control mechanism to data sets on hadoop. But there is a big gap in terms of monitoring all the data access events and activities in order to securing the hadoop data platform. Together with strong access control, perimeter security and data access monitoring in place data in the hadoop clusters can be secured against breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional databases and data warehouse. Existing monitoring platforms cannot scale out to support fast growing data and petabyte scale. Few products in the industry are still very early in terms of supporting HDFS, Hive, HBase data access monitoring.
> As mentioned in the background, the business requirement and urgency to secure the data from users with malicious intent drove eBay to invest in building a real time data access monitoring solution from scratch to offer real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and much more we were able to develop a data activity monitoring system that can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for monitoring HDFS, Hive and HBase data. Eagle also provides out of box machine learning models for modeling user profiles based on user access behaviour and use the model to alert on anomalies.
> 
> Current Status
> 
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of events per day from HDFS and Hive operations. From the start; the product has been built with focus on high scalability and application extensibility in mind and Eagle has demonstrated great performance in responding to suspicious events instantly and great flexibility in defining policy.
> 
> Community
> Eagle seeks to develop the developer and user communities during incubation.
> 
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang, Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of these core developers have deep expertise in developing monitoring products for the Hadoop ecosystem.
> 
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data projects. Eagle leverages lot of Apache open-source products. Eagle was designed to offer real time insights into sensitive data access by actively monitoring the data access on various data sets in hadoop and an extensible alerting framework with a powerful policy engine. Eagle compliments the existing Hadoop platform area by providing a comprehensive monitoring and alerting solution for detecting sensitive data access threats based on preset policies and machine learning models for user behaviour analysis.
> 
> Known Risks
> 
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is no risk of Eagle getting orphaned since eBay is extensively using it in their production Hadoop clusters and have plans to go beyond hadoop. For example, currently there are 7 hadoop clusters and 2 of them are being monitored using Hadoop Eagle in production. We have plans to extend it to all hadoop clusters and eventually other data platforms. There are 10’s of policies onboarded and actively monitored with plans to onboard more use case. We are very confident that every hadoop cluster in the world will be monitored using Eagle for securing the hadoop ecosystem by actively monitoring for data access on sensitive data. We plan to extend and diversify this community further through Apache. We presented Eagle at the hadoop summit in china and garnered interest from different companies who use hadoop extensively.
> 
> Inexperience with Open Source
> The core developers are all active users and followers of open source. They are already committers and contributors to the Eagle Github project. All have been involved with the source code that has been released under an open source license, and several of them also have experience developing code in an open source environment. Though the core set of Developers do not have Apache Open Source experience, there are plans to onboard individuals with Apache open source experience on to the project. Apache Kylin PMC members are also in the same ebay organization. We work very closely with Apache Ranger committers and are looking forward to find meaningful integrations to improve the security of hadoop platform.
> 
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data activities to find and stop threats is a universal problem faced by all the businesses. Apache Incubation process encourages an open and diverse meritocratic community. Eagle intends to make every possible effort to build a diverse, vibrant and involved community and has already received substantial interest from various organizations.
> 
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and some of its key engineers are working full time on the project. In addition, since there is a growing need for securing sensitive data access we need a data activity monitoring solution for Hadoop, we look forward to other Apache developers and researchers to contribute to the project. Additional contributors, including Apache committers have plans to join this effort shortly. Also key to addressing the risk associated with relying on Salaried developers from a single entity is to increase the diversity of the contributors and actively lobby for Domain experts in the security space to contribute. Eagle intends to do this.
> 
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation community, could help with a closer collaboration among these projects and as well as others. An Excessive Fascination with the Apache Brand Eagle is proposing to enter incubation at Apache in order to help efforts to diversify the committer-base, not so much to capitalize on the Apache brand. The Eagle project is in production use already inside eBay, but is not expected to be an eBay product for external customers. As such, the Eagle project is not seeking to use the Apache brand as a marketing tool.
> 
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle. The following link provide more information about Eagle http://goeagle.io<http://goeagle.io/>.
> 
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay Inc. It is currently hosted on Github.com under an Apache license 2.0 at https://github.com/eBay/Eagle. Once in incubation we will be moving the code base to apache git library.
> 
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
> 
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
> 
> Apache Spark
> •Spark Core Library
> 
> REST Service
> •Jersey
> 
> Query
> •Antlr
> 
> Stream processing
> •Apache Storm
> •Apache Kafka
> 
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
> 
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of the initial goals, and we do not expect Eagle to be a controlled export item due to the use of encryption. Eagle supports but does not require the Kerberos authentication mechanism to access secured Hadoop services.
> 
> Required Resources
> 
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
> 
> Subversion Directory
> •Git is the preferred source control system.
> 
> Issue Tracking
> •JIRA Eagle (Eagle)
> 
> Other Resources
> The existing code already has unit tests so we will make use of existing Apache continuous testing infrastructure. The resulting load should not be very large.
> 
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
> 
> 
> Affiliations
> The initial committers are employees of eBay Inc.
> 
> Sponsors
> 
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> 
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member, Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member, Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
> 
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
> 

Re: [VOTE] Accept Eagle into Apache Incubation

[Julian Hyde <jh...@apache.org>]

+1 (binding)

> On Oct 23, 2015, at 10:13 AM, John D. Ament <jo...@apache.org> wrote:
> 
> +1
> On Oct 23, 2015 10:11, "Manoharan, Arun" <ar...@ebay.com> wrote:
> 
>> Hello Everyone,
>> 
>> Thanks for all the feedback on the Eagle Proposal.
>> 
>> I would like to call for a [VOTE] on Eagle joining the ASF as an
>> incubation project.
>> 
>> The vote is open for 72 hours:
>> 
>> [ ] +1 accept Eagle in the Incubator
>> [ ] ±0
>> [ ] -1 (please give reason)
>> 
>> Eagle is a Monitoring solution for Hadoop to instantly identify access to
>> sensitive data, recognize attacks, malicious activities and take actions in
>> real time. Eagle supports a wide variety of policies on HDFS data and Hive.
>> Eagle also provides machine learning models for detecting anomalous user
>> behavior in Hadoop.
>> 
>> The proposal is available on the wiki here:
>> https://wiki.apache.org/incubator/EagleProposal
>> 
>> The text of the proposal is also available at the end of this email.
>> 
>> Thanks for your time and help.
>> 
>> Thanks,
>> Arun
>> 
>> <COPY of the proposal in text format>
>> 
>> Eagle
>> 
>> Abstract
>> Eagle is an Open Source Monitoring solution for Hadoop to instantly
>> identify access to sensitive data, recognize attacks, malicious activities
>> in hadoop and take actions.
>> 
>> Proposal
>> Eagle audits access to HDFS files, Hive and HBase tables in real time,
>> enforces policies defined on sensitive data access and alerts or blocks
>> user’s access to that sensitive data in real time. Eagle also creates user
>> profiles based on the typical access behaviour for HDFS and Hive and sends
>> alerts when anomalous behaviour is detected. Eagle can also import
>> sensitive data information classified by external classification engines to
>> help define its policies.
>> 
>> Overview of Eagle
>> Eagle has 3 main parts.
>> 1.Data collection and storage - Eagle collects data from various hadoop
>> logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
>> 2.Data processing and policy engine - Eagle allows users to create
>> policies based on various metadata properties on HDFS, Hive and HBase data.
>> 3.Eagle services - Eagle services include policy manager, query service
>> and the visualization component. Eagle provides intuitive user interface to
>> administer Eagle and an alert dashboard to respond to real time alerts.
>> 
>> Data Collection and Storage:
>> Eagle provides programming API for extending Eagle to integrate any data
>> source into Eagle policy evaluation framework. For example, Eagle hdfs
>> audit monitoring collects data from Kafka which is populated from namenode
>> log4j appender or from logstash agent. Eagle hive monitoring collects hive
>> query logs from running job through YARN API, which is designed to be
>> scalable and fault-tolerant. Eagle uses HBase as storage for storing
>> metadata and metrics data, and also supports relational database through
>> configuration change.
>> 
>> Data Processing and Policy Engine:
>> Processing Engine: Eagle provides stream processing API which is an
>> abstraction of Apache Storm. It can also be extended to other streaming
>> engines. This abstraction allows developers to assemble data
>> transformation, filtering, external data join etc. without physically bound
>> to a specific streaming platform. Eagle streaming API allows developers to
>> easily integrate business logic with Eagle policy engine and internally
>> Eagle framework compiles business logic execution DAG into program
>> primitives of underlying stream infrastructure e.g. Apache Storm. For
>> example, Eagle HDFS monitoring transforms audit log from Namenode to object
>> and joins sensitivity metadata, security zone metadata which are generated
>> from external programs or configured by user. Eagle hive monitoring filters
>> running jobs to get hive query string and parses query string into object
>> and then joins sensitivity metadata.
>> Alerting Framework: Eagle Alert Framework includes stream metadata API,
>> scalable policy engine framework, extensible policy engine framework.
>> Stream metadata API allows developers to declare event schema including
>> what attributes constitute an event, what is the type for each attribute,
>> and how to dynamically resolve attribute value in runtime when user
>> configures policy. Scalable policy engine framework allows policies to be
>> executed on different physical nodes in parallel. It is also used to define
>> your own policy partitioner class. Policy engine framework together with
>> streaming partitioning capability provided by all streaming platforms will
>> make sure policies and events can be evaluated in a fully distributed way.
>> Extensible policy engine framework allows developer to plugin a new policy
>> engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
>> engine which Eagle supports as first-class citizen.
>> Machine Learning module: Eagle provides capabilities to define user
>> activity patterns or user profiles for Hadoop users based on the user
>> behaviour in the platform. These user profiles are modeled using Machine
>> Learning algorithms and used for detection of anomalous users activities.
>> Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for
>> generating user profile models. The model reads data from HDFS audit logs,
>> preprocesses and aggregates data, and generates models using Spark
>> programming APIs. Once models are generated, Eagle uses stream processing
>> engine for near real-time anomaly detection to determine if any user’s
>> activities are suspicious or not.
>> 
>> Eagle Services:
>> Query Service: Eagle provides SQL-like service API to support
>> comprehensive computation for huge set of data on the fly, for e.g.
>> comprehensive filtering, aggregation, histogram, sorting, top, arithmetical
>> expression, pagination etc. HBase is the data storage which Eagle supports
>> as first-class citizen, relational database is supported as well. For HBase
>> storage, Eagle query framework compiles user provided SQL-like query into
>> HBase native filter objects and execute it through HBase coprocessor on the
>> fly.
>> Policy Manager: Eagle policy manager provides UI and Restful API for user
>> to define policy with just a few clicks. It includes site management UI,
>> policy editor, sensitivity metadata import, HDFS or Hive sensitive resource
>> browsing, alert dashboards etc.
>> Background
>> Data is one of the most important assets for today’s businesses, which
>> makes data security one of the top priorities of today’s enterprises.
>> Hadoop is widely used across different verticals as a big data repository
>> to store this data in most modern enterprises.
>> At eBay we use hadoop platform extensively for our data processing needs.
>> Our data in Hadoop is becoming bigger and bigger as our user base is seeing
>> an exponential growth. Today there are variety of data sets available in
>> Hadoop cluster for our users to consume. eBay has around 120 PB of data
>> stored in HDFS across 6 different clusters and around 1800+ active hadoop
>> users consuming data thru Hive, HBase and mapreduce jobs everyday to build
>> applications using this data. With this astronomical growth of data there
>> are also challenges in securing sensitive data and monitoring the access to
>> this sensitive data. Today in large organizations HDFS is the defacto
>> standard for storing big data. Data sets which includes and not limited to
>> consumer sentiment, social media data, customer segmentation, web clicks,
>> sensor data, geo-location and transaction data get stored in Hadoop for day
>> to day business needs.
>> We at eBay want to make sure the sensitive data and data platforms are
>> completely protected from security breaches. So we partnered very closely
>> with our Information Security team to understand the requirements for Eagle
>> to monitor sensitive data access on hadoop:
>> 1.Ability to identify and stop security threats in real time
>> 2.Scale for big data (Support PB scale and Billions of events)
>> 3.Ability to create data access policies
>> 4.Support multiple data sources like HDFS, HBase, Hive
>> 5.Visualize alerts in real time
>> 6.Ability to block malicious access in real time
>> We did not find any data access monitoring solution that available today
>> and can provide the features and functionality that we need to monitor the
>> data access in the hadoop ecosystem at our scale. Hence with an excellent
>> team of world class developers and several users, we have been able to
>> bring Eagle into production as well as open source it.
>> 
>> Rationale
>> In today’s world; data is an important asset for any company. Businesses
>> are using data extensively to create amazing experiences for users. Data
>> has to be protected and access to data should be secured from security
>> breaches. Today Hadoop is not only used to store logs but also stores
>> financial data, sensitive data sets, geographical data, user click stream
>> data sets etc. which makes it more important to be protected from security
>> breaches. To secure a data platform there are multiple things that need to
>> happen. One is having a strong access control mechanism which today is
>> provided by Apache Ranger and Apache Sentry. These tools provide the
>> ability to provide fine grain access control mechanism to data sets on
>> hadoop. But there is a big gap in terms of monitoring all the data access
>> events and activities in order to securing the hadoop data platform.
>> Together with strong access control, perimeter security and data access
>> monitoring in place data in the hadoop clusters can be secured against
>> breaches. We looked around and found following:
>> Existing data activity monitoring products are designed for traditional
>> databases and data warehouse. Existing monitoring platforms cannot scale
>> out to support fast growing data and petabyte scale. Few products in the
>> industry are still very early in terms of supporting HDFS, Hive, HBase data
>> access monitoring.
>> As mentioned in the background, the business requirement and urgency to
>> secure the data from users with malicious intent drove eBay to invest in
>> building a real time data access monitoring solution from scratch to offer
>> real time alerts and remediation features for malicious data access.
>> With the power of open source distributed systems like Hadoop, Kafka and
>> much more we were able to develop a data activity monitoring system that
>> can scale, identify and stop malicious access in real time.
>> Eagle allows admins to create standard access policies and rules for
>> monitoring HDFS, Hive and HBase data. Eagle also provides out of box
>> machine learning models for modeling user profiles based on user access
>> behaviour and use the model to alert on anomalies.
>> 
>> Current Status
>> 
>> Meritocracy
>> Eagle has been deployed in production at eBay for monitoring billions of
>> events per day from HDFS and Hive operations. From the start; the product
>> has been built with focus on high scalability and application extensibility
>> in mind and Eagle has demonstrated great performance in responding to
>> suspicious events instantly and great flexibility in defining policy.
>> 
>> Community
>> Eagle seeks to develop the developer and user communities during
>> incubation.
>> 
>> Core Developers
>> Eagle is currently being designed and developed by engineers from eBay
>> Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
>> Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
>> these core developers have deep expertise in developing monitoring products
>> for the Hadoop ecosystem.
>> 
>> Alignment
>> The ASF is a natural host for Eagle given that it is already the home of
>> Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
>> projects. Eagle leverages lot of Apache open-source products. Eagle was
>> designed to offer real time insights into sensitive data access by actively
>> monitoring the data access on various data sets in hadoop and an extensible
>> alerting framework with a powerful policy engine. Eagle compliments the
>> existing Hadoop platform area by providing a comprehensive monitoring and
>> alerting solution for detecting sensitive data access threats based on
>> preset policies and machine learning models for user behaviour analysis.
>> 
>> Known Risks
>> 
>> Orphaned Products
>> The core developers of Eagle team work full time on this project. There is
>> no risk of Eagle getting orphaned since eBay is extensively using it in
>> their production Hadoop clusters and have plans to go beyond hadoop. For
>> example, currently there are 7 hadoop clusters and 2 of them are being
>> monitored using Hadoop Eagle in production. We have plans to extend it to
>> all hadoop clusters and eventually other data platforms. There are 10’s of
>> policies onboarded and actively monitored with plans to onboard more use
>> case. We are very confident that every hadoop cluster in the world will be
>> monitored using Eagle for securing the hadoop ecosystem by actively
>> monitoring for data access on sensitive data. We plan to extend and
>> diversify this community further through Apache. We presented Eagle at the
>> hadoop summit in china and garnered interest from different companies who
>> use hadoop extensively.
>> 
>> Inexperience with Open Source
>> The core developers are all active users and followers of open source.
>> They are already committers and contributors to the Eagle Github project.
>> All have been involved with the source code that has been released under an
>> open source license, and several of them also have experience developing
>> code in an open source environment. Though the core set of Developers do
>> not have Apache Open Source experience, there are plans to onboard
>> individuals with Apache open source experience on to the project. Apache
>> Kylin PMC members are also in the same ebay organization. We work very
>> closely with Apache Ranger committers and are looking forward to find
>> meaningful integrations to improve the security of hadoop platform.
>> 
>> Homogenous Developers
>> The core developers are from eBay. Today the problem of monitoring data
>> activities to find and stop threats is a universal problem faced by all the
>> businesses. Apache Incubation process encourages an open and diverse
>> meritocratic community. Eagle intends to make every possible effort to
>> build a diverse, vibrant and involved community and has already received
>> substantial interest from various organizations.
>> 
>> Reliance on Salaried Developers
>> eBay invested in Eagle as the monitoring solution for Hadoop clusters and
>> some of its key engineers are working full time on the project. In
>> addition, since there is a growing need for securing sensitive data access
>> we need a data activity monitoring solution for Hadoop, we look forward to
>> other Apache developers and researchers to contribute to the project.
>> Additional contributors, including Apache committers have plans to join
>> this effort shortly. Also key to addressing the risk associated with
>> relying on Salaried developers from a single entity is to increase the
>> diversity of the contributors and actively lobby for Domain experts in the
>> security space to contribute. Eagle intends to do this.
>> 
>> Relationships with Other Apache Products
>> Eagle has a strong relationship and dependency with Apache Hadoop, HBase,
>> Spark, Kafka and Storm. Being part of Apache’s Incubation community, could
>> help with a closer collaboration among these projects and as well as
>> others. An Excessive Fascination with the Apache Brand Eagle is proposing
>> to enter incubation at Apache in order to help efforts to diversify the
>> committer-base, not so much to capitalize on the Apache brand. The Eagle
>> project is in production use already inside eBay, but is not expected to be
>> an eBay product for external customers. As such, the Eagle project is not
>> seeking to use the Apache brand as a marketing tool.
>> 
>> Documentation
>> Information about Eagle can be found at https://github.com/eBay/Eagle.
>> The following link provide more information about Eagle http://goeagle.io<
>> http://goeagle.io/>.
>> 
>> Initial Source
>> Eagle has been under development since 2014 by a team of engineers at eBay
>> Inc. It is currently hosted on Github.com under an Apache license 2.0 at
>> https://github.com/eBay/Eagle. Once in incubation we will be moving the
>> code base to apache git library.
>> 
>> External Dependencies
>> Eagle has the following external dependencies.
>> Basic
>> •JDK 1.7+
>> •Scala 2.10.4
>> •Apache Maven
>> •JUnit
>> •Log4j
>> •Slf4j
>> •Apache Commons
>> •Apache Commons Math3
>> •Jackson
>> •Siddhi CEP engine
>> 
>> Hadoop
>> •Apache Hadoop
>> •Apache HBase
>> •Apache Hive
>> •Apache Zookeeper
>> •Apache Curator
>> 
>> Apache Spark
>> •Spark Core Library
>> 
>> REST Service
>> •Jersey
>> 
>> Query
>> •Antlr
>> 
>> Stream processing
>> •Apache Storm
>> •Apache Kafka
>> 
>> Web
>> •AngularJS
>> •jQuery
>> •Bootstrap V3
>> •Moment JS
>> •Admin LTE
>> •html5shiv
>> •respond
>> •Fastclick
>> •Date Range Picker
>> •Flot JS
>> 
>> Cryptography
>> Eagle will eventually support encryption on the wire. This is not one of
>> the initial goals, and we do not expect Eagle to be a controlled export
>> item due to the use of encryption. Eagle supports but does not require the
>> Kerberos authentication mechanism to access secured Hadoop services.
>> 
>> Required Resources
>> 
>> Mailing List
>> •eagle-private for private PMC discussions
>> •eagle-dev for developers
>> •eagle-commits for all commits
>> •eagle-users for all eagle users
>> 
>> Subversion Directory
>> •Git is the preferred source control system.
>> 
>> Issue Tracking
>> •JIRA Eagle (Eagle)
>> 
>> Other Resources
>> The existing code already has unit tests so we will make use of existing
>> Apache continuous testing infrastructure. The resulting load should not be
>> very large.
>> 
>> Initial Committers
>> •Seshu Adunuthula <sadunuthula at ebay dot com>
>> •Arun Manoharan <armanoharan at ebay dot com>
>> •Edward Zhang <yonzhang at ebay dot com>
>> •Hao Chen <hchen9 at ebay dot com>
>> •Chaitali Gupta <cgupta at ebay dot com>
>> •Libin Sun <libsun at ebay dot com>
>> •Jilin Jiang <jiljiang at ebay dot com>
>> •Qingwen Zhao <qingwzhao at ebay dot com>
>> •Hemanth Dendukuri <hdendukuri at ebay dot com>
>> •Senthil Kumar <senthilkumar at ebay dot com>
>> 
>> 
>> Affiliations
>> The initial committers are employees of eBay Inc.
>> 
>> Sponsors
>> 
>> Champion
>> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>> 
>> Nominated Mentors
>> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
>> Hortonworks
>> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
>> Hortonworks
>> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
>> member
>> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
>> 
>> Sponsoring Entity
>> We are requesting the Incubator to sponsor this project.
>> 
>> 


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Re: [VOTE] Accept Eagle into Apache Incubation

["John D. Ament" <jo...@apache.org>]

+1
On Oct 23, 2015 10:11, "Manoharan, Arun" <ar...@ebay.com> wrote:

> Hello Everyone,
>
> Thanks for all the feedback on the Eagle Proposal.
>
> I would like to call for a [VOTE] on Eagle joining the ASF as an
> incubation project.
>
> The vote is open for 72 hours:
>
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
>
> Eagle is a Monitoring solution for Hadoop to instantly identify access to
> sensitive data, recognize attacks, malicious activities and take actions in
> real time. Eagle supports a wide variety of policies on HDFS data and Hive.
> Eagle also provides machine learning models for detecting anomalous user
> behavior in Hadoop.
>
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
>
> The text of the proposal is also available at the end of this email.
>
> Thanks for your time and help.
>
> Thanks,
> Arun
>
> <COPY of the proposal in text format>
>
> Eagle
>
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly
> identify access to sensitive data, recognize attacks, malicious activities
> in hadoop and take actions.
>
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time,
> enforces policies defined on sensitive data access and alerts or blocks
> user’s access to that sensitive data in real time. Eagle also creates user
> profiles based on the typical access behaviour for HDFS and Hive and sends
> alerts when anomalous behaviour is detected. Eagle can also import
> sensitive data information classified by external classification engines to
> help define its policies.
>
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop
> logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create
> policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service
> and the visualization component. Eagle provides intuitive user interface to
> administer Eagle and an alert dashboard to respond to real time alerts.
>
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data
> source into Eagle policy evaluation framework. For example, Eagle hdfs
> audit monitoring collects data from Kafka which is populated from namenode
> log4j appender or from logstash agent. Eagle hive monitoring collects hive
> query logs from running job through YARN API, which is designed to be
> scalable and fault-tolerant. Eagle uses HBase as storage for storing
> metadata and metrics data, and also supports relational database through
> configuration change.
>
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an
> abstraction of Apache Storm. It can also be extended to other streaming
> engines. This abstraction allows developers to assemble data
> transformation, filtering, external data join etc. without physically bound
> to a specific streaming platform. Eagle streaming API allows developers to
> easily integrate business logic with Eagle policy engine and internally
> Eagle framework compiles business logic execution DAG into program
> primitives of underlying stream infrastructure e.g. Apache Storm. For
> example, Eagle HDFS monitoring transforms audit log from Namenode to object
> and joins sensitivity metadata, security zone metadata which are generated
> from external programs or configured by user. Eagle hive monitoring filters
> running jobs to get hive query string and parses query string into object
> and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API,
> scalable policy engine framework, extensible policy engine framework.
> Stream metadata API allows developers to declare event schema including
> what attributes constitute an event, what is the type for each attribute,
> and how to dynamically resolve attribute value in runtime when user
> configures policy. Scalable policy engine framework allows policies to be
> executed on different physical nodes in parallel. It is also used to define
> your own policy partitioner class. Policy engine framework together with
> streaming partitioning capability provided by all streaming platforms will
> make sure policies and events can be evaluated in a fully distributed way.
> Extensible policy engine framework allows developer to plugin a new policy
> engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user
> activity patterns or user profiles for Hadoop users based on the user
> behaviour in the platform. These user profiles are modeled using Machine
> Learning algorithms and used for detection of anomalous users activities.
> Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for
> generating user profile models. The model reads data from HDFS audit logs,
> preprocesses and aggregates data, and generates models using Spark
> programming APIs. Once models are generated, Eagle uses stream processing
> engine for near real-time anomaly detection to determine if any user’s
> activities are suspicious or not.
>
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support
> comprehensive computation for huge set of data on the fly, for e.g.
> comprehensive filtering, aggregation, histogram, sorting, top, arithmetical
> expression, pagination etc. HBase is the data storage which Eagle supports
> as first-class citizen, relational database is supported as well. For HBase
> storage, Eagle query framework compiles user provided SQL-like query into
> HBase native filter objects and execute it through HBase coprocessor on the
> fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user
> to define policy with just a few clicks. It includes site management UI,
> policy editor, sensitivity metadata import, HDFS or Hive sensitive resource
> browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which
> makes data security one of the top priorities of today’s enterprises.
> Hadoop is widely used across different verticals as a big data repository
> to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs.
> Our data in Hadoop is becoming bigger and bigger as our user base is seeing
> an exponential growth. Today there are variety of data sets available in
> Hadoop cluster for our users to consume. eBay has around 120 PB of data
> stored in HDFS across 6 different clusters and around 1800+ active hadoop
> users consuming data thru Hive, HBase and mapreduce jobs everyday to build
> applications using this data. With this astronomical growth of data there
> are also challenges in securing sensitive data and monitoring the access to
> this sensitive data. Today in large organizations HDFS is the defacto
> standard for storing big data. Data sets which includes and not limited to
> consumer sentiment, social media data, customer segmentation, web clicks,
> sensor data, geo-location and transaction data get stored in Hadoop for day
> to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are
> completely protected from security breaches. So we partnered very closely
> with our Information Security team to understand the requirements for Eagle
> to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today
> and can provide the features and functionality that we need to monitor the
> data access in the hadoop ecosystem at our scale. Hence with an excellent
> team of world class developers and several users, we have been able to
> bring Eagle into production as well as open source it.
>
> Rationale
> In today’s world; data is an important asset for any company. Businesses
> are using data extensively to create amazing experiences for users. Data
> has to be protected and access to data should be secured from security
> breaches. Today Hadoop is not only used to store logs but also stores
> financial data, sensitive data sets, geographical data, user click stream
> data sets etc. which makes it more important to be protected from security
> breaches. To secure a data platform there are multiple things that need to
> happen. One is having a strong access control mechanism which today is
> provided by Apache Ranger and Apache Sentry. These tools provide the
> ability to provide fine grain access control mechanism to data sets on
> hadoop. But there is a big gap in terms of monitoring all the data access
> events and activities in order to securing the hadoop data platform.
> Together with strong access control, perimeter security and data access
> monitoring in place data in the hadoop clusters can be secured against
> breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional
> databases and data warehouse. Existing monitoring platforms cannot scale
> out to support fast growing data and petabyte scale. Few products in the
> industry are still very early in terms of supporting HDFS, Hive, HBase data
> access monitoring.
> As mentioned in the background, the business requirement and urgency to
> secure the data from users with malicious intent drove eBay to invest in
> building a real time data access monitoring solution from scratch to offer
> real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and
> much more we were able to develop a data activity monitoring system that
> can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for
> monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> machine learning models for modeling user profiles based on user access
> behaviour and use the model to alert on anomalies.
>
> Current Status
>
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of
> events per day from HDFS and Hive operations. From the start; the product
> has been built with focus on high scalability and application extensibility
> in mind and Eagle has demonstrated great performance in responding to
> suspicious events instantly and great flexibility in defining policy.
>
> Community
> Eagle seeks to develop the developer and user communities during
> incubation.
>
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay
> Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> these core developers have deep expertise in developing monitoring products
> for the Hadoop ecosystem.
>
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of
> Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> projects. Eagle leverages lot of Apache open-source products. Eagle was
> designed to offer real time insights into sensitive data access by actively
> monitoring the data access on various data sets in hadoop and an extensible
> alerting framework with a powerful policy engine. Eagle compliments the
> existing Hadoop platform area by providing a comprehensive monitoring and
> alerting solution for detecting sensitive data access threats based on
> preset policies and machine learning models for user behaviour analysis.
>
> Known Risks
>
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is
> no risk of Eagle getting orphaned since eBay is extensively using it in
> their production Hadoop clusters and have plans to go beyond hadoop. For
> example, currently there are 7 hadoop clusters and 2 of them are being
> monitored using Hadoop Eagle in production. We have plans to extend it to
> all hadoop clusters and eventually other data platforms. There are 10’s of
> policies onboarded and actively monitored with plans to onboard more use
> case. We are very confident that every hadoop cluster in the world will be
> monitored using Eagle for securing the hadoop ecosystem by actively
> monitoring for data access on sensitive data. We plan to extend and
> diversify this community further through Apache. We presented Eagle at the
> hadoop summit in china and garnered interest from different companies who
> use hadoop extensively.
>
> Inexperience with Open Source
> The core developers are all active users and followers of open source.
> They are already committers and contributors to the Eagle Github project.
> All have been involved with the source code that has been released under an
> open source license, and several of them also have experience developing
> code in an open source environment. Though the core set of Developers do
> not have Apache Open Source experience, there are plans to onboard
> individuals with Apache open source experience on to the project. Apache
> Kylin PMC members are also in the same ebay organization. We work very
> closely with Apache Ranger committers and are looking forward to find
> meaningful integrations to improve the security of hadoop platform.
>
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data
> activities to find and stop threats is a universal problem faced by all the
> businesses. Apache Incubation process encourages an open and diverse
> meritocratic community. Eagle intends to make every possible effort to
> build a diverse, vibrant and involved community and has already received
> substantial interest from various organizations.
>
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and
> some of its key engineers are working full time on the project. In
> addition, since there is a growing need for securing sensitive data access
> we need a data activity monitoring solution for Hadoop, we look forward to
> other Apache developers and researchers to contribute to the project.
> Additional contributors, including Apache committers have plans to join
> this effort shortly. Also key to addressing the risk associated with
> relying on Salaried developers from a single entity is to increase the
> diversity of the contributors and actively lobby for Domain experts in the
> security space to contribute. Eagle intends to do this.
>
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase,
> Spark, Kafka and Storm. Being part of Apache’s Incubation community, could
> help with a closer collaboration among these projects and as well as
> others. An Excessive Fascination with the Apache Brand Eagle is proposing
> to enter incubation at Apache in order to help efforts to diversify the
> committer-base, not so much to capitalize on the Apache brand. The Eagle
> project is in production use already inside eBay, but is not expected to be
> an eBay product for external customers. As such, the Eagle project is not
> seeking to use the Apache brand as a marketing tool.
>
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle.
> The following link provide more information about Eagle http://goeagle.io<
> http://goeagle.io/>.
>
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay
> Inc. It is currently hosted on Github.com under an Apache license 2.0 at
> https://github.com/eBay/Eagle. Once in incubation we will be moving the
> code base to apache git library.
>
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
>
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
>
> Apache Spark
> •Spark Core Library
>
> REST Service
> •Jersey
>
> Query
> •Antlr
>
> Stream processing
> •Apache Storm
> •Apache Kafka
>
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
>
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of
> the initial goals, and we do not expect Eagle to be a controlled export
> item due to the use of encryption. Eagle supports but does not require the
> Kerberos authentication mechanism to access secured Hadoop services.
>
> Required Resources
>
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
>
> Subversion Directory
> •Git is the preferred source control system.
>
> Issue Tracking
> •JIRA Eagle (Eagle)
>
> Other Resources
> The existing code already has unit tests so we will make use of existing
> Apache continuous testing infrastructure. The resulting load should not be
> very large.
>
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
>
>
> Affiliations
> The initial committers are employees of eBay Inc.
>
> Sponsors
>
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
>
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
>
>

Re: [VOTE] Accept Eagle into Apache Incubation

[Luciano Resende <lu...@gmail.com>]

+1 (binding)

On Fri, Oct 23, 2015 at 7:11 AM, Manoharan, Arun <ar...@ebay.com>
wrote:

> Hello Everyone,
>
> Thanks for all the feedback on the Eagle Proposal.
>
> I would like to call for a [VOTE] on Eagle joining the ASF as an
> incubation project.
>
> The vote is open for 72 hours:
>
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
>
> Eagle is a Monitoring solution for Hadoop to instantly identify access to
> sensitive data, recognize attacks, malicious activities and take actions in
> real time. Eagle supports a wide variety of policies on HDFS data and Hive.
> Eagle also provides machine learning models for detecting anomalous user
> behavior in Hadoop.
>
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
>
> The text of the proposal is also available at the end of this email.
>
> Thanks for your time and help.
>
> Thanks,
> Arun
>
> <COPY of the proposal in text format>
>
> Eagle
>
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly
> identify access to sensitive data, recognize attacks, malicious activities
> in hadoop and take actions.
>
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time,
> enforces policies defined on sensitive data access and alerts or blocks
> user’s access to that sensitive data in real time. Eagle also creates user
> profiles based on the typical access behaviour for HDFS and Hive and sends
> alerts when anomalous behaviour is detected. Eagle can also import
> sensitive data information classified by external classification engines to
> help define its policies.
>
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop
> logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create
> policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service
> and the visualization component. Eagle provides intuitive user interface to
> administer Eagle and an alert dashboard to respond to real time alerts.
>
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data
> source into Eagle policy evaluation framework. For example, Eagle hdfs
> audit monitoring collects data from Kafka which is populated from namenode
> log4j appender or from logstash agent. Eagle hive monitoring collects hive
> query logs from running job through YARN API, which is designed to be
> scalable and fault-tolerant. Eagle uses HBase as storage for storing
> metadata and metrics data, and also supports relational database through
> configuration change.
>
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an
> abstraction of Apache Storm. It can also be extended to other streaming
> engines. This abstraction allows developers to assemble data
> transformation, filtering, external data join etc. without physically bound
> to a specific streaming platform. Eagle streaming API allows developers to
> easily integrate business logic with Eagle policy engine and internally
> Eagle framework compiles business logic execution DAG into program
> primitives of underlying stream infrastructure e.g. Apache Storm. For
> example, Eagle HDFS monitoring transforms audit log from Namenode to object
> and joins sensitivity metadata, security zone metadata which are generated
> from external programs or configured by user. Eagle hive monitoring filters
> running jobs to get hive query string and parses query string into object
> and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API,
> scalable policy engine framework, extensible policy engine framework.
> Stream metadata API allows developers to declare event schema including
> what attributes constitute an event, what is the type for each attribute,
> and how to dynamically resolve attribute value in runtime when user
> configures policy. Scalable policy engine framework allows policies to be
> executed on different physical nodes in parallel. It is also used to define
> your own policy partitioner class. Policy engine framework together with
> streaming partitioning capability provided by all streaming platforms will
> make sure policies and events can be evaluated in a fully distributed way.
> Extensible policy engine framework allows developer to plugin a new policy
> engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user
> activity patterns or user profiles for Hadoop users based on the user
> behaviour in the platform. These user profiles are modeled using Machine
> Learning algorithms and used for detection of anomalous users activities.
> Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for
> generating user profile models. The model reads data from HDFS audit logs,
> preprocesses and aggregates data, and generates models using Spark
> programming APIs. Once models are generated, Eagle uses stream processing
> engine for near real-time anomaly detection to determine if any user’s
> activities are suspicious or not.
>
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support
> comprehensive computation for huge set of data on the fly, for e.g.
> comprehensive filtering, aggregation, histogram, sorting, top, arithmetical
> expression, pagination etc. HBase is the data storage which Eagle supports
> as first-class citizen, relational database is supported as well. For HBase
> storage, Eagle query framework compiles user provided SQL-like query into
> HBase native filter objects and execute it through HBase coprocessor on the
> fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user
> to define policy with just a few clicks. It includes site management UI,
> policy editor, sensitivity metadata import, HDFS or Hive sensitive resource
> browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which
> makes data security one of the top priorities of today’s enterprises.
> Hadoop is widely used across different verticals as a big data repository
> to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs.
> Our data in Hadoop is becoming bigger and bigger as our user base is seeing
> an exponential growth. Today there are variety of data sets available in
> Hadoop cluster for our users to consume. eBay has around 120 PB of data
> stored in HDFS across 6 different clusters and around 1800+ active hadoop
> users consuming data thru Hive, HBase and mapreduce jobs everyday to build
> applications using this data. With this astronomical growth of data there
> are also challenges in securing sensitive data and monitoring the access to
> this sensitive data. Today in large organizations HDFS is the defacto
> standard for storing big data. Data sets which includes and not limited to
> consumer sentiment, social media data, customer segmentation, web clicks,
> sensor data, geo-location and transaction data get stored in Hadoop for day
> to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are
> completely protected from security breaches. So we partnered very closely
> with our Information Security team to understand the requirements for Eagle
> to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today
> and can provide the features and functionality that we need to monitor the
> data access in the hadoop ecosystem at our scale. Hence with an excellent
> team of world class developers and several users, we have been able to
> bring Eagle into production as well as open source it.
>
> Rationale
> In today’s world; data is an important asset for any company. Businesses
> are using data extensively to create amazing experiences for users. Data
> has to be protected and access to data should be secured from security
> breaches. Today Hadoop is not only used to store logs but also stores
> financial data, sensitive data sets, geographical data, user click stream
> data sets etc. which makes it more important to be protected from security
> breaches. To secure a data platform there are multiple things that need to
> happen. One is having a strong access control mechanism which today is
> provided by Apache Ranger and Apache Sentry. These tools provide the
> ability to provide fine grain access control mechanism to data sets on
> hadoop. But there is a big gap in terms of monitoring all the data access
> events and activities in order to securing the hadoop data platform.
> Together with strong access control, perimeter security and data access
> monitoring in place data in the hadoop clusters can be secured against
> breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional
> databases and data warehouse. Existing monitoring platforms cannot scale
> out to support fast growing data and petabyte scale. Few products in the
> industry are still very early in terms of supporting HDFS, Hive, HBase data
> access monitoring.
> As mentioned in the background, the business requirement and urgency to
> secure the data from users with malicious intent drove eBay to invest in
> building a real time data access monitoring solution from scratch to offer
> real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and
> much more we were able to develop a data activity monitoring system that
> can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for
> monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> machine learning models for modeling user profiles based on user access
> behaviour and use the model to alert on anomalies.
>
> Current Status
>
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of
> events per day from HDFS and Hive operations. From the start; the product
> has been built with focus on high scalability and application extensibility
> in mind and Eagle has demonstrated great performance in responding to
> suspicious events instantly and great flexibility in defining policy.
>
> Community
> Eagle seeks to develop the developer and user communities during
> incubation.
>
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay
> Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> these core developers have deep expertise in developing monitoring products
> for the Hadoop ecosystem.
>
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of
> Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> projects. Eagle leverages lot of Apache open-source products. Eagle was
> designed to offer real time insights into sensitive data access by actively
> monitoring the data access on various data sets in hadoop and an extensible
> alerting framework with a powerful policy engine. Eagle compliments the
> existing Hadoop platform area by providing a comprehensive monitoring and
> alerting solution for detecting sensitive data access threats based on
> preset policies and machine learning models for user behaviour analysis.
>
> Known Risks
>
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is
> no risk of Eagle getting orphaned since eBay is extensively using it in
> their production Hadoop clusters and have plans to go beyond hadoop. For
> example, currently there are 7 hadoop clusters and 2 of them are being
> monitored using Hadoop Eagle in production. We have plans to extend it to
> all hadoop clusters and eventually other data platforms. There are 10’s of
> policies onboarded and actively monitored with plans to onboard more use
> case. We are very confident that every hadoop cluster in the world will be
> monitored using Eagle for securing the hadoop ecosystem by actively
> monitoring for data access on sensitive data. We plan to extend and
> diversify this community further through Apache. We presented Eagle at the
> hadoop summit in china and garnered interest from different companies who
> use hadoop extensively.
>
> Inexperience with Open Source
> The core developers are all active users and followers of open source.
> They are already committers and contributors to the Eagle Github project.
> All have been involved with the source code that has been released under an
> open source license, and several of them also have experience developing
> code in an open source environment. Though the core set of Developers do
> not have Apache Open Source experience, there are plans to onboard
> individuals with Apache open source experience on to the project. Apache
> Kylin PMC members are also in the same ebay organization. We work very
> closely with Apache Ranger committers and are looking forward to find
> meaningful integrations to improve the security of hadoop platform.
>
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data
> activities to find and stop threats is a universal problem faced by all the
> businesses. Apache Incubation process encourages an open and diverse
> meritocratic community. Eagle intends to make every possible effort to
> build a diverse, vibrant and involved community and has already received
> substantial interest from various organizations.
>
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and
> some of its key engineers are working full time on the project. In
> addition, since there is a growing need for securing sensitive data access
> we need a data activity monitoring solution for Hadoop, we look forward to
> other Apache developers and researchers to contribute to the project.
> Additional contributors, including Apache committers have plans to join
> this effort shortly. Also key to addressing the risk associated with
> relying on Salaried developers from a single entity is to increase the
> diversity of the contributors and actively lobby for Domain experts in the
> security space to contribute. Eagle intends to do this.
>
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase,
> Spark, Kafka and Storm. Being part of Apache’s Incubation community, could
> help with a closer collaboration among these projects and as well as
> others. An Excessive Fascination with the Apache Brand Eagle is proposing
> to enter incubation at Apache in order to help efforts to diversify the
> committer-base, not so much to capitalize on the Apache brand. The Eagle
> project is in production use already inside eBay, but is not expected to be
> an eBay product for external customers. As such, the Eagle project is not
> seeking to use the Apache brand as a marketing tool.
>
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle.
> The following link provide more information about Eagle http://goeagle.io<
> http://goeagle.io/>.
>
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay
> Inc. It is currently hosted on Github.com under an Apache license 2.0 at
> https://github.com/eBay/Eagle. Once in incubation we will be moving the
> code base to apache git library.
>
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
>
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
>
> Apache Spark
> •Spark Core Library
>
> REST Service
> •Jersey
>
> Query
> •Antlr
>
> Stream processing
> •Apache Storm
> •Apache Kafka
>
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
>
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of
> the initial goals, and we do not expect Eagle to be a controlled export
> item due to the use of encryption. Eagle supports but does not require the
> Kerberos authentication mechanism to access secured Hadoop services.
>
> Required Resources
>
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
>
> Subversion Directory
> •Git is the preferred source control system.
>
> Issue Tracking
> •JIRA Eagle (Eagle)
>
> Other Resources
> The existing code already has unit tests so we will make use of existing
> Apache continuous testing infrastructure. The resulting load should not be
> very large.
>
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
>
>
> Affiliations
> The initial committers are employees of eBay Inc.
>
> Sponsors
>
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
>
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
>
>


-- 
Luciano Resende
http://people.apache.org/~lresende
http://twitter.com/lresende1975
http://lresende.blogspot.com/

Re: [VOTE] Accept Eagle into Apache Incubation

[Ted Dunning <te...@gmail.com>]

+1 (binding)


On Fri, Oct 23, 2015 at 7:11 AM, Manoharan, Arun <ar...@ebay.com>
wrote:

> Hello Everyone,
>
> Thanks for all the feedback on the Eagle Proposal.
>
> I would like to call for a [VOTE] on Eagle joining the ASF as an
> incubation project.
>
> The vote is open for 72 hours:
>
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
>
> Eagle is a Monitoring solution for Hadoop to instantly identify access to
> sensitive data, recognize attacks, malicious activities and take actions in
> real time. Eagle supports a wide variety of policies on HDFS data and Hive.
> Eagle also provides machine learning models for detecting anomalous user
> behavior in Hadoop.
>
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
>
> The text of the proposal is also available at the end of this email.
>
> Thanks for your time and help.
>
> Thanks,
> Arun
>
> <COPY of the proposal in text format>
>
> Eagle
>
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly
> identify access to sensitive data, recognize attacks, malicious activities
> in hadoop and take actions.
>
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time,
> enforces policies defined on sensitive data access and alerts or blocks
> user’s access to that sensitive data in real time. Eagle also creates user
> profiles based on the typical access behaviour for HDFS and Hive and sends
> alerts when anomalous behaviour is detected. Eagle can also import
> sensitive data information classified by external classification engines to
> help define its policies.
>
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop
> logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create
> policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service
> and the visualization component. Eagle provides intuitive user interface to
> administer Eagle and an alert dashboard to respond to real time alerts.
>
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data
> source into Eagle policy evaluation framework. For example, Eagle hdfs
> audit monitoring collects data from Kafka which is populated from namenode
> log4j appender or from logstash agent. Eagle hive monitoring collects hive
> query logs from running job through YARN API, which is designed to be
> scalable and fault-tolerant. Eagle uses HBase as storage for storing
> metadata and metrics data, and also supports relational database through
> configuration change.
>
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an
> abstraction of Apache Storm. It can also be extended to other streaming
> engines. This abstraction allows developers to assemble data
> transformation, filtering, external data join etc. without physically bound
> to a specific streaming platform. Eagle streaming API allows developers to
> easily integrate business logic with Eagle policy engine and internally
> Eagle framework compiles business logic execution DAG into program
> primitives of underlying stream infrastructure e.g. Apache Storm. For
> example, Eagle HDFS monitoring transforms audit log from Namenode to object
> and joins sensitivity metadata, security zone metadata which are generated
> from external programs or configured by user. Eagle hive monitoring filters
> running jobs to get hive query string and parses query string into object
> and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API,
> scalable policy engine framework, extensible policy engine framework.
> Stream metadata API allows developers to declare event schema including
> what attributes constitute an event, what is the type for each attribute,
> and how to dynamically resolve attribute value in runtime when user
> configures policy. Scalable policy engine framework allows policies to be
> executed on different physical nodes in parallel. It is also used to define
> your own policy partitioner class. Policy engine framework together with
> streaming partitioning capability provided by all streaming platforms will
> make sure policies and events can be evaluated in a fully distributed way.
> Extensible policy engine framework allows developer to plugin a new policy
> engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user
> activity patterns or user profiles for Hadoop users based on the user
> behaviour in the platform. These user profiles are modeled using Machine
> Learning algorithms and used for detection of anomalous users activities.
> Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for
> generating user profile models. The model reads data from HDFS audit logs,
> preprocesses and aggregates data, and generates models using Spark
> programming APIs. Once models are generated, Eagle uses stream processing
> engine for near real-time anomaly detection to determine if any user’s
> activities are suspicious or not.
>
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support
> comprehensive computation for huge set of data on the fly, for e.g.
> comprehensive filtering, aggregation, histogram, sorting, top, arithmetical
> expression, pagination etc. HBase is the data storage which Eagle supports
> as first-class citizen, relational database is supported as well. For HBase
> storage, Eagle query framework compiles user provided SQL-like query into
> HBase native filter objects and execute it through HBase coprocessor on the
> fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user
> to define policy with just a few clicks. It includes site management UI,
> policy editor, sensitivity metadata import, HDFS or Hive sensitive resource
> browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which
> makes data security one of the top priorities of today’s enterprises.
> Hadoop is widely used across different verticals as a big data repository
> to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs.
> Our data in Hadoop is becoming bigger and bigger as our user base is seeing
> an exponential growth. Today there are variety of data sets available in
> Hadoop cluster for our users to consume. eBay has around 120 PB of data
> stored in HDFS across 6 different clusters and around 1800+ active hadoop
> users consuming data thru Hive, HBase and mapreduce jobs everyday to build
> applications using this data. With this astronomical growth of data there
> are also challenges in securing sensitive data and monitoring the access to
> this sensitive data. Today in large organizations HDFS is the defacto
> standard for storing big data. Data sets which includes and not limited to
> consumer sentiment, social media data, customer segmentation, web clicks,
> sensor data, geo-location and transaction data get stored in Hadoop for day
> to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are
> completely protected from security breaches. So we partnered very closely
> with our Information Security team to understand the requirements for Eagle
> to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today
> and can provide the features and functionality that we need to monitor the
> data access in the hadoop ecosystem at our scale. Hence with an excellent
> team of world class developers and several users, we have been able to
> bring Eagle into production as well as open source it.
>
> Rationale
> In today’s world; data is an important asset for any company. Businesses
> are using data extensively to create amazing experiences for users. Data
> has to be protected and access to data should be secured from security
> breaches. Today Hadoop is not only used to store logs but also stores
> financial data, sensitive data sets, geographical data, user click stream
> data sets etc. which makes it more important to be protected from security
> breaches. To secure a data platform there are multiple things that need to
> happen. One is having a strong access control mechanism which today is
> provided by Apache Ranger and Apache Sentry. These tools provide the
> ability to provide fine grain access control mechanism to data sets on
> hadoop. But there is a big gap in terms of monitoring all the data access
> events and activities in order to securing the hadoop data platform.
> Together with strong access control, perimeter security and data access
> monitoring in place data in the hadoop clusters can be secured against
> breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional
> databases and data warehouse. Existing monitoring platforms cannot scale
> out to support fast growing data and petabyte scale. Few products in the
> industry are still very early in terms of supporting HDFS, Hive, HBase data
> access monitoring.
> As mentioned in the background, the business requirement and urgency to
> secure the data from users with malicious intent drove eBay to invest in
> building a real time data access monitoring solution from scratch to offer
> real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and
> much more we were able to develop a data activity monitoring system that
> can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for
> monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> machine learning models for modeling user profiles based on user access
> behaviour and use the model to alert on anomalies.
>
> Current Status
>
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of
> events per day from HDFS and Hive operations. From the start; the product
> has been built with focus on high scalability and application extensibility
> in mind and Eagle has demonstrated great performance in responding to
> suspicious events instantly and great flexibility in defining policy.
>
> Community
> Eagle seeks to develop the developer and user communities during
> incubation.
>
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay
> Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> these core developers have deep expertise in developing monitoring products
> for the Hadoop ecosystem.
>
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of
> Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> projects. Eagle leverages lot of Apache open-source products. Eagle was
> designed to offer real time insights into sensitive data access by actively
> monitoring the data access on various data sets in hadoop and an extensible
> alerting framework with a powerful policy engine. Eagle compliments the
> existing Hadoop platform area by providing a comprehensive monitoring and
> alerting solution for detecting sensitive data access threats based on
> preset policies and machine learning models for user behaviour analysis.
>
> Known Risks
>
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is
> no risk of Eagle getting orphaned since eBay is extensively using it in
> their production Hadoop clusters and have plans to go beyond hadoop. For
> example, currently there are 7 hadoop clusters and 2 of them are being
> monitored using Hadoop Eagle in production. We have plans to extend it to
> all hadoop clusters and eventually other data platforms. There are 10’s of
> policies onboarded and actively monitored with plans to onboard more use
> case. We are very confident that every hadoop cluster in the world will be
> monitored using Eagle for securing the hadoop ecosystem by actively
> monitoring for data access on sensitive data. We plan to extend and
> diversify this community further through Apache. We presented Eagle at the
> hadoop summit in china and garnered interest from different companies who
> use hadoop extensively.
>
> Inexperience with Open Source
> The core developers are all active users and followers of open source.
> They are already committers and contributors to the Eagle Github project.
> All have been involved with the source code that has been released under an
> open source license, and several of them also have experience developing
> code in an open source environment. Though the core set of Developers do
> not have Apache Open Source experience, there are plans to onboard
> individuals with Apache open source experience on to the project. Apache
> Kylin PMC members are also in the same ebay organization. We work very
> closely with Apache Ranger committers and are looking forward to find
> meaningful integrations to improve the security of hadoop platform.
>
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data
> activities to find and stop threats is a universal problem faced by all the
> businesses. Apache Incubation process encourages an open and diverse
> meritocratic community. Eagle intends to make every possible effort to
> build a diverse, vibrant and involved community and has already received
> substantial interest from various organizations.
>
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and
> some of its key engineers are working full time on the project. In
> addition, since there is a growing need for securing sensitive data access
> we need a data activity monitoring solution for Hadoop, we look forward to
> other Apache developers and researchers to contribute to the project.
> Additional contributors, including Apache committers have plans to join
> this effort shortly. Also key to addressing the risk associated with
> relying on Salaried developers from a single entity is to increase the
> diversity of the contributors and actively lobby for Domain experts in the
> security space to contribute. Eagle intends to do this.
>
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase,
> Spark, Kafka and Storm. Being part of Apache’s Incubation community, could
> help with a closer collaboration among these projects and as well as
> others. An Excessive Fascination with the Apache Brand Eagle is proposing
> to enter incubation at Apache in order to help efforts to diversify the
> committer-base, not so much to capitalize on the Apache brand. The Eagle
> project is in production use already inside eBay, but is not expected to be
> an eBay product for external customers. As such, the Eagle project is not
> seeking to use the Apache brand as a marketing tool.
>
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle.
> The following link provide more information about Eagle http://goeagle.io<
> http://goeagle.io/>.
>
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay
> Inc. It is currently hosted on Github.com under an Apache license 2.0 at
> https://github.com/eBay/Eagle. Once in incubation we will be moving the
> code base to apache git library.
>
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
>
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
>
> Apache Spark
> •Spark Core Library
>
> REST Service
> •Jersey
>
> Query
> •Antlr
>
> Stream processing
> •Apache Storm
> •Apache Kafka
>
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
>
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of
> the initial goals, and we do not expect Eagle to be a controlled export
> item due to the use of encryption. Eagle supports but does not require the
> Kerberos authentication mechanism to access secured Hadoop services.
>
> Required Resources
>
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
>
> Subversion Directory
> •Git is the preferred source control system.
>
> Issue Tracking
> •JIRA Eagle (Eagle)
>
> Other Resources
> The existing code already has unit tests so we will make use of existing
> Apache continuous testing infrastructure. The resulting load should not be
> very large.
>
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
>
>
> Affiliations
> The initial committers are employees of eBay Inc.
>
> Sponsors
>
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
>
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
>
>

Re: [VOTE] Accept Eagle into Apache Incubation

["Adunuthula, Seshu" <sa...@ebay.com>]

+1 (non binding)

On 10/23/15, 9:52 AM, "Hitesh Shah" <hi...@apache.org> wrote:

>+1 (binding)
>
>‹ Hitesh
>
>On Oct 23, 2015, at 7:11 AM, Manoharan, Arun <ar...@ebay.com> wrote:
>
>> Hello Everyone,
>> 
>> Thanks for all the feedback on the Eagle Proposal.
>> 
>> I would like to call for a [VOTE] on Eagle joining the ASF as an
>>incubation project.
>> 
>> The vote is open for 72 hours:
>> 
>> [ ] +1 accept Eagle in the Incubator
>> [ ] ±0
>> [ ] -1 (please give reason)
>> 
>> Eagle is a Monitoring solution for Hadoop to instantly identify access
>>to sensitive data, recognize attacks, malicious activities and take
>>actions in real time. Eagle supports a wide variety of policies on HDFS
>>data and Hive. Eagle also provides machine learning models for detecting
>>anomalous user behavior in Hadoop.
>> 
>> The proposal is available on the wiki here:
>> https://wiki.apache.org/incubator/EagleProposal
>> 
>> The text of the proposal is also available at the end of this email.
>> 
>> Thanks for your time and help.
>> 
>> Thanks,
>> Arun
>> 
>> <COPY of the proposal in text format>
>> 
>> Eagle
>> 
>> Abstract
>> Eagle is an Open Source Monitoring solution for Hadoop to instantly
>>identify access to sensitive data, recognize attacks, malicious
>>activities in hadoop and take actions.
>> 
>> Proposal
>> Eagle audits access to HDFS files, Hive and HBase tables in real time,
>>enforces policies defined on sensitive data access and alerts or blocks
>>user¹s access to that sensitive data in real time. Eagle also creates
>>user profiles based on the typical access behaviour for HDFS and Hive
>>and sends alerts when anomalous behaviour is detected. Eagle can also
>>import sensitive data information classified by external classification
>>engines to help define its policies.
>> 
>> Overview of Eagle
>> Eagle has 3 main parts.
>> 1.Data collection and storage - Eagle collects data from various hadoop
>>logs in real time using Kafka/Yarn API and uses HDFS and HBase for
>>storage.
>> 2.Data processing and policy engine - Eagle allows users to create
>>policies based on various metadata properties on HDFS, Hive and HBase
>>data.
>> 3.Eagle services - Eagle services include policy manager, query service
>>and the visualization component. Eagle provides intuitive user interface
>>to administer Eagle and an alert dashboard to respond to real time
>>alerts.
>> 
>> Data Collection and Storage:
>> Eagle provides programming API for extending Eagle to integrate any
>>data source into Eagle policy evaluation framework. For example, Eagle
>>hdfs audit monitoring collects data from Kafka which is populated from
>>namenode log4j appender or from logstash agent. Eagle hive monitoring
>>collects hive query logs from running job through YARN API, which is
>>designed to be scalable and fault-tolerant. Eagle uses HBase as storage
>>for storing metadata and metrics data, and also supports relational
>>database through configuration change.
>> 
>> Data Processing and Policy Engine:
>> Processing Engine: Eagle provides stream processing API which is an
>>abstraction of Apache Storm. It can also be extended to other streaming
>>engines. This abstraction allows developers to assemble data
>>transformation, filtering, external data join etc. without physically
>>bound to a specific streaming platform. Eagle streaming API allows
>>developers to easily integrate business logic with Eagle policy engine
>>and internally Eagle framework compiles business logic execution DAG
>>into program primitives of underlying stream infrastructure e.g. Apache
>>Storm. For example, Eagle HDFS monitoring transforms audit log from
>>Namenode to object and joins sensitivity metadata, security zone
>>metadata which are generated from external programs or configured by
>>user. Eagle hive monitoring filters running jobs to get hive query
>>string and parses query string into object and then joins sensitivity
>>metadata.
>> Alerting Framework: Eagle Alert Framework includes stream metadata API,
>>scalable policy engine framework, extensible policy engine framework.
>>Stream metadata API allows developers to declare event schema including
>>what attributes constitute an event, what is the type for each
>>attribute, and how to dynamically resolve attribute value in runtime
>>when user configures policy. Scalable policy engine framework allows
>>policies to be executed on different physical nodes in parallel. It is
>>also used to define your own policy partitioner class. Policy engine
>>framework together with streaming partitioning capability provided by
>>all streaming platforms will make sure policies and events can be
>>evaluated in a fully distributed way. Extensible policy engine framework
>>allows developer to plugin a new policy engine with a few lines of
>>codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports
>>as first-class citizen.
>> Machine Learning module: Eagle provides capabilities to define user
>>activity patterns or user profiles for Hadoop users based on the user
>>behaviour in the platform. These user profiles are modeled using Machine
>>Learning algorithms and used for detection of anomalous users
>>activities. Eagle uses Eigen Value Decomposition, and Density Estimation
>>algorithms for generating user profile models. The model reads data from
>>HDFS audit logs, preprocesses and aggregates data, and generates models
>>using Spark programming APIs. Once models are generated, Eagle uses
>>stream processing engine for near real-time anomaly detection to
>>determine if any user¹s activities are suspicious or not.
>> 
>> Eagle Services:
>> Query Service: Eagle provides SQL-like service API to support
>>comprehensive computation for huge set of data on the fly, for e.g.
>>comprehensive filtering, aggregation, histogram, sorting, top,
>>arithmetical expression, pagination etc. HBase is the data storage which
>>Eagle supports as first-class citizen, relational database is supported
>>as well. For HBase storage, Eagle query framework compiles user provided
>>SQL-like query into HBase native filter objects and execute it through
>>HBase coprocessor on the fly.
>> Policy Manager: Eagle policy manager provides UI and Restful API for
>>user to define policy with just a few clicks. It includes site
>>management UI, policy editor, sensitivity metadata import, HDFS or Hive
>>sensitive resource browsing, alert dashboards etc.
>> Background
>> Data is one of the most important assets for today¹s businesses, which
>>makes data security one of the top priorities of today¹s enterprises.
>>Hadoop is widely used across different verticals as a big data
>>repository to store this data in most modern enterprises.
>> At eBay we use hadoop platform extensively for our data processing
>>needs. Our data in Hadoop is becoming bigger and bigger as our user base
>>is seeing an exponential growth. Today there are variety of data sets
>>available in Hadoop cluster for our users to consume. eBay has around
>>120 PB of data stored in HDFS across 6 different clusters and around
>>1800+ active hadoop users consuming data thru Hive, HBase and mapreduce
>>jobs everyday to build applications using this data. With this
>>astronomical growth of data there are also challenges in securing
>>sensitive data and monitoring the access to this sensitive data. Today
>>in large organizations HDFS is the defacto standard for storing big
>>data. Data sets which includes and not limited to consumer sentiment,
>>social media data, customer segmentation, web clicks, sensor data,
>>geo-location and transaction data get stored in Hadoop for day to day
>>business needs.
>> We at eBay want to make sure the sensitive data and data platforms are
>>completely protected from security breaches. So we partnered very
>>closely with our Information Security team to understand the
>>requirements for Eagle to monitor sensitive data access on hadoop:
>> 1.Ability to identify and stop security threats in real time
>> 2.Scale for big data (Support PB scale and Billions of events)
>> 3.Ability to create data access policies
>> 4.Support multiple data sources like HDFS, HBase, Hive
>> 5.Visualize alerts in real time
>> 6.Ability to block malicious access in real time
>> We did not find any data access monitoring solution that available
>>today and can provide the features and functionality that we need to
>>monitor the data access in the hadoop ecosystem at our scale. Hence with
>>an excellent team of world class developers and several users, we have
>>been able to bring Eagle into production as well as open source it.
>> 
>> Rationale
>> In today¹s world; data is an important asset for any company.
>>Businesses are using data extensively to create amazing experiences for
>>users. Data has to be protected and access to data should be secured
>>from security breaches. Today Hadoop is not only used to store logs but
>>also stores financial data, sensitive data sets, geographical data, user
>>click stream data sets etc. which makes it more important to be
>>protected from security breaches. To secure a data platform there are
>>multiple things that need to happen. One is having a strong access
>>control mechanism which today is provided by Apache Ranger and Apache
>>Sentry. These tools provide the ability to provide fine grain access
>>control mechanism to data sets on hadoop. But there is a big gap in
>>terms of monitoring all the data access events and activities in order
>>to securing the hadoop data platform. Together with strong access
>>control, perimeter security and data access monitoring in place data in
>>the hadoop clusters can be secured against breaches. We looked around
>>and found following:
>> Existing data activity monitoring products are designed for traditional
>>databases and data warehouse. Existing monitoring platforms cannot scale
>>out to support fast growing data and petabyte scale. Few products in the
>>industry are still very early in terms of supporting HDFS, Hive, HBase
>>data access monitoring.
>> As mentioned in the background, the business requirement and urgency to
>>secure the data from users with malicious intent drove eBay to invest in
>>building a real time data access monitoring solution from scratch to
>>offer real time alerts and remediation features for malicious data
>>access.
>> With the power of open source distributed systems like Hadoop, Kafka
>>and much more we were able to develop a data activity monitoring system
>>that can scale, identify and stop malicious access in real time.
>> Eagle allows admins to create standard access policies and rules for
>>monitoring HDFS, Hive and HBase data. Eagle also provides out of box
>>machine learning models for modeling user profiles based on user access
>>behaviour and use the model to alert on anomalies.
>> 
>> Current Status
>> 
>> Meritocracy
>> Eagle has been deployed in production at eBay for monitoring billions
>>of events per day from HDFS and Hive operations. From the start; the
>>product has been built with focus on high scalability and application
>>extensibility in mind and Eagle has demonstrated great performance in
>>responding to suspicious events instantly and great flexibility in
>>defining policy.
>> 
>> Community
>> Eagle seeks to develop the developer and user communities during
>>incubation.
>> 
>> Core Developers
>> Eagle is currently being designed and developed by engineers from eBay
>>Inc. ­ Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
>>Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
>>these core developers have deep expertise in developing monitoring
>>products for the Hadoop ecosystem.
>> 
>> Alignment
>> The ASF is a natural host for Eagle given that it is already the home
>>of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
>>projects. Eagle leverages lot of Apache open-source products. Eagle was
>>designed to offer real time insights into sensitive data access by
>>actively monitoring the data access on various data sets in hadoop and
>>an extensible alerting framework with a powerful policy engine. Eagle
>>compliments the existing Hadoop platform area by providing a
>>comprehensive monitoring and alerting solution for detecting sensitive
>>data access threats based on preset policies and machine learning models
>>for user behaviour analysis.
>> 
>> Known Risks
>> 
>> Orphaned Products
>> The core developers of Eagle team work full time on this project. There
>>is no risk of Eagle getting orphaned since eBay is extensively using it
>>in their production Hadoop clusters and have plans to go beyond hadoop.
>>For example, currently there are 7 hadoop clusters and 2 of them are
>>being monitored using Hadoop Eagle in production. We have plans to
>>extend it to all hadoop clusters and eventually other data platforms.
>>There are 10¹s of policies onboarded and actively monitored with plans
>>to onboard more use case. We are very confident that every hadoop
>>cluster in the world will be monitored using Eagle for securing the
>>hadoop ecosystem by actively monitoring for data access on sensitive
>>data. We plan to extend and diversify this community further through
>>Apache. We presented Eagle at the hadoop summit in china and garnered
>>interest from different companies who use hadoop extensively.
>> 
>> Inexperience with Open Source
>> The core developers are all active users and followers of open source.
>>They are already committers and contributors to the Eagle Github
>>project. All have been involved with the source code that has been
>>released under an open source license, and several of them also have
>>experience developing code in an open source environment. Though the
>>core set of Developers do not have Apache Open Source experience, there
>>are plans to onboard individuals with Apache open source experience on
>>to the project. Apache Kylin PMC members are also in the same ebay
>>organization. We work very closely with Apache Ranger committers and are
>>looking forward to find meaningful integrations to improve the security
>>of hadoop platform.
>> 
>> Homogenous Developers
>> The core developers are from eBay. Today the problem of monitoring data
>>activities to find and stop threats is a universal problem faced by all
>>the businesses. Apache Incubation process encourages an open and diverse
>>meritocratic community. Eagle intends to make every possible effort to
>>build a diverse, vibrant and involved community and has already received
>>substantial interest from various organizations.
>> 
>> Reliance on Salaried Developers
>> eBay invested in Eagle as the monitoring solution for Hadoop clusters
>>and some of its key engineers are working full time on the project. In
>>addition, since there is a growing need for securing sensitive data
>>access we need a data activity monitoring solution for Hadoop, we look
>>forward to other Apache developers and researchers to contribute to the
>>project. Additional contributors, including Apache committers have plans
>>to join this effort shortly. Also key to addressing the risk associated
>>with relying on Salaried developers from a single entity is to increase
>>the diversity of the contributors and actively lobby for Domain experts
>>in the security space to contribute. Eagle intends to do this.
>> 
>> Relationships with Other Apache Products
>> Eagle has a strong relationship and dependency with Apache Hadoop,
>>HBase, Spark, Kafka and Storm. Being part of Apache¹s Incubation
>>community, could help with a closer collaboration among these projects
>>and as well as others. An Excessive Fascination with the Apache Brand
>>Eagle is proposing to enter incubation at Apache in order to help
>>efforts to diversify the committer-base, not so much to capitalize on
>>the Apache brand. The Eagle project is in production use already inside
>>eBay, but is not expected to be an eBay product for external customers.
>>As such, the Eagle project is not seeking to use the Apache brand as a
>>marketing tool.
>> 
>> Documentation
>> Information about Eagle can be found at https://github.com/eBay/Eagle.
>>The following link provide more information about Eagle
>>http://goeagle.io<http://goeagle.io/>.
>> 
>> Initial Source
>> Eagle has been under development since 2014 by a team of engineers at
>>eBay Inc. It is currently hosted on Github.com under an Apache license
>>2.0 at https://github.com/eBay/Eagle. Once in incubation we will be
>>moving the code base to apache git library.
>> 
>> External Dependencies
>> Eagle has the following external dependencies.
>> Basic
>> €JDK 1.7+
>> €Scala 2.10.4
>> €Apache Maven
>> €JUnit
>> €Log4j
>> €Slf4j
>> €Apache Commons
>> €Apache Commons Math3
>> €Jackson
>> €Siddhi CEP engine
>> 
>> Hadoop
>> €Apache Hadoop
>> €Apache HBase
>> €Apache Hive
>> €Apache Zookeeper
>> €Apache Curator
>> 
>> Apache Spark
>> €Spark Core Library
>> 
>> REST Service
>> €Jersey
>> 
>> Query
>> €Antlr
>> 
>> Stream processing
>> €Apache Storm
>> €Apache Kafka
>> 
>> Web
>> €AngularJS
>> €jQuery
>> €Bootstrap V3
>> €Moment JS
>> €Admin LTE
>> €html5shiv
>> €respond
>> €Fastclick
>> €Date Range Picker
>> €Flot JS
>> 
>> Cryptography
>> Eagle will eventually support encryption on the wire. This is not one
>>of the initial goals, and we do not expect Eagle to be a controlled
>>export item due to the use of encryption. Eagle supports but does not
>>require the Kerberos authentication mechanism to access secured Hadoop
>>services.
>> 
>> Required Resources
>> 
>> Mailing List
>> €eagle-private for private PMC discussions
>> €eagle-dev for developers
>> €eagle-commits for all commits
>> €eagle-users for all eagle users
>> 
>> Subversion Directory
>> €Git is the preferred source control system.
>> 
>> Issue Tracking
>> €JIRA Eagle (Eagle)
>> 
>> Other Resources
>> The existing code already has unit tests so we will make use of
>>existing Apache continuous testing infrastructure. The resulting load
>>should not be very large.
>> 
>> Initial Committers
>> €Seshu Adunuthula <sadunuthula at ebay dot com>
>> €Arun Manoharan <armanoharan at ebay dot com>
>> €Edward Zhang <yonzhang at ebay dot com>
>> €Hao Chen <hchen9 at ebay dot com>
>> €Chaitali Gupta <cgupta at ebay dot com>
>> €Libin Sun <libsun at ebay dot com>
>> €Jilin Jiang <jiljiang at ebay dot com>
>> €Qingwen Zhao <qingwzhao at ebay dot com>
>> €Hemanth Dendukuri <hdendukuri at ebay dot com>
>> €Senthil Kumar <senthilkumar at ebay dot com>
>> 
>> 
>> Affiliations
>> The initial committers are employees of eBay Inc.
>> 
>> Sponsors
>> 
>> Champion
>> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>> 
>> Nominated Mentors
>> €Owen O¹Malley < omalley at apache dot org > - Apache IPMC member,
>>Hortonworks
>> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>> €Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
>>Hortonworks
>> €Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
>>member
>> €Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
>>Hortonworks
>> 
>> Sponsoring Entity
>> We are requesting the Incubator to sponsor this project.
>> 
>
>
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Re: [VOTE] Accept Eagle into Apache Incubation

[Hitesh Shah <hi...@apache.org>]

+1 (binding)

— Hitesh

On Oct 23, 2015, at 7:11 AM, Manoharan, Arun <ar...@ebay.com> wrote:

> Hello Everyone,
> 
> Thanks for all the feedback on the Eagle Proposal.
> 
> I would like to call for a [VOTE] on Eagle joining the ASF as an incubation project.
> 
> The vote is open for 72 hours:
> 
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
> 
> Eagle is a Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities and take actions in real time. Eagle supports a wide variety of policies on HDFS data and Hive. Eagle also provides machine learning models for detecting anomalous user behavior in Hadoop.
> 
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
> 
> The text of the proposal is also available at the end of this email.
> 
> Thanks for your time and help.
> 
> Thanks,
> Arun
> 
> <COPY of the proposal in text format>
> 
> Eagle
> 
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly identify access to sensitive data, recognize attacks, malicious activities in hadoop and take actions.
> 
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time, enforces policies defined on sensitive data access and alerts or blocks user’s access to that sensitive data in real time. Eagle also creates user profiles based on the typical access behaviour for HDFS and Hive and sends alerts when anomalous behaviour is detected. Eagle can also import sensitive data information classified by external classification engines to help define its policies.
> 
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service and the visualization component. Eagle provides intuitive user interface to administer Eagle and an alert dashboard to respond to real time alerts.
> 
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data source into Eagle policy evaluation framework. For example, Eagle hdfs audit monitoring collects data from Kafka which is populated from namenode log4j appender or from logstash agent. Eagle hive monitoring collects hive query logs from running job through YARN API, which is designed to be scalable and fault-tolerant. Eagle uses HBase as storage for storing metadata and metrics data, and also supports relational database through configuration change.
> 
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an abstraction of Apache Storm. It can also be extended to other streaming engines. This abstraction allows developers to assemble data transformation, filtering, external data join etc. without physically bound to a specific streaming platform. Eagle streaming API allows developers to easily integrate business logic with Eagle policy engine and internally Eagle framework compiles business logic execution DAG into program primitives of underlying stream infrastructure e.g. Apache Storm. For example, Eagle HDFS monitoring transforms audit log from Namenode to object and joins sensitivity metadata, security zone metadata which are generated from external programs or configured by user. Eagle hive monitoring filters running jobs to get hive query string and parses query string into object and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API, scalable policy engine framework, extensible policy engine framework. Stream metadata API allows developers to declare event schema including what attributes constitute an event, what is the type for each attribute, and how to dynamically resolve attribute value in runtime when user configures policy. Scalable policy engine framework allows policies to be executed on different physical nodes in parallel. It is also used to define your own policy partitioner class. Policy engine framework together with streaming partitioning capability provided by all streaming platforms will make sure policies and events can be evaluated in a fully distributed way. Extensible policy engine framework allows developer to plugin a new policy engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user activity patterns or user profiles for Hadoop users based on the user behaviour in the platform. These user profiles are modeled using Machine Learning algorithms and used for detection of anomalous users activities. Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for generating user profile models. The model reads data from HDFS audit logs, preprocesses and aggregates data, and generates models using Spark programming APIs. Once models are generated, Eagle uses stream processing engine for near real-time anomaly detection to determine if any user’s activities are suspicious or not.
> 
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support comprehensive computation for huge set of data on the fly, for e.g. comprehensive filtering, aggregation, histogram, sorting, top, arithmetical expression, pagination etc. HBase is the data storage which Eagle supports as first-class citizen, relational database is supported as well. For HBase storage, Eagle query framework compiles user provided SQL-like query into HBase native filter objects and execute it through HBase coprocessor on the fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user to define policy with just a few clicks. It includes site management UI, policy editor, sensitivity metadata import, HDFS or Hive sensitive resource browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which makes data security one of the top priorities of today’s enterprises. Hadoop is widely used across different verticals as a big data repository to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs. Our data in Hadoop is becoming bigger and bigger as our user base is seeing an exponential growth. Today there are variety of data sets available in Hadoop cluster for our users to consume. eBay has around 120 PB of data stored in HDFS across 6 different clusters and around 1800+ active hadoop users consuming data thru Hive, HBase and mapreduce jobs everyday to build applications using this data. With this astronomical growth of data there are also challenges in securing sensitive data and monitoring the access to this sensitive data. Today in large organizations HDFS is the defacto standard for storing big data. Data sets which includes and not limited to consumer sentiment, social media data, customer segmentation, web clicks, sensor data, geo-location and transaction data get stored in Hadoop for day to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are completely protected from security breaches. So we partnered very closely with our Information Security team to understand the requirements for Eagle to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today and can provide the features and functionality that we need to monitor the data access in the hadoop ecosystem at our scale. Hence with an excellent team of world class developers and several users, we have been able to bring Eagle into production as well as open source it.
> 
> Rationale
> In today’s world; data is an important asset for any company. Businesses are using data extensively to create amazing experiences for users. Data has to be protected and access to data should be secured from security breaches. Today Hadoop is not only used to store logs but also stores financial data, sensitive data sets, geographical data, user click stream data sets etc. which makes it more important to be protected from security breaches. To secure a data platform there are multiple things that need to happen. One is having a strong access control mechanism which today is provided by Apache Ranger and Apache Sentry. These tools provide the ability to provide fine grain access control mechanism to data sets on hadoop. But there is a big gap in terms of monitoring all the data access events and activities in order to securing the hadoop data platform. Together with strong access control, perimeter security and data access monitoring in place data in the hadoop clusters can be secured against breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional databases and data warehouse. Existing monitoring platforms cannot scale out to support fast growing data and petabyte scale. Few products in the industry are still very early in terms of supporting HDFS, Hive, HBase data access monitoring.
> As mentioned in the background, the business requirement and urgency to secure the data from users with malicious intent drove eBay to invest in building a real time data access monitoring solution from scratch to offer real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and much more we were able to develop a data activity monitoring system that can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for monitoring HDFS, Hive and HBase data. Eagle also provides out of box machine learning models for modeling user profiles based on user access behaviour and use the model to alert on anomalies.
> 
> Current Status
> 
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of events per day from HDFS and Hive operations. From the start; the product has been built with focus on high scalability and application extensibility in mind and Eagle has demonstrated great performance in responding to suspicious events instantly and great flexibility in defining policy.
> 
> Community
> Eagle seeks to develop the developer and user communities during incubation.
> 
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang, Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of these core developers have deep expertise in developing monitoring products for the Hadoop ecosystem.
> 
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data projects. Eagle leverages lot of Apache open-source products. Eagle was designed to offer real time insights into sensitive data access by actively monitoring the data access on various data sets in hadoop and an extensible alerting framework with a powerful policy engine. Eagle compliments the existing Hadoop platform area by providing a comprehensive monitoring and alerting solution for detecting sensitive data access threats based on preset policies and machine learning models for user behaviour analysis.
> 
> Known Risks
> 
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is no risk of Eagle getting orphaned since eBay is extensively using it in their production Hadoop clusters and have plans to go beyond hadoop. For example, currently there are 7 hadoop clusters and 2 of them are being monitored using Hadoop Eagle in production. We have plans to extend it to all hadoop clusters and eventually other data platforms. There are 10’s of policies onboarded and actively monitored with plans to onboard more use case. We are very confident that every hadoop cluster in the world will be monitored using Eagle for securing the hadoop ecosystem by actively monitoring for data access on sensitive data. We plan to extend and diversify this community further through Apache. We presented Eagle at the hadoop summit in china and garnered interest from different companies who use hadoop extensively.
> 
> Inexperience with Open Source
> The core developers are all active users and followers of open source. They are already committers and contributors to the Eagle Github project. All have been involved with the source code that has been released under an open source license, and several of them also have experience developing code in an open source environment. Though the core set of Developers do not have Apache Open Source experience, there are plans to onboard individuals with Apache open source experience on to the project. Apache Kylin PMC members are also in the same ebay organization. We work very closely with Apache Ranger committers and are looking forward to find meaningful integrations to improve the security of hadoop platform.
> 
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data activities to find and stop threats is a universal problem faced by all the businesses. Apache Incubation process encourages an open and diverse meritocratic community. Eagle intends to make every possible effort to build a diverse, vibrant and involved community and has already received substantial interest from various organizations.
> 
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and some of its key engineers are working full time on the project. In addition, since there is a growing need for securing sensitive data access we need a data activity monitoring solution for Hadoop, we look forward to other Apache developers and researchers to contribute to the project. Additional contributors, including Apache committers have plans to join this effort shortly. Also key to addressing the risk associated with relying on Salaried developers from a single entity is to increase the diversity of the contributors and actively lobby for Domain experts in the security space to contribute. Eagle intends to do this.
> 
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase, Spark, Kafka and Storm. Being part of Apache’s Incubation community, could help with a closer collaboration among these projects and as well as others. An Excessive Fascination with the Apache Brand Eagle is proposing to enter incubation at Apache in order to help efforts to diversify the committer-base, not so much to capitalize on the Apache brand. The Eagle project is in production use already inside eBay, but is not expected to be an eBay product for external customers. As such, the Eagle project is not seeking to use the Apache brand as a marketing tool.
> 
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle. The following link provide more information about Eagle http://goeagle.io<http://goeagle.io/>.
> 
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay Inc. It is currently hosted on Github.com under an Apache license 2.0 at https://github.com/eBay/Eagle. Once in incubation we will be moving the code base to apache git library.
> 
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
> 
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
> 
> Apache Spark
> •Spark Core Library
> 
> REST Service
> •Jersey
> 
> Query
> •Antlr
> 
> Stream processing
> •Apache Storm
> •Apache Kafka
> 
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
> 
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of the initial goals, and we do not expect Eagle to be a controlled export item due to the use of encryption. Eagle supports but does not require the Kerberos authentication mechanism to access secured Hadoop services.
> 
> Required Resources
> 
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
> 
> Subversion Directory
> •Git is the preferred source control system.
> 
> Issue Tracking
> •JIRA Eagle (Eagle)
> 
> Other Resources
> The existing code already has unit tests so we will make use of existing Apache continuous testing infrastructure. The resulting load should not be very large.
> 
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
> 
> 
> Affiliations
> The initial committers are employees of eBay Inc.
> 
> Sponsors
> 
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> 
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member, Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member, Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
> 
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
> 


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Re: [VOTE] Accept Eagle into Apache Incubation

[Hao Chen <cn...@gmail.com>]

+1 (non-binding)

On Fri, Oct 23, 2015 at 10:11 PM, Manoharan, Arun <ar...@ebay.com>
wrote:

> Hello Everyone,
>
> Thanks for all the feedback on the Eagle Proposal.
>
> I would like to call for a [VOTE] on Eagle joining the ASF as an
> incubation project.
>
> The vote is open for 72 hours:
>
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
>
> Eagle is a Monitoring solution for Hadoop to instantly identify access to
> sensitive data, recognize attacks, malicious activities and take actions in
> real time. Eagle supports a wide variety of policies on HDFS data and Hive.
> Eagle also provides machine learning models for detecting anomalous user
> behavior in Hadoop.
>
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
>
> The text of the proposal is also available at the end of this email.
>
> Thanks for your time and help.
>
> Thanks,
> Arun
>
> <COPY of the proposal in text format>
>
> Eagle
>
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly
> identify access to sensitive data, recognize attacks, malicious activities
> in hadoop and take actions.
>
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time,
> enforces policies defined on sensitive data access and alerts or blocks
> user’s access to that sensitive data in real time. Eagle also creates user
> profiles based on the typical access behaviour for HDFS and Hive and sends
> alerts when anomalous behaviour is detected. Eagle can also import
> sensitive data information classified by external classification engines to
> help define its policies.
>
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop
> logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create
> policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service
> and the visualization component. Eagle provides intuitive user interface to
> administer Eagle and an alert dashboard to respond to real time alerts.
>
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data
> source into Eagle policy evaluation framework. For example, Eagle hdfs
> audit monitoring collects data from Kafka which is populated from namenode
> log4j appender or from logstash agent. Eagle hive monitoring collects hive
> query logs from running job through YARN API, which is designed to be
> scalable and fault-tolerant. Eagle uses HBase as storage for storing
> metadata and metrics data, and also supports relational database through
> configuration change.
>
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an
> abstraction of Apache Storm. It can also be extended to other streaming
> engines. This abstraction allows developers to assemble data
> transformation, filtering, external data join etc. without physically bound
> to a specific streaming platform. Eagle streaming API allows developers to
> easily integrate business logic with Eagle policy engine and internally
> Eagle framework compiles business logic execution DAG into program
> primitives of underlying stream infrastructure e.g. Apache Storm. For
> example, Eagle HDFS monitoring transforms audit log from Namenode to object
> and joins sensitivity metadata, security zone metadata which are generated
> from external programs or configured by user. Eagle hive monitoring filters
> running jobs to get hive query string and parses query string into object
> and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API,
> scalable policy engine framework, extensible policy engine framework.
> Stream metadata API allows developers to declare event schema including
> what attributes constitute an event, what is the type for each attribute,
> and how to dynamically resolve attribute value in runtime when user
> configures policy. Scalable policy engine framework allows policies to be
> executed on different physical nodes in parallel. It is also used to define
> your own policy partitioner class. Policy engine framework together with
> streaming partitioning capability provided by all streaming platforms will
> make sure policies and events can be evaluated in a fully distributed way.
> Extensible policy engine framework allows developer to plugin a new policy
> engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user
> activity patterns or user profiles for Hadoop users based on the user
> behaviour in the platform. These user profiles are modeled using Machine
> Learning algorithms and used for detection of anomalous users activities.
> Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for
> generating user profile models. The model reads data from HDFS audit logs,
> preprocesses and aggregates data, and generates models using Spark
> programming APIs. Once models are generated, Eagle uses stream processing
> engine for near real-time anomaly detection to determine if any user’s
> activities are suspicious or not.
>
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support
> comprehensive computation for huge set of data on the fly, for e.g.
> comprehensive filtering, aggregation, histogram, sorting, top, arithmetical
> expression, pagination etc. HBase is the data storage which Eagle supports
> as first-class citizen, relational database is supported as well. For HBase
> storage, Eagle query framework compiles user provided SQL-like query into
> HBase native filter objects and execute it through HBase coprocessor on the
> fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user
> to define policy with just a few clicks. It includes site management UI,
> policy editor, sensitivity metadata import, HDFS or Hive sensitive resource
> browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which
> makes data security one of the top priorities of today’s enterprises.
> Hadoop is widely used across different verticals as a big data repository
> to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs.
> Our data in Hadoop is becoming bigger and bigger as our user base is seeing
> an exponential growth. Today there are variety of data sets available in
> Hadoop cluster for our users to consume. eBay has around 120 PB of data
> stored in HDFS across 6 different clusters and around 1800+ active hadoop
> users consuming data thru Hive, HBase and mapreduce jobs everyday to build
> applications using this data. With this astronomical growth of data there
> are also challenges in securing sensitive data and monitoring the access to
> this sensitive data. Today in large organizations HDFS is the defacto
> standard for storing big data. Data sets which includes and not limited to
> consumer sentiment, social media data, customer segmentation, web clicks,
> sensor data, geo-location and transaction data get stored in Hadoop for day
> to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are
> completely protected from security breaches. So we partnered very closely
> with our Information Security team to understand the requirements for Eagle
> to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today
> and can provide the features and functionality that we need to monitor the
> data access in the hadoop ecosystem at our scale. Hence with an excellent
> team of world class developers and several users, we have been able to
> bring Eagle into production as well as open source it.
>
> Rationale
> In today’s world; data is an important asset for any company. Businesses
> are using data extensively to create amazing experiences for users. Data
> has to be protected and access to data should be secured from security
> breaches. Today Hadoop is not only used to store logs but also stores
> financial data, sensitive data sets, geographical data, user click stream
> data sets etc. which makes it more important to be protected from security
> breaches. To secure a data platform there are multiple things that need to
> happen. One is having a strong access control mechanism which today is
> provided by Apache Ranger and Apache Sentry. These tools provide the
> ability to provide fine grain access control mechanism to data sets on
> hadoop. But there is a big gap in terms of monitoring all the data access
> events and activities in order to securing the hadoop data platform.
> Together with strong access control, perimeter security and data access
> monitoring in place data in the hadoop clusters can be secured against
> breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional
> databases and data warehouse. Existing monitoring platforms cannot scale
> out to support fast growing data and petabyte scale. Few products in the
> industry are still very early in terms of supporting HDFS, Hive, HBase data
> access monitoring.
> As mentioned in the background, the business requirement and urgency to
> secure the data from users with malicious intent drove eBay to invest in
> building a real time data access monitoring solution from scratch to offer
> real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and
> much more we were able to develop a data activity monitoring system that
> can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for
> monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> machine learning models for modeling user profiles based on user access
> behaviour and use the model to alert on anomalies.
>
> Current Status
>
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of
> events per day from HDFS and Hive operations. From the start; the product
> has been built with focus on high scalability and application extensibility
> in mind and Eagle has demonstrated great performance in responding to
> suspicious events instantly and great flexibility in defining policy.
>
> Community
> Eagle seeks to develop the developer and user communities during
> incubation.
>
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay
> Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> these core developers have deep expertise in developing monitoring products
> for the Hadoop ecosystem.
>
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of
> Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> projects. Eagle leverages lot of Apache open-source products. Eagle was
> designed to offer real time insights into sensitive data access by actively
> monitoring the data access on various data sets in hadoop and an extensible
> alerting framework with a powerful policy engine. Eagle compliments the
> existing Hadoop platform area by providing a comprehensive monitoring and
> alerting solution for detecting sensitive data access threats based on
> preset policies and machine learning models for user behaviour analysis.
>
> Known Risks
>
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is
> no risk of Eagle getting orphaned since eBay is extensively using it in
> their production Hadoop clusters and have plans to go beyond hadoop. For
> example, currently there are 7 hadoop clusters and 2 of them are being
> monitored using Hadoop Eagle in production. We have plans to extend it to
> all hadoop clusters and eventually other data platforms. There are 10’s of
> policies onboarded and actively monitored with plans to onboard more use
> case. We are very confident that every hadoop cluster in the world will be
> monitored using Eagle for securing the hadoop ecosystem by actively
> monitoring for data access on sensitive data. We plan to extend and
> diversify this community further through Apache. We presented Eagle at the
> hadoop summit in china and garnered interest from different companies who
> use hadoop extensively.
>
> Inexperience with Open Source
> The core developers are all active users and followers of open source.
> They are already committers and contributors to the Eagle Github project.
> All have been involved with the source code that has been released under an
> open source license, and several of them also have experience developing
> code in an open source environment. Though the core set of Developers do
> not have Apache Open Source experience, there are plans to onboard
> individuals with Apache open source experience on to the project. Apache
> Kylin PMC members are also in the same ebay organization. We work very
> closely with Apache Ranger committers and are looking forward to find
> meaningful integrations to improve the security of hadoop platform.
>
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data
> activities to find and stop threats is a universal problem faced by all the
> businesses. Apache Incubation process encourages an open and diverse
> meritocratic community. Eagle intends to make every possible effort to
> build a diverse, vibrant and involved community and has already received
> substantial interest from various organizations.
>
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and
> some of its key engineers are working full time on the project. In
> addition, since there is a growing need for securing sensitive data access
> we need a data activity monitoring solution for Hadoop, we look forward to
> other Apache developers and researchers to contribute to the project.
> Additional contributors, including Apache committers have plans to join
> this effort shortly. Also key to addressing the risk associated with
> relying on Salaried developers from a single entity is to increase the
> diversity of the contributors and actively lobby for Domain experts in the
> security space to contribute. Eagle intends to do this.
>
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase,
> Spark, Kafka and Storm. Being part of Apache’s Incubation community, could
> help with a closer collaboration among these projects and as well as
> others. An Excessive Fascination with the Apache Brand Eagle is proposing
> to enter incubation at Apache in order to help efforts to diversify the
> committer-base, not so much to capitalize on the Apache brand. The Eagle
> project is in production use already inside eBay, but is not expected to be
> an eBay product for external customers. As such, the Eagle project is not
> seeking to use the Apache brand as a marketing tool.
>
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle.
> The following link provide more information about Eagle http://goeagle.io<
> http://goeagle.io/>.
>
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay
> Inc. It is currently hosted on Github.com under an Apache license 2.0 at
> https://github.com/eBay/Eagle. Once in incubation we will be moving the
> code base to apache git library.
>
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
>
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
>
> Apache Spark
> •Spark Core Library
>
> REST Service
> •Jersey
>
> Query
> •Antlr
>
> Stream processing
> •Apache Storm
> •Apache Kafka
>
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
>
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of
> the initial goals, and we do not expect Eagle to be a controlled export
> item due to the use of encryption. Eagle supports but does not require the
> Kerberos authentication mechanism to access secured Hadoop services.
>
> Required Resources
>
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
>
> Subversion Directory
> •Git is the preferred source control system.
>
> Issue Tracking
> •JIRA Eagle (Eagle)
>
> Other Resources
> The existing code already has unit tests so we will make use of existing
> Apache continuous testing infrastructure. The resulting load should not be
> very large.
>
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
>
>
> Affiliations
> The initial committers are employees of eBay Inc.
>
> Sponsors
>
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
>
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
>
>

Re: [VOTE] Accept Eagle into Apache Incubation

[Chris Nauroth <cn...@hortonworks.com>]

+1 (binding)

--Chris Nauroth




On 10/23/15, 7:11 AM, "Manoharan, Arun" <ar...@ebay.com> wrote:

>Hello Everyone,
>
>Thanks for all the feedback on the Eagle Proposal.
>
>I would like to call for a [VOTE] on Eagle joining the ASF as an
>incubation project.
>
>The vote is open for 72 hours:
>
>[ ] +1 accept Eagle in the Incubator
>[ ] ±0
>[ ] -1 (please give reason)
>
>Eagle is a Monitoring solution for Hadoop to instantly identify access to
>sensitive data, recognize attacks, malicious activities and take actions
>in real time. Eagle supports a wide variety of policies on HDFS data and
>Hive. Eagle also provides machine learning models for detecting anomalous
>user behavior in Hadoop.
>
>The proposal is available on the wiki here:
>https://wiki.apache.org/incubator/EagleProposal
>
>The text of the proposal is also available at the end of this email.
>
>Thanks for your time and help.
>
>Thanks,
>Arun
>
><COPY of the proposal in text format>
>
>Eagle
>
>Abstract
>Eagle is an Open Source Monitoring solution for Hadoop to instantly
>identify access to sensitive data, recognize attacks, malicious
>activities in hadoop and take actions.
>
>Proposal
>Eagle audits access to HDFS files, Hive and HBase tables in real time,
>enforces policies defined on sensitive data access and alerts or blocks
>user¹s access to that sensitive data in real time. Eagle also creates
>user profiles based on the typical access behaviour for HDFS and Hive and
>sends alerts when anomalous behaviour is detected. Eagle can also import
>sensitive data information classified by external classification engines
>to help define its policies.
>
>Overview of Eagle
>Eagle has 3 main parts.
>1.Data collection and storage - Eagle collects data from various hadoop
>logs in real time using Kafka/Yarn API and uses HDFS and HBase for
>storage.
>2.Data processing and policy engine - Eagle allows users to create
>policies based on various metadata properties on HDFS, Hive and HBase
>data.
>3.Eagle services - Eagle services include policy manager, query service
>and the visualization component. Eagle provides intuitive user interface
>to administer Eagle and an alert dashboard to respond to real time alerts.
>
>Data Collection and Storage:
>Eagle provides programming API for extending Eagle to integrate any data
>source into Eagle policy evaluation framework. For example, Eagle hdfs
>audit monitoring collects data from Kafka which is populated from
>namenode log4j appender or from logstash agent. Eagle hive monitoring
>collects hive query logs from running job through YARN API, which is
>designed to be scalable and fault-tolerant. Eagle uses HBase as storage
>for storing metadata and metrics data, and also supports relational
>database through configuration change.
>
>Data Processing and Policy Engine:
>Processing Engine: Eagle provides stream processing API which is an
>abstraction of Apache Storm. It can also be extended to other streaming
>engines. This abstraction allows developers to assemble data
>transformation, filtering, external data join etc. without physically
>bound to a specific streaming platform. Eagle streaming API allows
>developers to easily integrate business logic with Eagle policy engine
>and internally Eagle framework compiles business logic execution DAG into
>program primitives of underlying stream infrastructure e.g. Apache Storm.
>For example, Eagle HDFS monitoring transforms audit log from Namenode to
>object and joins sensitivity metadata, security zone metadata which are
>generated from external programs or configured by user. Eagle hive
>monitoring filters running jobs to get hive query string and parses query
>string into object and then joins sensitivity metadata.
>Alerting Framework: Eagle Alert Framework includes stream metadata API,
>scalable policy engine framework, extensible policy engine framework.
>Stream metadata API allows developers to declare event schema including
>what attributes constitute an event, what is the type for each attribute,
>and how to dynamically resolve attribute value in runtime when user
>configures policy. Scalable policy engine framework allows policies to be
>executed on different physical nodes in parallel. It is also used to
>define your own policy partitioner class. Policy engine framework
>together with streaming partitioning capability provided by all streaming
>platforms will make sure policies and events can be evaluated in a fully
>distributed way. Extensible policy engine framework allows developer to
>plugin a new policy engine with a few lines of codes. WSO2 Siddhi CEP
>engine is the policy engine which Eagle supports as first-class citizen.
>Machine Learning module: Eagle provides capabilities to define user
>activity patterns or user profiles for Hadoop users based on the user
>behaviour in the platform. These user profiles are modeled using Machine
>Learning algorithms and used for detection of anomalous users activities.
>Eagle uses Eigen Value Decomposition, and Density Estimation algorithms
>for generating user profile models. The model reads data from HDFS audit
>logs, preprocesses and aggregates data, and generates models using Spark
>programming APIs. Once models are generated, Eagle uses stream processing
>engine for near real-time anomaly detection to determine if any user¹s
>activities are suspicious or not.
>
>Eagle Services:
>Query Service: Eagle provides SQL-like service API to support
>comprehensive computation for huge set of data on the fly, for e.g.
>comprehensive filtering, aggregation, histogram, sorting, top,
>arithmetical expression, pagination etc. HBase is the data storage which
>Eagle supports as first-class citizen, relational database is supported
>as well. For HBase storage, Eagle query framework compiles user provided
>SQL-like query into HBase native filter objects and execute it through
>HBase coprocessor on the fly.
>Policy Manager: Eagle policy manager provides UI and Restful API for user
>to define policy with just a few clicks. It includes site management UI,
>policy editor, sensitivity metadata import, HDFS or Hive sensitive
>resource browsing, alert dashboards etc.
>Background
>Data is one of the most important assets for today¹s businesses, which
>makes data security one of the top priorities of today¹s enterprises.
>Hadoop is widely used across different verticals as a big data repository
>to store this data in most modern enterprises.
>At eBay we use hadoop platform extensively for our data processing needs.
>Our data in Hadoop is becoming bigger and bigger as our user base is
>seeing an exponential growth. Today there are variety of data sets
>available in Hadoop cluster for our users to consume. eBay has around 120
>PB of data stored in HDFS across 6 different clusters and around 1800+
>active hadoop users consuming data thru Hive, HBase and mapreduce jobs
>everyday to build applications using this data. With this astronomical
>growth of data there are also challenges in securing sensitive data and
>monitoring the access to this sensitive data. Today in large
>organizations HDFS is the defacto standard for storing big data. Data
>sets which includes and not limited to consumer sentiment, social media
>data, customer segmentation, web clicks, sensor data, geo-location and
>transaction data get stored in Hadoop for day to day business needs.
>We at eBay want to make sure the sensitive data and data platforms are
>completely protected from security breaches. So we partnered very closely
>with our Information Security team to understand the requirements for
>Eagle to monitor sensitive data access on hadoop:
>1.Ability to identify and stop security threats in real time
>2.Scale for big data (Support PB scale and Billions of events)
>3.Ability to create data access policies
>4.Support multiple data sources like HDFS, HBase, Hive
>5.Visualize alerts in real time
>6.Ability to block malicious access in real time
>We did not find any data access monitoring solution that available today
>and can provide the features and functionality that we need to monitor
>the data access in the hadoop ecosystem at our scale. Hence with an
>excellent team of world class developers and several users, we have been
>able to bring Eagle into production as well as open source it.
>
>Rationale
>In today¹s world; data is an important asset for any company. Businesses
>are using data extensively to create amazing experiences for users. Data
>has to be protected and access to data should be secured from security
>breaches. Today Hadoop is not only used to store logs but also stores
>financial data, sensitive data sets, geographical data, user click stream
>data sets etc. which makes it more important to be protected from
>security breaches. To secure a data platform there are multiple things
>that need to happen. One is having a strong access control mechanism
>which today is provided by Apache Ranger and Apache Sentry. These tools
>provide the ability to provide fine grain access control mechanism to
>data sets on hadoop. But there is a big gap in terms of monitoring all
>the data access events and activities in order to securing the hadoop
>data platform. Together with strong access control, perimeter security
>and data access monitoring in place data in the hadoop clusters can be
>secured against breaches. We looked around and found following:
>Existing data activity monitoring products are designed for traditional
>databases and data warehouse. Existing monitoring platforms cannot scale
>out to support fast growing data and petabyte scale. Few products in the
>industry are still very early in terms of supporting HDFS, Hive, HBase
>data access monitoring.
>As mentioned in the background, the business requirement and urgency to
>secure the data from users with malicious intent drove eBay to invest in
>building a real time data access monitoring solution from scratch to
>offer real time alerts and remediation features for malicious data access.
>With the power of open source distributed systems like Hadoop, Kafka and
>much more we were able to develop a data activity monitoring system that
>can scale, identify and stop malicious access in real time.
>Eagle allows admins to create standard access policies and rules for
>monitoring HDFS, Hive and HBase data. Eagle also provides out of box
>machine learning models for modeling user profiles based on user access
>behaviour and use the model to alert on anomalies.
>
>Current Status
>
>Meritocracy
>Eagle has been deployed in production at eBay for monitoring billions of
>events per day from HDFS and Hive operations. From the start; the product
>has been built with focus on high scalability and application
>extensibility in mind and Eagle has demonstrated great performance in
>responding to suspicious events instantly and great flexibility in
>defining policy.
>
>Community
>Eagle seeks to develop the developer and user communities during
>incubation.
>
>Core Developers
>Eagle is currently being designed and developed by engineers from eBay
>Inc. ­ Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
>Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
>these core developers have deep expertise in developing monitoring
>products for the Hadoop ecosystem.
>
>Alignment
>The ASF is a natural host for Eagle given that it is already the home of
>Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
>projects. Eagle leverages lot of Apache open-source products. Eagle was
>designed to offer real time insights into sensitive data access by
>actively monitoring the data access on various data sets in hadoop and an
>extensible alerting framework with a powerful policy engine. Eagle
>compliments the existing Hadoop platform area by providing a
>comprehensive monitoring and alerting solution for detecting sensitive
>data access threats based on preset policies and machine learning models
>for user behaviour analysis.
>
>Known Risks
>
>Orphaned Products
>The core developers of Eagle team work full time on this project. There
>is no risk of Eagle getting orphaned since eBay is extensively using it
>in their production Hadoop clusters and have plans to go beyond hadoop.
>For example, currently there are 7 hadoop clusters and 2 of them are
>being monitored using Hadoop Eagle in production. We have plans to extend
>it to all hadoop clusters and eventually other data platforms. There are
>10¹s of policies onboarded and actively monitored with plans to onboard
>more use case. We are very confident that every hadoop cluster in the
>world will be monitored using Eagle for securing the hadoop ecosystem by
>actively monitoring for data access on sensitive data. We plan to extend
>and diversify this community further through Apache. We presented Eagle
>at the hadoop summit in china and garnered interest from different
>companies who use hadoop extensively.
>
>Inexperience with Open Source
>The core developers are all active users and followers of open source.
>They are already committers and contributors to the Eagle Github project.
>All have been involved with the source code that has been released under
>an open source license, and several of them also have experience
>developing code in an open source environment. Though the core set of
>Developers do not have Apache Open Source experience, there are plans to
>onboard individuals with Apache open source experience on to the project.
>Apache Kylin PMC members are also in the same ebay organization. We work
>very closely with Apache Ranger committers and are looking forward to
>find meaningful integrations to improve the security of hadoop platform.
>
>Homogenous Developers
>The core developers are from eBay. Today the problem of monitoring data
>activities to find and stop threats is a universal problem faced by all
>the businesses. Apache Incubation process encourages an open and diverse
>meritocratic community. Eagle intends to make every possible effort to
>build a diverse, vibrant and involved community and has already received
>substantial interest from various organizations.
>
>Reliance on Salaried Developers
>eBay invested in Eagle as the monitoring solution for Hadoop clusters and
>some of its key engineers are working full time on the project. In
>addition, since there is a growing need for securing sensitive data
>access we need a data activity monitoring solution for Hadoop, we look
>forward to other Apache developers and researchers to contribute to the
>project. Additional contributors, including Apache committers have plans
>to join this effort shortly. Also key to addressing the risk associated
>with relying on Salaried developers from a single entity is to increase
>the diversity of the contributors and actively lobby for Domain experts
>in the security space to contribute. Eagle intends to do this.
>
>Relationships with Other Apache Products
>Eagle has a strong relationship and dependency with Apache Hadoop, HBase,
>Spark, Kafka and Storm. Being part of Apache¹s Incubation community,
>could help with a closer collaboration among these projects and as well
>as others. An Excessive Fascination with the Apache Brand Eagle is
>proposing to enter incubation at Apache in order to help efforts to
>diversify the committer-base, not so much to capitalize on the Apache
>brand. The Eagle project is in production use already inside eBay, but is
>not expected to be an eBay product for external customers. As such, the
>Eagle project is not seeking to use the Apache brand as a marketing tool.
>
>Documentation
>Information about Eagle can be found at https://github.com/eBay/Eagle.
>The following link provide more information about Eagle
>http://goeagle.io<http://goeagle.io/>.
>
>Initial Source
>Eagle has been under development since 2014 by a team of engineers at
>eBay Inc. It is currently hosted on Github.com under an Apache license
>2.0 at https://github.com/eBay/Eagle. Once in incubation we will be
>moving the code base to apache git library.
>
>External Dependencies
>Eagle has the following external dependencies.
>Basic
>€JDK 1.7+
>€Scala 2.10.4
>€Apache Maven
>€JUnit
>€Log4j
>€Slf4j
>€Apache Commons
>€Apache Commons Math3
>€Jackson
>€Siddhi CEP engine
>
>Hadoop
>€Apache Hadoop
>€Apache HBase
>€Apache Hive
>€Apache Zookeeper
>€Apache Curator
>
>Apache Spark
>€Spark Core Library
>
>REST Service
>€Jersey
>
>Query
>€Antlr
>
>Stream processing
>€Apache Storm
>€Apache Kafka
>
>Web
>€AngularJS
>€jQuery
>€Bootstrap V3
>€Moment JS
>€Admin LTE
>€html5shiv
>€respond
>€Fastclick
>€Date Range Picker
>€Flot JS
>
>Cryptography
>Eagle will eventually support encryption on the wire. This is not one of
>the initial goals, and we do not expect Eagle to be a controlled export
>item due to the use of encryption. Eagle supports but does not require
>the Kerberos authentication mechanism to access secured Hadoop services.
>
>Required Resources
>
>Mailing List
>€eagle-private for private PMC discussions
>€eagle-dev for developers
>€eagle-commits for all commits
>€eagle-users for all eagle users
>
>Subversion Directory
>€Git is the preferred source control system.
>
>Issue Tracking
>€JIRA Eagle (Eagle)
>
>Other Resources
>The existing code already has unit tests so we will make use of existing
>Apache continuous testing infrastructure. The resulting load should not
>be very large.
>
>Initial Committers
>€Seshu Adunuthula <sadunuthula at ebay dot com>
>€Arun Manoharan <armanoharan at ebay dot com>
>€Edward Zhang <yonzhang at ebay dot com>
>€Hao Chen <hchen9 at ebay dot com>
>€Chaitali Gupta <cgupta at ebay dot com>
>€Libin Sun <libsun at ebay dot com>
>€Jilin Jiang <jiljiang at ebay dot com>
>€Qingwen Zhao <qingwzhao at ebay dot com>
>€Hemanth Dendukuri <hdendukuri at ebay dot com>
>€Senthil Kumar <senthilkumar at ebay dot com>
>
>
>Affiliations
>The initial committers are employees of eBay Inc.
>
>Sponsors
>
>Champion
>€Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>
>Nominated Mentors
>€Owen O¹Malley < omalley at apache dot org > - Apache IPMC member,
>Hortonworks
>€Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>€Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
>Hortonworks
>€Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
>member
>€Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
>Hortonworks
>
>Sponsoring Entity
>We are requesting the Incubator to sponsor this project.
>


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Re: [VOTE] Accept Eagle into Apache Incubation

[larry mccay <la...@gmail.com>]

+1 (non-binding)

On Fri, Oct 23, 2015 at 7:11 AM, Manoharan, Arun <ar...@ebay.com>
wrote:

> Hello Everyone,
>
> Thanks for all the feedback on the Eagle Proposal.
>
> I would like to call for a [VOTE] on Eagle joining the ASF as an
> incubation project.
>
> The vote is open for 72 hours:
>
> [ ] +1 accept Eagle in the Incubator
> [ ] ±0
> [ ] -1 (please give reason)
>
> Eagle is a Monitoring solution for Hadoop to instantly identify access to
> sensitive data, recognize attacks, malicious activities and take actions in
> real time. Eagle supports a wide variety of policies on HDFS data and Hive.
> Eagle also provides machine learning models for detecting anomalous user
> behavior in Hadoop.
>
> The proposal is available on the wiki here:
> https://wiki.apache.org/incubator/EagleProposal
>
> The text of the proposal is also available at the end of this email.
>
> Thanks for your time and help.
>
> Thanks,
> Arun
>
> <COPY of the proposal in text format>
>
> Eagle
>
> Abstract
> Eagle is an Open Source Monitoring solution for Hadoop to instantly
> identify access to sensitive data, recognize attacks, malicious activities
> in hadoop and take actions.
>
> Proposal
> Eagle audits access to HDFS files, Hive and HBase tables in real time,
> enforces policies defined on sensitive data access and alerts or blocks
> user’s access to that sensitive data in real time. Eagle also creates user
> profiles based on the typical access behaviour for HDFS and Hive and sends
> alerts when anomalous behaviour is detected. Eagle can also import
> sensitive data information classified by external classification engines to
> help define its policies.
>
> Overview of Eagle
> Eagle has 3 main parts.
> 1.Data collection and storage - Eagle collects data from various hadoop
> logs in real time using Kafka/Yarn API and uses HDFS and HBase for storage.
> 2.Data processing and policy engine - Eagle allows users to create
> policies based on various metadata properties on HDFS, Hive and HBase data.
> 3.Eagle services - Eagle services include policy manager, query service
> and the visualization component. Eagle provides intuitive user interface to
> administer Eagle and an alert dashboard to respond to real time alerts.
>
> Data Collection and Storage:
> Eagle provides programming API for extending Eagle to integrate any data
> source into Eagle policy evaluation framework. For example, Eagle hdfs
> audit monitoring collects data from Kafka which is populated from namenode
> log4j appender or from logstash agent. Eagle hive monitoring collects hive
> query logs from running job through YARN API, which is designed to be
> scalable and fault-tolerant. Eagle uses HBase as storage for storing
> metadata and metrics data, and also supports relational database through
> configuration change.
>
> Data Processing and Policy Engine:
> Processing Engine: Eagle provides stream processing API which is an
> abstraction of Apache Storm. It can also be extended to other streaming
> engines. This abstraction allows developers to assemble data
> transformation, filtering, external data join etc. without physically bound
> to a specific streaming platform. Eagle streaming API allows developers to
> easily integrate business logic with Eagle policy engine and internally
> Eagle framework compiles business logic execution DAG into program
> primitives of underlying stream infrastructure e.g. Apache Storm. For
> example, Eagle HDFS monitoring transforms audit log from Namenode to object
> and joins sensitivity metadata, security zone metadata which are generated
> from external programs or configured by user. Eagle hive monitoring filters
> running jobs to get hive query string and parses query string into object
> and then joins sensitivity metadata.
> Alerting Framework: Eagle Alert Framework includes stream metadata API,
> scalable policy engine framework, extensible policy engine framework.
> Stream metadata API allows developers to declare event schema including
> what attributes constitute an event, what is the type for each attribute,
> and how to dynamically resolve attribute value in runtime when user
> configures policy. Scalable policy engine framework allows policies to be
> executed on different physical nodes in parallel. It is also used to define
> your own policy partitioner class. Policy engine framework together with
> streaming partitioning capability provided by all streaming platforms will
> make sure policies and events can be evaluated in a fully distributed way.
> Extensible policy engine framework allows developer to plugin a new policy
> engine with a few lines of codes. WSO2 Siddhi CEP engine is the policy
> engine which Eagle supports as first-class citizen.
> Machine Learning module: Eagle provides capabilities to define user
> activity patterns or user profiles for Hadoop users based on the user
> behaviour in the platform. These user profiles are modeled using Machine
> Learning algorithms and used for detection of anomalous users activities.
> Eagle uses Eigen Value Decomposition, and Density Estimation algorithms for
> generating user profile models. The model reads data from HDFS audit logs,
> preprocesses and aggregates data, and generates models using Spark
> programming APIs. Once models are generated, Eagle uses stream processing
> engine for near real-time anomaly detection to determine if any user’s
> activities are suspicious or not.
>
> Eagle Services:
> Query Service: Eagle provides SQL-like service API to support
> comprehensive computation for huge set of data on the fly, for e.g.
> comprehensive filtering, aggregation, histogram, sorting, top, arithmetical
> expression, pagination etc. HBase is the data storage which Eagle supports
> as first-class citizen, relational database is supported as well. For HBase
> storage, Eagle query framework compiles user provided SQL-like query into
> HBase native filter objects and execute it through HBase coprocessor on the
> fly.
> Policy Manager: Eagle policy manager provides UI and Restful API for user
> to define policy with just a few clicks. It includes site management UI,
> policy editor, sensitivity metadata import, HDFS or Hive sensitive resource
> browsing, alert dashboards etc.
> Background
> Data is one of the most important assets for today’s businesses, which
> makes data security one of the top priorities of today’s enterprises.
> Hadoop is widely used across different verticals as a big data repository
> to store this data in most modern enterprises.
> At eBay we use hadoop platform extensively for our data processing needs.
> Our data in Hadoop is becoming bigger and bigger as our user base is seeing
> an exponential growth. Today there are variety of data sets available in
> Hadoop cluster for our users to consume. eBay has around 120 PB of data
> stored in HDFS across 6 different clusters and around 1800+ active hadoop
> users consuming data thru Hive, HBase and mapreduce jobs everyday to build
> applications using this data. With this astronomical growth of data there
> are also challenges in securing sensitive data and monitoring the access to
> this sensitive data. Today in large organizations HDFS is the defacto
> standard for storing big data. Data sets which includes and not limited to
> consumer sentiment, social media data, customer segmentation, web clicks,
> sensor data, geo-location and transaction data get stored in Hadoop for day
> to day business needs.
> We at eBay want to make sure the sensitive data and data platforms are
> completely protected from security breaches. So we partnered very closely
> with our Information Security team to understand the requirements for Eagle
> to monitor sensitive data access on hadoop:
> 1.Ability to identify and stop security threats in real time
> 2.Scale for big data (Support PB scale and Billions of events)
> 3.Ability to create data access policies
> 4.Support multiple data sources like HDFS, HBase, Hive
> 5.Visualize alerts in real time
> 6.Ability to block malicious access in real time
> We did not find any data access monitoring solution that available today
> and can provide the features and functionality that we need to monitor the
> data access in the hadoop ecosystem at our scale. Hence with an excellent
> team of world class developers and several users, we have been able to
> bring Eagle into production as well as open source it.
>
> Rationale
> In today’s world; data is an important asset for any company. Businesses
> are using data extensively to create amazing experiences for users. Data
> has to be protected and access to data should be secured from security
> breaches. Today Hadoop is not only used to store logs but also stores
> financial data, sensitive data sets, geographical data, user click stream
> data sets etc. which makes it more important to be protected from security
> breaches. To secure a data platform there are multiple things that need to
> happen. One is having a strong access control mechanism which today is
> provided by Apache Ranger and Apache Sentry. These tools provide the
> ability to provide fine grain access control mechanism to data sets on
> hadoop. But there is a big gap in terms of monitoring all the data access
> events and activities in order to securing the hadoop data platform.
> Together with strong access control, perimeter security and data access
> monitoring in place data in the hadoop clusters can be secured against
> breaches. We looked around and found following:
> Existing data activity monitoring products are designed for traditional
> databases and data warehouse. Existing monitoring platforms cannot scale
> out to support fast growing data and petabyte scale. Few products in the
> industry are still very early in terms of supporting HDFS, Hive, HBase data
> access monitoring.
> As mentioned in the background, the business requirement and urgency to
> secure the data from users with malicious intent drove eBay to invest in
> building a real time data access monitoring solution from scratch to offer
> real time alerts and remediation features for malicious data access.
> With the power of open source distributed systems like Hadoop, Kafka and
> much more we were able to develop a data activity monitoring system that
> can scale, identify and stop malicious access in real time.
> Eagle allows admins to create standard access policies and rules for
> monitoring HDFS, Hive and HBase data. Eagle also provides out of box
> machine learning models for modeling user profiles based on user access
> behaviour and use the model to alert on anomalies.
>
> Current Status
>
> Meritocracy
> Eagle has been deployed in production at eBay for monitoring billions of
> events per day from HDFS and Hive operations. From the start; the product
> has been built with focus on high scalability and application extensibility
> in mind and Eagle has demonstrated great performance in responding to
> suspicious events instantly and great flexibility in defining policy.
>
> Community
> Eagle seeks to develop the developer and user communities during
> incubation.
>
> Core Developers
> Eagle is currently being designed and developed by engineers from eBay
> Inc. – Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
> Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
> these core developers have deep expertise in developing monitoring products
> for the Hadoop ecosystem.
>
> Alignment
> The ASF is a natural host for Eagle given that it is already the home of
> Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
> projects. Eagle leverages lot of Apache open-source products. Eagle was
> designed to offer real time insights into sensitive data access by actively
> monitoring the data access on various data sets in hadoop and an extensible
> alerting framework with a powerful policy engine. Eagle compliments the
> existing Hadoop platform area by providing a comprehensive monitoring and
> alerting solution for detecting sensitive data access threats based on
> preset policies and machine learning models for user behaviour analysis.
>
> Known Risks
>
> Orphaned Products
> The core developers of Eagle team work full time on this project. There is
> no risk of Eagle getting orphaned since eBay is extensively using it in
> their production Hadoop clusters and have plans to go beyond hadoop. For
> example, currently there are 7 hadoop clusters and 2 of them are being
> monitored using Hadoop Eagle in production. We have plans to extend it to
> all hadoop clusters and eventually other data platforms. There are 10’s of
> policies onboarded and actively monitored with plans to onboard more use
> case. We are very confident that every hadoop cluster in the world will be
> monitored using Eagle for securing the hadoop ecosystem by actively
> monitoring for data access on sensitive data. We plan to extend and
> diversify this community further through Apache. We presented Eagle at the
> hadoop summit in china and garnered interest from different companies who
> use hadoop extensively.
>
> Inexperience with Open Source
> The core developers are all active users and followers of open source.
> They are already committers and contributors to the Eagle Github project.
> All have been involved with the source code that has been released under an
> open source license, and several of them also have experience developing
> code in an open source environment. Though the core set of Developers do
> not have Apache Open Source experience, there are plans to onboard
> individuals with Apache open source experience on to the project. Apache
> Kylin PMC members are also in the same ebay organization. We work very
> closely with Apache Ranger committers and are looking forward to find
> meaningful integrations to improve the security of hadoop platform.
>
> Homogenous Developers
> The core developers are from eBay. Today the problem of monitoring data
> activities to find and stop threats is a universal problem faced by all the
> businesses. Apache Incubation process encourages an open and diverse
> meritocratic community. Eagle intends to make every possible effort to
> build a diverse, vibrant and involved community and has already received
> substantial interest from various organizations.
>
> Reliance on Salaried Developers
> eBay invested in Eagle as the monitoring solution for Hadoop clusters and
> some of its key engineers are working full time on the project. In
> addition, since there is a growing need for securing sensitive data access
> we need a data activity monitoring solution for Hadoop, we look forward to
> other Apache developers and researchers to contribute to the project.
> Additional contributors, including Apache committers have plans to join
> this effort shortly. Also key to addressing the risk associated with
> relying on Salaried developers from a single entity is to increase the
> diversity of the contributors and actively lobby for Domain experts in the
> security space to contribute. Eagle intends to do this.
>
> Relationships with Other Apache Products
> Eagle has a strong relationship and dependency with Apache Hadoop, HBase,
> Spark, Kafka and Storm. Being part of Apache’s Incubation community, could
> help with a closer collaboration among these projects and as well as
> others. An Excessive Fascination with the Apache Brand Eagle is proposing
> to enter incubation at Apache in order to help efforts to diversify the
> committer-base, not so much to capitalize on the Apache brand. The Eagle
> project is in production use already inside eBay, but is not expected to be
> an eBay product for external customers. As such, the Eagle project is not
> seeking to use the Apache brand as a marketing tool.
>
> Documentation
> Information about Eagle can be found at https://github.com/eBay/Eagle.
> The following link provide more information about Eagle http://goeagle.io<
> http://goeagle.io/>.
>
> Initial Source
> Eagle has been under development since 2014 by a team of engineers at eBay
> Inc. It is currently hosted on Github.com under an Apache license 2.0 at
> https://github.com/eBay/Eagle. Once in incubation we will be moving the
> code base to apache git library.
>
> External Dependencies
> Eagle has the following external dependencies.
> Basic
> •JDK 1.7+
> •Scala 2.10.4
> •Apache Maven
> •JUnit
> •Log4j
> •Slf4j
> •Apache Commons
> •Apache Commons Math3
> •Jackson
> •Siddhi CEP engine
>
> Hadoop
> •Apache Hadoop
> •Apache HBase
> •Apache Hive
> •Apache Zookeeper
> •Apache Curator
>
> Apache Spark
> •Spark Core Library
>
> REST Service
> •Jersey
>
> Query
> •Antlr
>
> Stream processing
> •Apache Storm
> •Apache Kafka
>
> Web
> •AngularJS
> •jQuery
> •Bootstrap V3
> •Moment JS
> •Admin LTE
> •html5shiv
> •respond
> •Fastclick
> •Date Range Picker
> •Flot JS
>
> Cryptography
> Eagle will eventually support encryption on the wire. This is not one of
> the initial goals, and we do not expect Eagle to be a controlled export
> item due to the use of encryption. Eagle supports but does not require the
> Kerberos authentication mechanism to access secured Hadoop services.
>
> Required Resources
>
> Mailing List
> •eagle-private for private PMC discussions
> •eagle-dev for developers
> •eagle-commits for all commits
> •eagle-users for all eagle users
>
> Subversion Directory
> •Git is the preferred source control system.
>
> Issue Tracking
> •JIRA Eagle (Eagle)
>
> Other Resources
> The existing code already has unit tests so we will make use of existing
> Apache continuous testing infrastructure. The resulting load should not be
> very large.
>
> Initial Committers
> •Seshu Adunuthula <sadunuthula at ebay dot com>
> •Arun Manoharan <armanoharan at ebay dot com>
> •Edward Zhang <yonzhang at ebay dot com>
> •Hao Chen <hchen9 at ebay dot com>
> •Chaitali Gupta <cgupta at ebay dot com>
> •Libin Sun <libsun at ebay dot com>
> •Jilin Jiang <jiljiang at ebay dot com>
> •Qingwen Zhao <qingwzhao at ebay dot com>
> •Hemanth Dendukuri <hdendukuri at ebay dot com>
> •Senthil Kumar <senthilkumar at ebay dot com>
>
>
> Affiliations
> The initial committers are employees of eBay Inc.
>
> Sponsors
>
> Champion
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>
> Nominated Mentors
> •Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> Hortonworks
> •Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
> •Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
> Hortonworks
> •Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
> member
> •Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member, Hortonworks
>
> Sponsoring Entity
> We are requesting the Incubator to sponsor this project.
>
>