Streams Processing meetup on Wednesday, February 5, 2020 at LinkedIn, Sunnyvale

[Joel Koshy <jj...@gmail.com>]

*[bcc: (users,dev)@kafka.apache.org <http://kafka.apache.org>]*

Hello,

The Streams Infra team invites you to attend the Streams Processing meetup
to be held on Wednesday, February 5, 2020. This meetup will focus on Apache
Kafka, Apache Samza and related streaming technologies.

*Where*: Unify Conference room, 950 W Maude Ave, Sunnyvale

*When*: 5:00 - 8:00 PM

*RSVP*: Please RSVP here (only if attending in person)
https://www.meetup.com/Stream-Processing-Meetup-LinkedIn/events/267283444/
A streaming link will be posted approximately 30 minutes prior to the event.

*Agenda:*

     - 5:00 PM: Doors open and catered food available

5:00 - 6:00 PM: Networking

6:00 - 6:30 PM:
*High-performance data replication at Salesforce with MirusPaul Davidson,
Salesforce*

At Salesforce we manage high-volume Apache Kafka clusters in a growing
number of data centers around the globe. In the past we relied on Kafka's
Mirror Maker tool for cross-data center replication but, as the volume and
variety of data increased, we needed a new solution to maintain a high
standard of service reliability. In this talk, we will describe Mirus, our
open-source data replication tool based on Kafka Connect. Mirus was
designed for reliable, high-performance data replication at scale. It
successfully replaced MirrorMaker at Salesforce and has now been running
reliably in production for more than a year. We will give an overview of
the Mirus design and discuss the lessons we learned deploying, tuning, and
operating Mirus in a high-volume production environment.

6:30 - 7:00 PM: *Defending users from Abuse using Stream Processing at
LinkedIn, Bhargav Golla, LinkedIn *

When there are more than half a billion users, how can one effectively,
reliably and scalably classify them as good and bad users? This talk will
highlight how the Anti-Abuse team at LinkedIn leverages Streams Processing
technologies like Samza and Brooklin to keep the good users in a trusted
environment devoid of bad actors.

7:00 - 7:30 PM: *Enabling Mission-critical Stateful Stream Processing with
Samza, Ray Manpreet Singh Matharu, LinkedIn*

Samza powers a variety of large-scale business-critical stateful stream
processing applications at LinkedIn. Their scale necessitates using
persistent and replicated local state. Unfortunately, hard failures can
cause a loss of this local state, and re-caching it can incur downtime
ranging from a few minutes to hours! In this talk, we describe the systems
and protocols that we've devised that bound the down time to a few seconds.
We detail the tradeoffs our approach brings and how we tackle them in
production at LinkedIn.

7:30 - 8:00 PM: Additional networking and Q&A

Hope to see you there!

*[Streams Infra team @ LinkedIn]*