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Posted to commits@spot.apache.org by ce...@apache.org on 2017/01/18 07:19:25 UTC

[6/7] incubator-spot git commit: Replacing PHP index files with regular HTML due compatibility of extension on ASF

http://git-wip-us.apache.org/repos/asf/incubator-spot/blob/7bb4a301/blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/index.html
----------------------------------------------------------------------
diff --git a/blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/index.html b/blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/index.html
new file mode 100755
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--- /dev/null
+++ b/blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/index.html
@@ -0,0 +1,250 @@
+<!doctype html>
+
+<!--[if lt IE 7]><html lang="en-US" class="no-js lt-ie9 lt-ie8 lt-ie7"><![endif]-->
+<!--[if (IE 7)&!(IEMobile)]><html lang="en-US" class="no-js lt-ie9 lt-ie8"><![endif]-->
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+        <meta charset="utf-8">
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+        <title>Apache Spot (Incubating) and Cybersecurity \u2014 Using NetFlows to Detect Threats to Critical Infrastructure - Apache Spot</title>
+
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+        <meta name="MobileOptimized" content="320">
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+        <meta name="theme-color" content="#121212">
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+        <link rel='dns-prefetch' href='//s.w.org' />
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+
+        <link rel='stylesheet' id='googleFonts-css'  href='http://fonts.googleapis.com/css?family=Lato%3A400%2C700%2C400italic%2C700italic' type='text/css' media='all' />
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+        <!--[if lt IE 9]>
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+                    <main id="main" class="m-all t-2of3 d-5of7 cf" role="main" itemscope itemprop="mainContentOfPage" itemtype="http://schema.org/Blog">
+
+                        <article id="post-117" class="cf post-117 post type-post status-publish format-standard hentry category-cybersecurity" role="article" itemscope itemprop="blogPost" itemtype="http://schema.org/BlogPosting">
+
+                            <header class="article-header entry-header">
+
+                                <h1 class="entry-title single-title" itemprop="headline" rel="bookmark">Apache Spot (Incubating) and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure</h1>
+
+                                <p class="byline entry-meta vcard">
+
+                                    <time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
+                                        August 8, 2016
+                                    </time>
+                                    </span>
+                                </p>
+
+                            </header>
+                            <section class="entry-content cf" itemprop="articleBody">
+                                <p>
+                                    The \u201cfirst\u201d documented cybersecurity case was the worm replication, which was initiated by Robert T. Morris on November 2, 1988. Wow! Here we are in 2016, 28 years later, with viruses and worms giving way to Trojan horses and polymorphic code. Nowadays, we are also fighting against DDoS, phishing, spear phishing attacks, command and controls along with APTs such as Aurora, Zeus, Red October and Stuxnet. What happened with our security controls on each attack?
+                                </p>
+                                <p>
+                                    Despite heroic efforts, internal and external security controls, no matter if they are preventive, detective or corrective, can be bypassed by different situations or misconfigurations. Capabilities to detect bugs or vulnerabilities in code, protocol, etc. are still limited. When we consider how to close these gaps, we have two options:
+                                </p>
+                                <ol>
+                                    <li>
+                                        Collect information from each device that is part of the environment.
+                                    </li>
+                                    <li>
+                                        Collect information from the critical infrastructure that is used for most, if not all, of the systems.
+                                    </li>
+                                </ol>
+                                <p>
+                                    This blog will describe the second approach.
+                                </p>
+                                <p>
+                                    Critical infrastructure, including nationally significant infrastructure, can be broadly defined as the systems, assets, facilities and networks that provide essential services. For nations, this means protecting the national security, economic security and prosperity as well as the health and safety of their citizenry. If we extrapolate this definition on the IT enterprise environments, we can define the critical infrastructure as the service, or services, that need to be up and running properly 99.99999% of the time, most of the time to support other critical infrastructure, such as databases, HR systems, manufacturing systems, etc.
+                                </p>
+                                <p>
+                                    Effectively protecting critical infrastructure means that millions, if not billions, of different scenarios must be identified and monitored. To do this, the cybersecurity problem must be broken into small pieces.
+                                </p>
+                                <p>
+                                    Let\u2019s consider DNS \u2014 your communications to the Web. How can you know which communications are being established by your critical servers? And, what if you want to do it for most of your infrastructure?
+                                </p>
+                                <p>
+                                    First idea: Use NetFlow, which is a network protocol that helps us collect IP traffic information and monitor network traffic. NetFlow has the details on the communications of all of your network traffic. However, the normal data on an enterprise environment includes billions of NetFlow events per day. To use this data to identify issues, it must be stored and analyzed. Storage alone is costly. Analyzing what amount Big Data stores is an entire other challenge.
+                                </p>
+                                <p>
+                                    Apache Spot offers a solution. It was designed to gather, store and analyze Big Data. In fact, Apache Spot is an ideal solution for this cybersecurity challenge. Apache Spot can integrate many different data sources in a data lake then add operational context to the data by linking configuration, inventory, service databases and other data stores. This helps you to prioritize the actions to take under different attack, malware, APT and hacking scenarios. With Apache Spot, attacks that bypass our external or internal security controls can be identified. By delivering risk-prioritized, actionable insights, Apache Spot can support the growing need for security analytics.
+                                </p>
+                                <p>
+                                    Not only can Apache Spot collect, store and analyze billions of NetFlow packets, but it can also be adapted to meet the unique requirements of your organization. How? Apache Spot is an open-source project.
+                                </p>
+                                <p>
+                                    <strong>But Wait, There\u2019s More</strong>
+                                </p>
+                                <p>
+                                    Check out \u201c<a href="../how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/"><u>How Apache Spot Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</u></a>\u201d to learn more about the underlying Apache Spot architecture.
+                                </p>
+                                <p>
+                                    This is the first of a series of blogs that we will be writing about cybersecurity, so check back to read more.
+                                </p>
+                            </section>
+                            <footer class="article-footer">
+
+                                filed under: <a href="../../category/cybersecurity/" rel="category tag">Cybersecurity</a>
+
+                            </footer>
+
+                        </article>
+
+                    </main>
+
+					<div id="sidebar1" class="sidebar m-all t-1of3 d-2of7 last-col cf" role="complementary">
+					
+						<div id="recent-posts-2" class="widget widget_recent_entries">
+							<h4 class="widgettitle">Recent Posts</h4>
+							<ul>
+								<li>
+									<a href="../../blog/strength-in-numbers-why-consider-open-source-cybersecurity-analytics/">Strength in Numbers:  Why Consider Open Source Cybersecurity Analytics</a>
+								</li>
+								<li>
+									<a href="../../blog/jupyter-notebooks-for-data-analysis/">Jupyter Notebooks for Data Analysis</a>
+								</li>
+								<li>
+									<a href="../../blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/">Apache Spot (Incubating) and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure</a>
+								</li>
+								<li>
+									<a href="../../blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/">How Apache Spot (Incubating) Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</a>
+								</li>
+								<li>
+									<a href="../../blog/apache-spot-3-most-asked-questions/">Apache Spot (Incubating): 3 Most-Asked Questions</a>
+								</li>
+							</ul>
+						</div>
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+							<h4 class="widgettitle">Archives</h4>
+							<ul>
+								<li>
+									<a href='../../2016/10/'>October 2016</a>
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+								</li>
+								<li>
+									<a href='../../2016/08/'>August 2016</a>
+								</li>
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+									<a href='../../2016/03/'>March 2016</a>
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http://git-wip-us.apache.org/repos/asf/incubator-spot/blob/7bb4a301/blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/index.php
----------------------------------------------------------------------
diff --git a/blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/index.php b/blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/index.php
deleted file mode 100755
index d32442d..0000000
--- a/blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/index.php
+++ /dev/null
@@ -1,98 +0,0 @@
-<?php include '../../includes/config.php'; ?>
-<?php
-$bodyclass = "single single-post";
-$pageTitle = "Apache Spot (Incubating) and Cybersecurity \u2014 Using NetFlows to Detect Threats to Critical Infrastructure - Apache Spot";
-$description = "";
-$currentPage = 'blog';
-?>
-<?php include '../../includes/header.php'; ?>
-
-            <div id="content">
-
-                <div id="inner-content" class="wrap cf">
-
-                    <main id="main" class="m-all t-2of3 d-5of7 cf" role="main" itemscope itemprop="mainContentOfPage" itemtype="http://schema.org/Blog">
-
-                        <article id="post-117" class="cf post-117 post type-post status-publish format-standard hentry category-cybersecurity" role="article" itemscope itemprop="blogPost" itemtype="http://schema.org/BlogPosting">
-
-                            <header class="article-header entry-header">
-
-                                <h1 class="entry-title single-title" itemprop="headline" rel="bookmark">Apache Spot (Incubating) and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure</h1>
-
-                                <p class="byline entry-meta vcard">
-
-                                    <time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
-                                        August 8, 2016
-                                    </time>
-                                    </span>
-                                </p>
-
-                            </header>
-                            <section class="entry-content cf" itemprop="articleBody">
-                                <p>
-                                    The \u201cfirst\u201d documented cybersecurity case was the worm replication, which was initiated by Robert T. Morris on November 2, 1988. Wow! Here we are in 2016, 28 years later, with viruses and worms giving way to Trojan horses and polymorphic code. Nowadays, we are also fighting against DDoS, phishing, spear phishing attacks, command and controls along with APTs such as Aurora, Zeus, Red October and Stuxnet. What happened with our security controls on each attack?
-                                </p>
-                                <p>
-                                    Despite heroic efforts, internal and external security controls, no matter if they are preventive, detective or corrective, can be bypassed by different situations or misconfigurations. Capabilities to detect bugs or vulnerabilities in code, protocol, etc. are still limited. When we consider how to close these gaps, we have two options:
-                                </p>
-                                <ol>
-                                    <li>
-                                        Collect information from each device that is part of the environment.
-                                    </li>
-                                    <li>
-                                        Collect information from the critical infrastructure that is used for most, if not all, of the systems.
-                                    </li>
-                                </ol>
-                                <p>
-                                    This blog will describe the second approach.
-                                </p>
-                                <p>
-                                    Critical infrastructure, including nationally significant infrastructure, can be broadly defined as the systems, assets, facilities and networks that provide essential services. For nations, this means protecting the national security, economic security and prosperity as well as the health and safety of their citizenry. If we extrapolate this definition on the IT enterprise environments, we can define the critical infrastructure as the service, or services, that need to be up and running properly 99.99999% of the time, most of the time to support other critical infrastructure, such as databases, HR systems, manufacturing systems, etc.
-                                </p>
-                                <p>
-                                    Effectively protecting critical infrastructure means that millions, if not billions, of different scenarios must be identified and monitored. To do this, the cybersecurity problem must be broken into small pieces.
-                                </p>
-                                <p>
-                                    Let\u2019s consider DNS \u2014 your communications to the Web. How can you know which communications are being established by your critical servers? And, what if you want to do it for most of your infrastructure?
-                                </p>
-                                <p>
-                                    First idea: Use NetFlow, which is a network protocol that helps us collect IP traffic information and monitor network traffic. NetFlow has the details on the communications of all of your network traffic. However, the normal data on an enterprise environment includes billions of NetFlow events per day. To use this data to identify issues, it must be stored and analyzed. Storage alone is costly. Analyzing what amount Big Data stores is an entire other challenge.
-                                </p>
-                                <p>
-                                    Apache Spot offers a solution. It was designed to gather, store and analyze Big Data. In fact, Apache Spot is an ideal solution for this cybersecurity challenge. Apache Spot can integrate many different data sources in a data lake then add operational context to the data by linking configuration, inventory, service databases and other data stores. This helps you to prioritize the actions to take under different attack, malware, APT and hacking scenarios. With Apache Spot, attacks that bypass our external or internal security controls can be identified. By delivering risk-prioritized, actionable insights, Apache Spot can support the growing need for security analytics.
-                                </p>
-                                <p>
-                                    Not only can Apache Spot collect, store and analyze billions of NetFlow packets, but it can also be adapted to meet the unique requirements of your organization. How? Apache Spot is an open-source project.
-                                </p>
-                                <p>
-                                    <strong>But Wait, There\u2019s More</strong>
-                                </p>
-                                <p>
-                                    Check out \u201c<a href="../how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/"><u>How Apache Spot Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</u></a>\u201d to learn more about the underlying Apache Spot architecture.
-                                </p>
-                                <p>
-                                    This is the first of a series of blogs that we will be writing about cybersecurity, so check back to read more.
-                                </p>
-                            </section>
-                            <footer class="article-footer">
-
-                                filed under: <a href="../../category/cybersecurity/" rel="category tag">Cybersecurity</a>
-
-                            </footer>
-
-                        </article>
-
-                    </main>
-
-					<?php include '../../includes/sidebar.php'; ?>
-
-                </div>
-
-            </div>
-            
-			<?php include '../../includes/footer.php'; ?>
-
-    </body>
-
-</html>
-<!-- end of site. what a ride! -->

http://git-wip-us.apache.org/repos/asf/incubator-spot/blob/7bb4a301/blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/index.html
----------------------------------------------------------------------
diff --git a/blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/index.html b/blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/index.html
new file mode 100755
index 0000000..79a8523
--- /dev/null
+++ b/blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/index.html
@@ -0,0 +1,232 @@
+<!doctype html>
+
+<!--[if lt IE 7]><html lang="en-US" class="no-js lt-ie9 lt-ie8 lt-ie7"><![endif]-->
+<!--[if (IE 7)&!(IEMobile)]><html lang="en-US" class="no-js lt-ie9 lt-ie8"><![endif]-->
+<!--[if (IE 8)&!(IEMobile)]><html lang="en-US" class="no-js lt-ie9"><![endif]-->
+<!--[if gt IE 8]><!-->
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+    <!--<![endif]-->
+
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+
+                            <header class="article-header entry-header">
+
+                                <h1 class="entry-title single-title" itemprop="headline" rel="bookmark">How Apache Spot (Incubating) Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</h1>
+
+                                <p class="byline entry-meta vcard">
+
+                                    <time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
+                                        August 8, 2016
+                                    </time>
+                                    </span>
+                                </p>
+
+                            </header>
+                            <section class="entry-content cf" itemprop="articleBody">
+                                <p>
+                                    About four years ago, the era of the Big Data analytics began. Paired with advanced analytics, massive volumes of data can be culled to not only inform critical decisions, but also to simulate sophisticated \u201cwhat if\u201d scenarios that allow companies to gain competitive advantages by generating and predicting different scenarios. For example, a financial services company can more accurately determine what other products to offer a customer, and in what order, based on a wide variety of data, then use advanced analytics to gather insights. Creating a data lake that can be effectively used for predictive analytics raises tough questions \u2014 what data sources should we use?  How should this data be collected and ingested? What are the best algorithms to analyze the data, and how should we present these results to our decision maker?
+                                </p>
+                                <p>
+                                    Apache Spot can help to solve most of these issues. Following is a description of the Apache Spot, which is designed to facilitate Big Data analytics scenarios like the financial services company\u2019s question about the right product to offer customers.
+                                </p>
+                                <a href="../../library/images/ONI_Architecture-Diagram_1300_v4.png"><img src="../../library/images/ONI_Architecture-Diagram_1300_v4.png" alt="oni_architecture-diagram_1300_v4" /></a>
+                                <h3><strong>Apache Spot Core Components</strong></h3>
+                                <p>
+                                    The Apache Spot Core is composed of three main components \u2014 data integration (collectors), data store (HDFS here, but can also be a non-SQL database) and machine learning.
+                                </p>
+                                <p>
+                                    In this diagram, the top left shows Apache Spot Data Sources, which include the collection of the information that will be used to create a data lake. The process is simple. Define a pull or push from the source of information then capture this information on Apache Spot\u2019s \u201ccollectors.\u201d The collectors are processes that interpret the information that is sent, then write it to the HDFS system in the Apache Spot cluster. The HDFS stores the data lake and ensures that resources can grow while remaining economical at every size. The Apache Spot algorithms are part of machine learning and are used to detect the uncommon information in the data lake.
+                                </p>
+                                <h3><strong>Operational Analytics</strong></h3>
+                                <p>
+                                    As part of operational analytics, Apache Spot executes different batch processes that add information to machine learning results to provide meaning and context. Using the financial services product example, basic customer data could be augmented with information about other customers in the same region along with information about which products those customers recommended or complained about. Basically, the data scientists can \u201cplay\u201d with the data using different algorithms to identify insights.
+                                </p>
+                                <h3><strong>Visualizing Results</strong></h3>
+                                <p>
+                                    The Apache Spot GUI displays the results that the machine learning algorithms generate. Results are represented such that it is easy to identify both the most common things as well as find the most suspicious or uncommon information that is part of the data lake.
+                                </p>
+                                <h3><strong>Customizable Open Source</strong></h3>
+                                <p>
+                                    Because Apache Spot is an open-source project, most of the components depicted here can be modified by the end user.
+                                </p>
+                            </section>
+                            <footer class="article-footer">
+
+                                filed under: <a href="../../category/uncategorized/" rel="category tag">Uncategorized</a>
+
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+							<ul>
+								<li>
+									<a href="../../blog/strength-in-numbers-why-consider-open-source-cybersecurity-analytics/">Strength in Numbers:  Why Consider Open Source Cybersecurity Analytics</a>
+								</li>
+								<li>
+									<a href="../../blog/jupyter-notebooks-for-data-analysis/">Jupyter Notebooks for Data Analysis</a>
+								</li>
+								<li>
+									<a href="../../blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/">Apache Spot (Incubating) and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure</a>
+								</li>
+								<li>
+									<a href="../../blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/">How Apache Spot (Incubating) Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</a>
+								</li>
+								<li>
+									<a href="../../blog/apache-spot-3-most-asked-questions/">Apache Spot (Incubating): 3 Most-Asked Questions</a>
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http://git-wip-us.apache.org/repos/asf/incubator-spot/blob/7bb4a301/blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/index.php
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diff --git a/blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/index.php b/blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/index.php
deleted file mode 100755
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--- a/blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/index.php
+++ /dev/null
@@ -1,80 +0,0 @@
-<?php include '../../includes/config.php'; ?>
-<?php
-$bodyclass = "single single-post";
-$pageTitle = "How Apache Spot (Incubating) Helps Create Well-Stocked Data Lakes and Catch Powerful Insights - Apache Spot";
-$description = "";
-$currentPage = 'blog';
-?>
-<?php include '../../includes/header.php'; ?>
-
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-
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-
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-
-                            <header class="article-header entry-header">
-
-                                <h1 class="entry-title single-title" itemprop="headline" rel="bookmark">How Apache Spot (Incubating) Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</h1>
-
-                                <p class="byline entry-meta vcard">
-
-                                    <time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
-                                        August 8, 2016
-                                    </time>
-                                    </span>
-                                </p>
-
-                            </header>
-                            <section class="entry-content cf" itemprop="articleBody">
-                                <p>
-                                    About four years ago, the era of the Big Data analytics began. Paired with advanced analytics, massive volumes of data can be culled to not only inform critical decisions, but also to simulate sophisticated \u201cwhat if\u201d scenarios that allow companies to gain competitive advantages by generating and predicting different scenarios. For example, a financial services company can more accurately determine what other products to offer a customer, and in what order, based on a wide variety of data, then use advanced analytics to gather insights. Creating a data lake that can be effectively used for predictive analytics raises tough questions \u2014 what data sources should we use?  How should this data be collected and ingested? What are the best algorithms to analyze the data, and how should we present these results to our decision maker?
-                                </p>
-                                <p>
-                                    Apache Spot can help to solve most of these issues. Following is a description of the Apache Spot, which is designed to facilitate Big Data analytics scenarios like the financial services company\u2019s question about the right product to offer customers.
-                                </p>
-                                <a href="<?php echo BASE_URL; ?>/library/images/ONI_Architecture-Diagram_1300_v4.png"><img src="<?php echo BASE_URL; ?>/library/images/ONI_Architecture-Diagram_1300_v4.png" alt="oni_architecture-diagram_1300_v4" /></a>
-                                <h3><strong>Apache Spot Core Components</strong></h3>
-                                <p>
-                                    The Apache Spot Core is composed of three main components \u2014 data integration (collectors), data store (HDFS here, but can also be a non-SQL database) and machine learning.
-                                </p>
-                                <p>
-                                    In this diagram, the top left shows Apache Spot Data Sources, which include the collection of the information that will be used to create a data lake. The process is simple. Define a pull or push from the source of information then capture this information on Apache Spot\u2019s \u201ccollectors.\u201d The collectors are processes that interpret the information that is sent, then write it to the HDFS system in the Apache Spot cluster. The HDFS stores the data lake and ensures that resources can grow while remaining economical at every size. The Apache Spot algorithms are part of machine learning and are used to detect the uncommon information in the data lake.
-                                </p>
-                                <h3><strong>Operational Analytics</strong></h3>
-                                <p>
-                                    As part of operational analytics, Apache Spot executes different batch processes that add information to machine learning results to provide meaning and context. Using the financial services product example, basic customer data could be augmented with information about other customers in the same region along with information about which products those customers recommended or complained about. Basically, the data scientists can \u201cplay\u201d with the data using different algorithms to identify insights.
-                                </p>
-                                <h3><strong>Visualizing Results</strong></h3>
-                                <p>
-                                    The Apache Spot GUI displays the results that the machine learning algorithms generate. Results are represented such that it is easy to identify both the most common things as well as find the most suspicious or uncommon information that is part of the data lake.
-                                </p>
-                                <h3><strong>Customizable Open Source</strong></h3>
-                                <p>
-                                    Because Apache Spot is an open-source project, most of the components depicted here can be modified by the end user.
-                                </p>
-                            </section>
-                            <footer class="article-footer">
-
-                                filed under: <a href="../../category/uncategorized/" rel="category tag">Uncategorized</a>
-
-                            </footer>
-
-                        </article>
-
-                    </main>
-
-					<?php include '../../includes/sidebar.php'; ?>
-
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-
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-<!-- end of site. what a ride! -->

http://git-wip-us.apache.org/repos/asf/incubator-spot/blob/7bb4a301/blog/index.html
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new file mode 100755
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--- /dev/null
+++ b/blog/index.html
@@ -0,0 +1,304 @@
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+                                <h1 class="h2 entry-title"><a href="strength-in-numbers-why-consider-open-source-cybersecurity-analytics/" rel="bookmark" title="Strength in Numbers:  Why Consider Open Source Cybersecurity Analytics">Strength in Numbers:  Why Consider Open Source Cybersecurity Analytics</a></h1>
+                                <p class="byline entry-meta vcard">
+                                    <time class="updated entry-time" datetime="2016-10-21" itemprop="datePublished">
+                                        October 21, 2016
+                                    </time>
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+
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+                                    <p>
+                                        By Rob Kent, Vice President of Marketing at Cybraics Competition is widely considered to be a healthy and positive thing, traditionally viewed as providing options for customers and fueling innovation. In the world of cybersecurity there is no shortage of competition, in fact cybersecurity is one of the most crowded and fast-growing areas of technology&#8230;. <a class="excerpt-read-more" href="strength-in-numbers-why-consider-open-source-cybersecurity-analytics/" title="Read Strength in Numbers:  Why Consider Open Source Cybersecurity Analytics">Read more &raquo;</a>
+                                    </p>
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+                        <article id="post-136" class="cf post-136 post type-post status-publish format-standard hentry category-uncategorized" role="article">
+
+                            <header class="article-header">
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+                                <h1 class="h2 entry-title"><a href="jupyter-notebooks-for-data-analysis" rel="bookmark" title="Jupyter Notebooks for Data Analysis">Jupyter Notebooks for Data Analysis</a></h1>
+                                <p class="byline entry-meta vcard">
+                                    <time class="updated entry-time" datetime="2016-09-22" itemprop="datePublished">
+                                        September 22, 2016
+                                    </time>
+                                    </span>
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+                                <div class="m-all t-3of4 d-5of7">
+                                    <p>
+                                        Why Does Apache Spot Include iPython notebooks? The project team wants Apache Spot to be a versatile tool that can be used by anyone. This means that data scientists and developers need to be able to query and handle the source data to find all the information they need for their decision making. The&#8230; <a class="excerpt-read-more" href="jupyter-notebooks-for-data-analysis/" title="Read Jupyter Notebooks for Data Analysis">Read more &raquo;</a>
+                                    </p>
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+                            </section>
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+                        </article>
+
+                        <article id="post-117" class="cf post-117 post type-post status-publish format-standard hentry category-cybersecurity" role="article">
+
+                            <header class="article-header">
+
+                                <h1 class="h2 entry-title"><a href="apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/" rel="bookmark" title="Apache Spot and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure">Apache Spot (Incubating) and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure</a></h1>
+                                <p class="byline entry-meta vcard">
+                                    <time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
+                                        August 8, 2016
+                                    </time>
+                                    </span>
+                                </p>
+
+                            </header>
+
+                            <section class="entry-content cf">
+                                <div class="m-all t-1of4 d-2of7"></div>
+                                <div class="m-all t-3of4 d-5of7">
+                                    <p>
+                                        The \u201cfirst\u201d documented cybersecurity case was the worm replication, which was initiated by Robert T. Morris on November 2, 1988. Wow! Here we are in 2016, 28 years later, with viruses and worms giving way to Trojan horses and polymorphic code. Nowadays, we are also fighting against DDoS, phishing, spear phishing attacks, command and controls&#8230; <a class="excerpt-read-more" href="apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/" title="Read Apache Spot and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure">Read more &raquo;</a>
+                                    </p>
+                                </div>
+                            </section>
+
+                        </article>
+
+                        <article id="post-113" class="cf post-113 post type-post status-publish format-standard hentry category-uncategorized" role="article">
+
+                            <header class="article-header">
+
+                                <h1 class="h2 entry-title"><a href="how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/" rel="bookmark" title="How Apache Spot Helps Create Well-Stocked Data Lakes and Catch Powerful Insights">How Apache Spot (Incubating) Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</a></h1>
+                                <p class="byline entry-meta vcard">
+                                    <time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
+                                        August 8, 2016
+                                    </time>
+                                    </span>
+                                </p>
+
+                            </header>
+
+                            <section class="entry-content cf">
+                                <div class="m-all t-1of4 d-2of7"></div>
+                                <div class="m-all t-3of4 d-5of7">
+                                    <p>
+                                        About four years ago, the era of the Big Data analytics began. Paired with advanced analytics, massive volumes of data can be culled to not only inform critical decisions, but also to simulate sophisticated \u201cwhat if\u201d scenarios that allow companies to gain competitive advantages by generating and predicting different scenarios. For example, a financial services&#8230; <a class="excerpt-read-more" href="how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/" title="Read How Apache Spot Helps Create Well-Stocked Data Lakes and Catch Powerful Insights">Read more &raquo;</a>
+                                    </p>
+                                </div>
+                            </section>
+
+                        </article>
+
+                        <article id="post-62" class="cf post-62 post type-post status-publish format-standard hentry category-security-analytics tag-github tag-apache-spot tag-open-source" role="article">
+
+                            <header class="article-header">
+
+                                <h1 class="h2 entry-title"><a href="apache-spot-3-most-asked-questions/" rel="bookmark" title="Apache Spot: Three Most-Asked Questions">Apache Spot (Incubating): Three Most-Asked Questions</a></h1>
+                                <p class="byline entry-meta vcard">
+                                    <time class="updated entry-time" datetime="2016-03-29" itemprop="datePublished">
+                                        March 29, 2016
+                                    </time>
+                                    </span>
+                                </p>
+
+                            </header>
+
+                            <section class="entry-content cf">
+                                <div class="m-all t-1of4 d-2of7"></div>
+                                <div class="m-all t-3of4 d-5of7">
+                                    <p>
+                                        While this is not the first blog post about Apache Spot, it is the first one by a creator of the solution. As a security data scientist in Intel&#8217;s Data Center Group, I joined a small team to start thinking about solving really hard problems in cloud analytics. The team grew, and out of that&#8230; <a class="excerpt-read-more" href="apache-spot-3-most-asked-questions/" title="Read Apache Spot: Three Most-Asked Questions">Read more &raquo;</a>
+                                    </p>
+                                </div>
+                            </section>
+
+                        </article>
+
+                    </main>
+
+					<div id="sidebar1" class="sidebar m-all t-1of3 d-2of7 last-col cf" role="complementary">
+					
+						<div id="recent-posts-2" class="widget widget_recent_entries">
+							<h4 class="widgettitle">Recent Posts</h4>
+							<ul>
+								<li>
+									<a href="../blog/strength-in-numbers-why-consider-open-source-cybersecurity-analytics/">Strength in Numbers:  Why Consider Open Source Cybersecurity Analytics</a>
+								</li>
+								<li>
+									<a href="../blog/jupyter-notebooks-for-data-analysis/">Jupyter Notebooks for Data Analysis</a>
+								</li>
+								<li>
+									<a href="../blog/apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/">Apache Spot (Incubating) and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure</a>
+								</li>
+								<li>
+									<a href="../blog/how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/">How Apache Spot (Incubating) Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</a>
+								</li>
+								<li>
+									<a href="../blog/apache-spot-3-most-asked-questions/">Apache Spot (Incubating): 3 Most-Asked Questions</a>
+								</li>
+							</ul>
+						</div>
+						<div id="archives-2" class="widget widget_archive">
+							<h4 class="widgettitle">Archives</h4>
+							<ul>
+								<li>
+									<a href='../2016/10/'>October 2016</a>
+								</li>
+								<li>
+									<a href='../2016/09/'>September 2016</a>
+								</li>
+								<li>
+									<a href='../2016/08/'>August 2016</a>
+								</li>
+								<li>
+									<a href='../2016/03/'>March 2016</a>
+								</li>
+							</ul>
+						</div>
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+                        &copy; 2016 Apache Spot.
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http://git-wip-us.apache.org/repos/asf/incubator-spot/blob/7bb4a301/blog/index.php
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-<?php include '../includes/config.php'; ?>
-<?php
-$bodyclass = "blog";
-$pageTitle = "Apache Spot Blog";
-$description = "";
-$currentPage = 'blog';
-?>
-<?php include '../includes/header.php'; ?>
-
-            <div id="content">
-
-                <div id="inner-content" class="wrap cf">
-                    <main id="main" class="m-all t-2of3 d-5of7 cf" role="main" itemscope itemprop="mainContentOfPage" itemtype="http://schema.org/Blog">
-
-                        <article id="post-149" class="cf post-149 post type-post status-publish format-standard hentry category-uncategorized" role="article">
-
-                            <header class="article-header">
-
-                                <h1 class="h2 entry-title"><a href="strength-in-numbers-why-consider-open-source-cybersecurity-analytics/" rel="bookmark" title="Strength in Numbers:  Why Consider Open Source Cybersecurity Analytics">Strength in Numbers:  Why Consider Open Source Cybersecurity Analytics</a></h1>
-                                <p class="byline entry-meta vcard">
-                                    <time class="updated entry-time" datetime="2016-10-21" itemprop="datePublished">
-                                        October 21, 2016
-                                    </time>
-                                    </span>
-                                </p>
-
-                            </header>
-
-                            <section class="entry-content cf">
-                                <div class="m-all t-1of4 d-2of7"></div>
-                                <div class="m-all t-3of4 d-5of7">
-                                    <p>
-                                        By Rob Kent, Vice President of Marketing at Cybraics Competition is widely considered to be a healthy and positive thing, traditionally viewed as providing options for customers and fueling innovation. In the world of cybersecurity there is no shortage of competition, in fact cybersecurity is one of the most crowded and fast-growing areas of technology&#8230;. <a class="excerpt-read-more" href="strength-in-numbers-why-consider-open-source-cybersecurity-analytics/" title="Read Strength in Numbers:  Why Consider Open Source Cybersecurity Analytics">Read more &raquo;</a>
-                                    </p>
-                                </div>
-                            </section>
-
-                        </article>
-
-                        <article id="post-136" class="cf post-136 post type-post status-publish format-standard hentry category-uncategorized" role="article">
-
-                            <header class="article-header">
-
-                                <h1 class="h2 entry-title"><a href="jupyter-notebooks-for-data-analysis" rel="bookmark" title="Jupyter Notebooks for Data Analysis">Jupyter Notebooks for Data Analysis</a></h1>
-                                <p class="byline entry-meta vcard">
-                                    <time class="updated entry-time" datetime="2016-09-22" itemprop="datePublished">
-                                        September 22, 2016
-                                    </time>
-                                    </span>
-                                </p>
-
-                            </header>
-
-                            <section class="entry-content cf">
-                                <div class="m-all t-1of4 d-2of7"></div>
-                                <div class="m-all t-3of4 d-5of7">
-                                    <p>
-                                        Why Does Apache Spot Include iPython notebooks? The project team wants Apache Spot to be a versatile tool that can be used by anyone. This means that data scientists and developers need to be able to query and handle the source data to find all the information they need for their decision making. The&#8230; <a class="excerpt-read-more" href="jupyter-notebooks-for-data-analysis/" title="Read Jupyter Notebooks for Data Analysis">Read more &raquo;</a>
-                                    </p>
-                                </div>
-                            </section>
-
-                        </article>
-
-                        <article id="post-117" class="cf post-117 post type-post status-publish format-standard hentry category-cybersecurity" role="article">
-
-                            <header class="article-header">
-
-                                <h1 class="h2 entry-title"><a href="apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/" rel="bookmark" title="Apache Spot and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure">Apache Spot (Incubating) and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure</a></h1>
-                                <p class="byline entry-meta vcard">
-                                    <time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
-                                        August 8, 2016
-                                    </time>
-                                    </span>
-                                </p>
-
-                            </header>
-
-                            <section class="entry-content cf">
-                                <div class="m-all t-1of4 d-2of7"></div>
-                                <div class="m-all t-3of4 d-5of7">
-                                    <p>
-                                        The \u201cfirst\u201d documented cybersecurity case was the worm replication, which was initiated by Robert T. Morris on November 2, 1988. Wow! Here we are in 2016, 28 years later, with viruses and worms giving way to Trojan horses and polymorphic code. Nowadays, we are also fighting against DDoS, phishing, spear phishing attacks, command and controls&#8230; <a class="excerpt-read-more" href="apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/" title="Read Apache Spot and Cybersecurity \u2014 Using NetFlows to Detect Threats to  Critical Infrastructure">Read more &raquo;</a>
-                                    </p>
-                                </div>
-                            </section>
-
-                        </article>
-
-                        <article id="post-113" class="cf post-113 post type-post status-publish format-standard hentry category-uncategorized" role="article">
-
-                            <header class="article-header">
-
-                                <h1 class="h2 entry-title"><a href="how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/" rel="bookmark" title="How Apache Spot Helps Create Well-Stocked Data Lakes and Catch Powerful Insights">How Apache Spot (Incubating) Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</a></h1>
-                                <p class="byline entry-meta vcard">
-                                    <time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
-                                        August 8, 2016
-                                    </time>
-                                    </span>
-                                </p>
-
-                            </header>
-
-                            <section class="entry-content cf">
-                                <div class="m-all t-1of4 d-2of7"></div>
-                                <div class="m-all t-3of4 d-5of7">
-                                    <p>
-                                        About four years ago, the era of the Big Data analytics began. Paired with advanced analytics, massive volumes of data can be culled to not only inform critical decisions, but also to simulate sophisticated \u201cwhat if\u201d scenarios that allow companies to gain competitive advantages by generating and predicting different scenarios. For example, a financial services&#8230; <a class="excerpt-read-more" href="how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/" title="Read How Apache Spot Helps Create Well-Stocked Data Lakes and Catch Powerful Insights">Read more &raquo;</a>
-                                    </p>
-                                </div>
-                            </section>
-
-                        </article>
-
-                        <article id="post-62" class="cf post-62 post type-post status-publish format-standard hentry category-security-analytics tag-github tag-apache-spot tag-open-source" role="article">
-
-                            <header class="article-header">
-
-                                <h1 class="h2 entry-title"><a href="apache-spot-3-most-asked-questions/" rel="bookmark" title="Apache Spot: Three Most-Asked Questions">Apache Spot (Incubating): Three Most-Asked Questions</a></h1>
-                                <p class="byline entry-meta vcard">
-                                    <time class="updated entry-time" datetime="2016-03-29" itemprop="datePublished">
-                                        March 29, 2016
-                                    </time>
-                                    </span>
-                                </p>
-
-                            </header>
-
-                            <section class="entry-content cf">
-                                <div class="m-all t-1of4 d-2of7"></div>
-                                <div class="m-all t-3of4 d-5of7">
-                                    <p>
-                                        While this is not the first blog post about Apache Spot, it is the first one by a creator of the solution. As a security data scientist in Intel&#8217;s Data Center Group, I joined a small team to start thinking about solving really hard problems in cloud analytics. The team grew, and out of that&#8230; <a class="excerpt-read-more" href="apache-spot-3-most-asked-questions/" title="Read Apache Spot: Three Most-Asked Questions">Read more &raquo;</a>
-                                    </p>
-                                </div>
-                            </section>
-
-                        </article>
-
-                    </main>
-
-				<?php include '../includes/sidebar.php'; ?>
-
-                </div>
-
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-            
-			<?php include '../includes/footer.php'; ?>
-
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-
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