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+        <h1 class="page-header" style="margin-top: 0px">HDFS Data Activity 
Monitoring Quick Start</h1>
+        <p><em>Since Apache Eagle 0.3.0-incubating. Apache Eagle will be 
called Eagle in the following.</em></p>
+
+<p>This Guide describes the steps to enable data activity monitoring of 
“HDFS File System”.</p>
+
+<ul>
+  <li>Prerequisite</li>
+  <li>Stream HDFS audit logs into Kafka<sup id="fnref:KAFKA"><a 
href="#fn:KAFKA" class="footnote">1</a></sup></li>
+  <li>Demos “HDFS Data Activity Monitoring”
+<br /><br /></li>
+</ul>
+
+<h3 id="prerequisite"><strong>Prerequisite</strong></h3>
+<ul>
+  <li>Complete the setup from <a href="/docs/quick-start.html">Quick 
Start(Eagle In Sandbox)</a>       
+<br /><br /></li>
+</ul>
+
+<h3 id="stream-hdfs-audit-logs-into-kafka"><strong>Stream HDFS audit logs into 
Kafka</strong></h3>
+
+<p>Note: This section describes how to configure Kafka log4j to stream audit 
logs into Eagle platform. For another option to stream HDFS audit logs into 
Kafka using Logstash <a href="/docs/import-hdfs-auditLog.html">Click 
Here</a></p>
+
+<ul>
+  <li>
+    <p><strong>Step 1</strong>: Configure Advanced hdfs-log4j via <a 
href="http://localhost:8080/#/main/services/HDFS/configs"; 
target="_blank">Ambari UI</a><sup id="fnref:AMBARI"><a href="#fn:AMBARI" 
class="footnote">2</a></sup>, by adding below “KAFKA_HDFS_AUDIT” log4j 
appender to hdfs audit logging.</p>
+
+    <pre><code> 
log4j.appender.KAFKA_HDFS_AUDIT=org.apache.eagle.log4j.kafka.KafkaLog4jAppender
+ log4j.appender.KAFKA_HDFS_AUDIT.Topic=sandbox_hdfs_audit_log
+ log4j.appender.KAFKA_HDFS_AUDIT.BrokerList=sandbox.hortonworks.com:6667
+ 
log4j.appender.KAFKA_HDFS_AUDIT.KeyClass=org.apache.eagle.log4j.kafka.hadoop.AuditLogKeyer
+ log4j.appender.KAFKA_HDFS_AUDIT.Layout=org.apache.log4j.PatternLayout
+ log4j.appender.KAFKA_HDFS_AUDIT.Layout.ConversionPattern=%d{ISO8601} %p 
%c{2}: %m%n
+ log4j.appender.KAFKA_HDFS_AUDIT.ProducerType=async
+</code></pre>
+
+    <p><img src="/images/docs/hdfs-log4j-conf.png" alt="HDFS LOG4J 
Configuration" title="hdfslog4jconf" /></p>
+  </li>
+  <li>
+    <p><strong>Step 2</strong>: Edit Advanced hadoop-env via <a 
href="http://localhost:8080/#/main/services/HDFS/configs"; 
target="_blank">Ambari UI</a>, and add the reference to KAFKA_HDFS_AUDIT to 
HADOOP_NAMENODE_OPTS.</p>
+
+    <pre><code>-Dhdfs.audit.logger=INFO,DRFAAUDIT,KAFKA_HDFS_AUDIT
+</code></pre>
+
+    <p><img src="/images/docs/hdfs-env-conf.png" alt="HDFS Environment 
Configuration" title="hdfsenvconf" /></p>
+  </li>
+  <li>
+    <p><strong>Step 3</strong>: Edit Advanced hadoop-env via <a 
href="http://localhost:8080/#/main/services/HDFS/configs"; 
target="_blank">Ambari UI</a>, and append the following command to it.</p>
+
+    <pre><code>export 
HADOOP_CLASSPATH=${HADOOP_CLASSPATH}:/usr/hdp/current/eagle/lib/log4jkafka/lib/*
+</code></pre>
+
+    <p><img src="/images/docs/hdfs-env-conf2.png" alt="HDFS Environment 
Configuration" title="hdfsenvconf2" /></p>
+  </li>
+  <li>
+    <p><strong>Step 4</strong>: save the changes</p>
+  </li>
+  <li>
+    <p><strong>Step 5</strong>: “Restart All” Storm<sup 
id="fnref:STORM"><a href="#fn:STORM" class="footnote">3</a></sup> &amp; Kafka 
from Ambari.</p>
+  </li>
+  <li>
+    <p><strong>Step 6</strong>: Restart name node</p>
+  </li>
+</ul>
+
+<p><img src="/images/docs/nn-restart.png" alt="Restart Services" 
title="Services" /></p>
+
+<ul>
+  <li>
+    <p><strong>Step 7</strong>: Check whether logs from 
“/var/log/hadoop/hdfs/hdfs-audit.log” are flowing into topic 
<code>sandbox_hdfs_audit_log</code></p>
+
+    <pre><code>  $ /usr/hdp/2.2.4.2-2/kafka/bin/kafka-console-consumer.sh 
--zookeeper sandbox.hortonworks.com:2181 --topic sandbox_hdfs_audit_log      
+</code></pre>
+  </li>
+</ul>
+
+<p><br /></p>
+
+<h3 id="demos"><strong>Demos</strong></h3>
+<ul>
+  <li>Login to Eagle UI <a 
href="http://localhost:9099/eagle-service/";>http://localhost:9099/eagle-service/</a>
 using username and password as “admin” and “secret”</li>
+  <li><strong>HDFS</strong>:
+    <ol>
+      <li>Click on menu “DAM” and select “HDFS” to view HDFS 
policy</li>
+      <li>You should see policy with name “viewPrivate”. This Policy 
generates alert when any user reads HDFS file name “private” under 
“tmp” folder.</li>
+      <li>
+        <p>In sandbox read restricted HDFS file “/tmp/private” by using 
command</p>
+
+        <blockquote>
+          <p>hadoop fs -cat /tmp/private</p>
+        </blockquote>
+      </li>
+    </ol>
+
+    <p>From UI click on alert tab and you should see alert for the attempt to 
read restricted file.<br />
+<br /></p>
+  </li>
+</ul>
+
+<hr />
+
+<h4 id="footnotes"><em>Footnotes</em></h4>
+
+<div class="footnotes">
+  <ol>
+    <li id="fn:KAFKA">
+      <p><em>All mentions of “kafka” on this page represent Apache 
Kafka.</em> <a href="#fnref:KAFKA" class="reversefootnote">&#8617;</a></p>
+    </li>
+    <li id="fn:AMBARI">
+      <p><em>All mentions of “ambari” on this page represent Apache 
Ambari.</em> <a href="#fnref:AMBARI" class="reversefootnote">&#8617;</a></p>
+    </li>
+    <li id="fn:STORM">
+      <p><em>Apache Storm.</em> <a href="#fnref:STORM" 
class="reversefootnote">&#8617;</a></p>
+    </li>
+  </ol>
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http://git-wip-us.apache.org/repos/asf/eagle/blob/d6fed677/_site/docs/hive-query-activity-monitoring.html
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+        
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+       
+        <li class="heading">Download</li>
+        
+          <li class="sidenavli  "><a href="/docs/download-latest.html" 
data-permalink="/docs/hive-query-activity-monitoring.html" id="">Latest version 
(v0.5.0)</a></li>
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id="">Archived</a></li>
+        
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+       
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+        
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data-permalink="/docs/hive-query-activity-monitoring.html" 
id="">Security</a></li>
+        
+        <li class="divider"></li>
+      
+        <li class="sidenavli">
+          <a href="mailto:d...@eagle.apache.org"; target="_blank">Need Help?</a>
+        </li>
+        </ul>
+      </div>
+      <div class="col-xs-6 col-sm-9 page-main-content" style="margin-left: 
-15px" id="loadcontent">
+        <h1 class="page-header" style="margin-top: 0px">Hive Query Activity 
Monitoring Quick Start</h1>
+        <p><em>Since Apache Eagle 0.3.0-incubating. Apache Eagle will be 
called Eagle in the following.</em></p>
+
+<p>This Guide describes the steps to enable HIVE<sup id="fnref:HIVE"><a 
href="#fn:HIVE" class="footnote">1</a></sup> query activity monitoring.</p>
+
+<ul>
+  <li>Prerequisite</li>
+  <li>Stream HIVE query logs into Eagle platform</li>
+  <li>Demos “Hive Query Activity Monitoring”
+<br /><br /></li>
+</ul>
+
+<h3 id="prerequisite"><strong>Prerequisite</strong></h3>
+<ul>
+  <li>Complete the setup from <a href="/docs/quick-start.html">Quick 
Start(Eagle In Sandbox)</a>        
+<br /><br /></li>
+</ul>
+
+<h3 id="stream-hive-query-logs-into-eagle-platform"><strong>Stream HIVE query 
logs into Eagle platform</strong></h3>
+<p>There are a couple of methods to capture HIVE query logs. As of 0.4.0, 
Eagle uses YARN API to periodically poll running HIVE jobs and in realtime 
parse query expressions. So here Eagle assumes resource manager is installed in 
Hadoop[^HADOOP] cluster.</p>
+
+<h3 id="demos"><strong>Demos</strong></h3>
+<ul>
+  <li><strong>Hive</strong>:
+    <ol>
+      <li>Click on menu “DAM” and select “Hive” to view Hive 
policy</li>
+      <li>You should see policy with name “queryPhoneNumber”. This Policy 
generates alert when hive table with sensitivity(Phone_Number) information is 
queried.</li>
+      <li>In sandbox read restricted sensitive HIVE column. ( To learn more 
about data sensitivity settings click <a 
href="/docs/tutorial/classification.html">Data Classification Tutorial</a>)</li>
+    </ol>
+  </li>
+</ul>
+
+<pre><code>$ su hive
+$ hive
+$ set hive.execution.engine=mr;
+$ use xademo;
+$ select a.phone_number from customer_details a, call_detail_records b where 
a.phone_number=b.phone_number;
+</code></pre>
+
+<p>From UI click on alert tab and you should see alert for your attempt to 
read restricted column.</p>
+
+<hr />
+
+<h4 id="footnotes"><em>Footnotes</em></h4>
+
+<div class="footnotes">
+  <ol>
+    <li id="fn:HIVE">
+      <p><em>All mentions of “hive” on this page represent Apache 
Hive.</em> <a href="#fnref:HIVE" class="reversefootnote">&#8617;</a></p>
+    </li>
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http://git-wip-us.apache.org/repos/asf/eagle/blob/d6fed677/_site/docs/import-hdfs-auditLog.html
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+        
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data-permalink="/docs/import-hdfs-auditLog.html" id="">Archived</a></li>
+        
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+       
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+        
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data-permalink="/docs/import-hdfs-auditLog.html" id="">Security</a></li>
+        
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+      
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+          <a href="mailto:d...@eagle.apache.org"; target="_blank">Need Help?</a>
+        </li>
+        </ul>
+      </div>
+      <div class="col-xs-6 col-sm-9 page-main-content" style="margin-left: 
-15px" id="loadcontent">
+        <h1 class="page-header" style="margin-top: 0px">How to stream hdfs log 
data into Kafka</h1>
+        <p>As Apache Eagle consumes the data via Kafka<sup id="fnref:KAFKA"><a 
href="#fn:KAFKA" class="footnote">1</a></sup> topics in some topologies, such 
as HDFS audit log. To enable the full function of monitoring, a user needs to 
stream its data into a Kafka topic.</p>
+
+<p>There are two ways to do that. The first one is <strong>Logstash</strong>, 
which naturally supports Kafka as the output plugin; the second one is to
+install a <strong>namenode log4j Kafka appender</strong>.</p>
+
+<h3 id="logstash-kafka">Logstash-kafka</h3>
+
+<ul>
+  <li>
+    <p><strong>Step 1</strong>: Create a Kafka topic as the streaming 
input.</p>
+
+    <p>Here is an sample Kafka command to create topic 
‘sandbox_hdfs_audit_log’</p>
+
+    <pre><code>cd &lt;kafka-home&gt;
+bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 
--partitions 1 --topic sandbox_hdfs_audit_log
+</code></pre>
+  </li>
+  <li>
+    <p><strong>Step 2</strong>: Install Logstash-kafka plugin</p>
+
+    <ul>
+      <li>
+        <p>For Logstash 1.5.x, logstash-kafka has been intergrated into <a 
href="https://github.com/logstash-plugins/logstash-input-kafka";>logstash-input-kafka</a>
 and <a 
href="https://github.com/logstash-plugins/logstash-output-kafka";>logstash-output-kafka</a>,
+  and released with the 1.5 version of Logstash. So you can directly use 
it.</p>
+      </li>
+      <li>
+        <p>For Logstash 1.4.x, a user should install <a 
href="https://github.com/joekiller/logstash-kafka";>logstash-kafka</a> firstly. 
Notice that this version <strong>does not support 
partition_key_format</strong>.</p>
+      </li>
+    </ul>
+  </li>
+  <li>
+    <p><strong>Step 3</strong>: Create a Logstash configuration file under 
${LOGSTASH_HOME}/conf. Here is a sample.</p>
+
+    <pre><code>  input {
+      file {
+          type =&gt; "hdp-nn-audit"
+          path =&gt; "/path/to/audit.log"
+          start_position =&gt; end
+          sincedb_path =&gt; "/var/log/logstash/"
+       }
+  }
+
+  filter{
+      if [type] == "hdp-nn-audit" {
+          grok {
+              match =&gt; ["message", 
"ugi=(?&lt;user&gt;([\w\d\-]+))@|ugi=(?&lt;user&gt;([\w\d\-]+))/[\w\d\-.]+@|ugi=(?&lt;user&gt;([\w\d.\-_]+))[\s(]+"]
+          }
+      }
+  }
+
+  output {
+      if [type] == "hdp-nn-audit" {
+          kafka {
+              codec =&gt; plain {
+                  format =&gt; "%{message}"
+              }
+              broker_list =&gt; "localhost:9092"
+              topic_id =&gt; "sandbox_hdfs_audit_log"
+              request_required_acks =&gt; 0
+              request_timeout_ms =&gt; 10000
+              producer_type =&gt; "async"
+              message_send_max_retries =&gt; 3
+              retry_backoff_ms =&gt; 100
+              queue_buffering_max_ms =&gt; 5000
+              queue_enqueue_timeout_ms =&gt; 5000
+              batch_num_messages =&gt; 200
+              send_buffer_bytes =&gt; 102400
+              client_id =&gt; "hdp-nn-audit"
+              partition_key_format =&gt; "%{user}"
+          }
+          # stdout { codec =&gt; rubydebug }
+      }
+  }
+</code></pre>
+  </li>
+  <li>
+    <p><strong>Step 4</strong>: Start Logstash</p>
+
+    <pre><code>bin/logstash -f conf/sample.conf
+</code></pre>
+  </li>
+  <li>
+    <p><strong>Step 5</strong>: Check whether logs are flowing into the kafka 
topic specified by <code>topic_id</code></p>
+  </li>
+</ul>
+
+<h3 id="log4j-kafka-appender">Log4j Kafka Appender</h3>
+
+<blockquote>
+  <p>Notice that if you use Ambari<sup id="fnref:AMBARI"><a href="#fn:AMBARI" 
class="footnote">2</a></sup>, such as in sandbox, you <strong>must</strong> 
follow below steps via Ambari UI. In addition, restarting namenode is 
required.</p>
+</blockquote>
+
+<ul>
+  <li>
+    <p><strong>Step 1</strong>: Create a Kafka topic. Here is a example Kafka 
command for creating topic “sandbox_hdfs_audit_log”</p>
+
+    <pre><code>cd &lt;kafka-home&gt;
+bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 
--partitions 1 --topic sandbox_hdfs_audit_log
+</code></pre>
+  </li>
+  <li>
+    <p><strong>Step 2</strong>: Configure $HADOOP_CONF_DIR/log4j.properties, 
and add a log4j appender “KAFKA_HDFS_AUDIT” to hdfs audit logging</p>
+
+    
<pre><code>log4j.appender.KAFKA_HDFS_AUDIT=org.apache.eagle.log4j.kafka.KafkaLog4jAppender
+log4j.appender.KAFKA_HDFS_AUDIT.Topic=sandbox_hdfs_audit_log
+log4j.appender.KAFKA_HDFS_AUDIT.BrokerList=sandbox.hortonworks.com:6667
+log4j.appender.KAFKA_HDFS_AUDIT.KeyClass=org.apache.eagle.log4j.kafka.hadoop.AuditLogKeyer
+log4j.appender.KAFKA_HDFS_AUDIT.Layout=org.apache.log4j.PatternLayout
+log4j.appender.KAFKA_HDFS_AUDIT.Layout.ConversionPattern=%d{ISO8601} %p %c{2}: 
%m%n
+log4j.appender.KAFKA_HDFS_AUDIT.ProducerType=async
+#log4j.appender.KAFKA_HDFS_AUDIT.BatchSize=1
+#log4j.appender.KAFKA_HDFS_AUDIT.QueueSize=1
+</code></pre>
+
+    <p><img src="/images/docs/hdfs-log4j-conf.png" alt="HDFS LOG4J 
Configuration" title="hdfslog4jconf" /></p>
+  </li>
+  <li>
+    <p><strong>Step 3</strong>: Edit $HADOOP_CONF_DIR/hadoop-env.sh, and add 
the reference to KAFKA_HDFS_AUDIT to HADOOP_NAMENODE_OPTS.</p>
+
+    <pre><code>-Dhdfs.audit.logger=INFO,DRFAAUDIT,KAFKA_HDFS_AUDIT
+</code></pre>
+
+    <p><img src="/images/docs/hdfs-env-conf.png" alt="HDFS Environment 
Configuration" title="hdfsenvconf" /></p>
+  </li>
+  <li>
+    <p><strong>Step 4</strong>: Edit $HADOOP_CONF_DIR/hadoop-env.sh, and 
append the following command to it.</p>
+
+    <pre><code>export 
HADOOP_CLASSPATH=${HADOOP_CLASSPATH}:/path/to/eagle/lib/log4jkafka/lib/*
+</code></pre>
+
+    <p><img src="/images/docs/hdfs-env-conf2.png" alt="HDFS Environment 
Configuration" title="hdfsenvconf2" /></p>
+  </li>
+  <li>
+    <p><strong>Step 5</strong>: save the changes and restart the namenode.</p>
+  </li>
+  <li>
+    <p><strong>Step 6</strong>: Check whether logs are flowing into Topic 
sandbox_hdfs_audit_log</p>
+
+    <pre><code>$ /usr/hdp/current/kafka-broker/bin/kafka-console-consumer.sh 
--zookeeper localhost:2181 --topic sandbox_hdfs_audit_log
+</code></pre>
+  </li>
+</ul>
+
+<hr />
+
+<h4 id="footnotes"><em>Footnotes</em></h4>
+
+<div class="footnotes">
+  <ol>
+    <li id="fn:KAFKA">
+      <p><em>All mentions of “kafka” on this page represent Apache 
Kafka.</em> <a href="#fnref:KAFKA" class="reversefootnote">&#8617;</a></p>
+    </li>
+    <li id="fn:AMBARI">
+      <p><em>all mentions of “ambari” on this page represent Apache 
Ambari.</em> <a href="#fnref:AMBARI" class="reversefootnote">&#8617;</a></p>
+    </li>
+  </ol>
+</div>
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Hive, Apache Ambari, Ambari, Apache Spark, Spark, Apache Kafka, Kafka, Apache 
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data-permalink="/docs/index.html" id="">Security</a></li>
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+      <div class="col-xs-6 col-sm-9 page-main-content" style="margin-left: 
-15px" id="loadcontent">
+        <h1 class="page-header" style="margin-top: 0px">Introduction</h1>
+        <h3 id="welcome-to-apache-eagle">Welcome to Apache Eagle</h3>
+
+<blockquote>
+  <p>Apache Eagle (called Eagle in the following) is an open source analytics 
solution for identifying security and performance issues instantly on big data 
platforms e.g. Hadoop<sup id="fnref:HADOOP"><a href="#fn:HADOOP" 
class="footnote">1</a></sup>, Spark<sup id="fnref:SPARK"><a href="#fn:SPARK" 
class="footnote">2</a></sup>, NoSQL etc. It analyzes data activities, yarn 
applications, jmx metrics, and daemon logs etc., provides state-of-the-art 
alert engine to identify security breach, performance issues and shows 
insights.</p>
+</blockquote>
+
+<h3 id="basic-analytics-and-monitoring-flow">Basic Analytics and Monitoring 
Flow</h3>
+
+<p>Normally 3 basic steps are involved in Eagle platform: Data Integration, 
Alerting Engine and Insights.</p>
+
+<ul>
+  <li>
+    <p>Data Integration normally is streaming process application, for example 
Apache Storm topology or Spark streaming application. During data integration, 
raw data can be transformed, normalized, analyzed etc. The output of data 
integration will be streamed into Alerting Engine and Insights.</p>
+  </li>
+  <li>
+    <p>Alerting Engine is highly scalable rule execution engine, which is 
embedded into Data Integration application as of Eagle 0.4.0. With alerting 
engine, user can create/update comprehensive policies on the fly.</p>
+  </li>
+  <li>
+    <p>Insights is for correlating alerts with raw data for user to explore 
root causes.</p>
+  </li>
+</ul>
+
+<p>Depending on data source, data integrations may use pull or push methods to 
stream data into Eagle platform, for example HDFS audit log can be pushed by 
logstash, but Hive<sup id="fnref:HIVE"><a href="#fn:HIVE" 
class="footnote">3</a></sup> query log can be pulled by Hive Integration 
application.</p>
+
+<h3 id="key-qualities">Key Qualities</h3>
+
+<ul>
+  <li>
+    <p><strong>Real Time</strong>: We understand the importance of timing and 
acting fast in case of a security breach or performance issue. So we designed 
Eagle to make sure the alerts are generated immediately even for very high 
volume streaming data. This is achieved by running Eagle alert engine on top of 
streaming framework, e.g. Apache Storm with high performance CEP engine e.g. 
WSO2 Siddhi etc.</p>
+  </li>
+  <li>
+    <p><strong>Scalability</strong>: At eBay we operate one of world’s 
largest big data platforms Hadoop, Spark etc. The volume of operational logs 
and user activities generated by big data platforms is very huge. Eagle alert 
engine is well designed to evaluate polices against data in motion at cloud 
scale.This is achieved by dynamically partitioning data and policies based on 
policy semantics.</p>
+  </li>
+  <li>
+    <p><strong>Metadata Driven</strong>: Eagle understands what policies are 
evaluated for what data source in what physical boxes. This thanks to Eagle 
metadata design and master/slave distributed computing architecture. Eagle 
alert engine’s coordinator listens to metadata change, calculates snapshot 
for mapping policy to resource and then dynamically deploys snapshot onto storm 
spouts and bolts.</p>
+  </li>
+  <li>
+    <p><strong>Extensibility</strong>: Eagle is designed with extensibility in 
mind. You can integrate many different data sources into Eagle platform with a 
few clicks.</p>
+  </li>
+</ul>
+
+<hr />
+
+<h4 id="footnotes"><em>Footnotes</em></h4>
+
+<div class="footnotes">
+  <ol>
+    <li id="fn:HADOOP">
+      <p><em>All mentions of “hadoop” on this page represent Apache 
Hadoop.</em> <a href="#fnref:HADOOP" class="reversefootnote">&#8617;</a></p>
+    </li>
+    <li id="fn:SPARK">
+      <p><em>All mentions of “spark” on this page represent Apache 
Spark.</em> <a href="#fnref:SPARK" class="reversefootnote">&#8617;</a></p>
+    </li>
+    <li id="fn:HIVE">
+      <p><em>All mentions of “hive” on this page represent Apache 
HIVE.</em> <a href="#fnref:HIVE" class="reversefootnote">&#8617;</a></p>
+    </li>
+  </ol>
+</div>
+
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+</div>
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+Apache Eagle, Eagle, Apache Hadoop, Hadoop, Apache HBase, HBase, Apache Hive, 
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data-permalink="/docs/installation.html" id="">Security</a></li>
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+      <div class="col-xs-6 col-sm-9 page-main-content" style="margin-left: 
-15px" id="loadcontent">
+        <h1 class="page-header" style="margin-top: 0px">Install Apache 
Eagle</h1>
+        <h3 
id="install-apache-eagle-called-eagle-in-the-following-to-sandbox">Install 
Apache Eagle (called Eagle in the following) to Sandbox</h3>
+
+<h4 id="pre-requisites">Pre-requisites</h4>
+
+<blockquote>
+  <p>To insall eagle on a sandbox you need to have orcale virtual box and HDP 
sandbox image.</p>
+</blockquote>
+
+<ol>
+  <li><a href="https://www.virtualbox.org/wiki/Downloads";>Oracle 
VirtualBox</a>.</li>
+  <li><a 
href="http://hortonworks.com/products/hortonworks-sandbox/#install";>Hortonworks 
Sandbox</a> v 2.2.4 or later.</li>
+</ol>
+
+<h4 id="register-hdp-sandbox">Register HDP sandbox</h4>
+
+<ol>
+  <li><a href="http://127.0.0.1:8888/";>Register</a> Hortonworks sandbox.</li>
+  <li><a href="http://127.0.0.1:8000/";>Enable Ambari</a>. Click on Enable 
Button.</li>
+  <li><a href="http://127.0.0.1:8080";>Login</a> as admin/admin.</li>
+</ol>
+
+<h4 id="install-eagle">Install Eagle</h4>
+
+<ul>
+  <li>
+    <p><strong>Step 1</strong>: Clone stable version from <a 
href="https://github.com/apache/eagle/releases/tag/v0.4.0-incubating";>eagle 
github</a>
+&gt;       Build project mvn clean install -DskipTests=true</p>
+  </li>
+  <li>
+    <p><strong>Step 2</strong>:  Download eagle-bin-0.1.0.tar.gz package from 
successful build into your HDP sandbox.</p>
+
+    <ul>
+      <li>
+        <p>Option 1: <code>scp -P 2222  
eagle/eagle-assembly/target/eagle-0.1.0-bin.tar.gz 
root@127.0.0.1:/usr/hdp/current/</code></p>
+      </li>
+      <li>
+        <p>Option 2: Create shared directory between host and Sandbox, and 
restart Sandbox. Then you can find the shared directory under /media in 
Sandbox.</p>
+      </li>
+    </ul>
+  </li>
+  <li>
+    <p><strong>Step 3</strong>: Extract eagle tarball package</p>
+
+    <pre><code>$ cd /usr/hdp/current
+$ tar -zxvf eagle-0.1.0-bin.tar.gz
+$ mv eagle-0.1.0 eagle
+</code></pre>
+  </li>
+  <li>
+    <p><strong>Step 4</strong>: Add root as a HBase<sup id="fnref:HBASE"><a 
href="#fn:HBASE" class="footnote">1</a></sup> superuser via <a 
href="http://127.0.0.1:8080/#/main/services/HBASE/configs";>Ambari</a> 
(Optional, a user can operate HBase by sudo su hbase, as an alternative).</p>
+  </li>
+  <li>
+    <p><strong>Step 5</strong>: Install Eagle Ambari<sup id="fnref:AMBARI"><a 
href="#fn:AMBARI" class="footnote">2</a></sup> service 
+&gt;
+  /usr/hdp/current/eagle/bin/eagle-ambari.sh install.</p>
+  </li>
+  <li>
+    <p><strong>Step 6</strong>: Restart <a 
href="http://127.0.0.1:8000/";>Ambari</a> click on disable and enable Ambari 
back.</p>
+  </li>
+  <li>
+    <p><strong>Step 7</strong>: Start HBase &amp; Storm<sup 
id="fnref:STORM"><a href="#fn:STORM" class="footnote">3</a></sup> &amp; 
Kafka<sup id="fnref:KAFKA"><a href="#fn:KAFKA" class="footnote">4</a></sup>
+From Ambari UI, restart any suggested components(“Restart button on top”) 
&amp; Start Storm (Start “Nimbus” ,”Supervisor” &amp; “Storm UI 
Server”), Kafka (Start “Kafka Broker”) , HBase (Start “RegionServer”  
and “ HBase Master”) 
+&gt;
+<img src="/images/docs/Services.png" alt="Restart Services" title="Services" 
/></p>
+  </li>
+  <li>
+    <p><strong>Step 8</strong>: Add Eagle Service To Ambari. (Click For 
Video)</p>
+
+    <ul>
+      <li>
+        <p>Click on “Add Service” under Actions button on Ambari Main 
page</p>
+
+        <p><img src="/images/docs/add-service.png" alt="AddService" 
title="AddService" /></p>
+      </li>
+      <li>
+        <p>Select “Eagle” in list of services and proceed to install all 
eagle services. 
+EagleServiceSuccess</p>
+
+        <p><img src="/images/docs/eagle-service-success.png" alt="Eagle 
Services" title="Eagle Services" /></p>
+      </li>
+    </ul>
+  </li>
+  <li>
+    <p><strong>Step 9</strong>: Add Policies and meta data required by running 
below script.</p>
+
+    <pre><code>$ 
/usr/hdp/current/eagle/examples/sample-sensitivity-resource-create.sh 
+$ /usr/hdp/current/eagle/examples/sample-policy-create.sh
+</code></pre>
+  </li>
+</ul>
+
+<hr />
+
+<h4 id="footnotes"><em>Footnotes</em></h4>
+
+<div class="footnotes">
+  <ol>
+    <li id="fn:HBASE">
+      <p><em>All mentions of “hbase” on this page represent Apache 
HBase.</em> <a href="#fnref:HBASE" class="reversefootnote">&#8617;</a></p>
+    </li>
+    <li id="fn:AMBARI">
+      <p><em>All mentions of “ambari” on this page represent Apache 
Ambari.</em> <a href="#fnref:AMBARI" class="reversefootnote">&#8617;</a></p>
+    </li>
+    <li id="fn:STORM">
+      <p><em>All mentions of “storm” on this page represent Apache 
Storm.</em> <a href="#fnref:STORM" class="reversefootnote">&#8617;</a></p>
+    </li>
+    <li id="fn:KAFKA">
+      <p><em>All mentions of “kafka” on this page represent Apache 
Kafka.</em> <a href="#fnref:KAFKA" class="reversefootnote">&#8617;</a></p>
+    </li>
+  </ol>
+</div>
+
+      </div><!--end of loadcontent-->  
+    </div>
+    <!--end of centered content--> 
+  </div>
+</div>
+<!--end of container-->
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+<!-- footer start -->
+<div class="footerwrapper">
+  <div class="container">
+    <div class="row">
+      <div class="col-md-12"><div style="margin-left:auto; margin-right:auto; 
text-align:center;font-size: 12px">
+<div>
+</div>
+<div>
+<a href="http://www.apache.org";>
+<img id="asf-logo" alt="Apache Software Foundation" 
src="/images/apache-logo-small.gif">
+</a>
+</div>
+<div>
+Copyright © 2015 <a href="http://www.apache.org";>The Apache Software 
Foundation</a>, Licensed under the <a 
href="http://www.apache.org/licenses/LICENSE-2.0";>Apache License, Version 
2.0</a>.
+</div>
+<div>
+Apache Eagle, Eagle, Apache Hadoop, Hadoop, Apache HBase, HBase, Apache Hive, 
Hive, Apache Ambari, Ambari, Apache Spark, Spark, Apache Kafka, Kafka, Apache 
Storm, Storm, Apache Maven, Maven, Apache Tomcat, Tomcat, Apache Derby, Derby, 
Apache Cassandra, Cassandra, Apache ZooKeeper, ZooKeeper, Apache, the Apache 
feather logo, and the Apache project logo are trademarks of The Apache Software 
Foundation.
+</div>
+      </div></div>
+    </div>
+  </div>
+</div>
+<!-- footer end --> 
+
+<!-- JavaScripts -->
+<script src="/js/jquery-1.11.1.min.js"></script>
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+<script>
+    /************** FlexSlider *********************/
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+        animation: "fade",
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+    });
+</script>
+
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+    });
+</script>
+</body>
+</html>

http://git-wip-us.apache.org/repos/asf/eagle/blob/d6fed677/_site/docs/jmx-metric-monitoring.html
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+        <h2>Analyze Big Data Platforms For Security and Performance</h2>
+        <div class="social-buttons">
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+        <ul class="nav" id="adminnav">
+         
+        <li class="heading">Getting Started</li>
+        
+          <li class="sidenavli  "><a href="/docs/index.html" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">Introduction</a></li>
+        
+          <li class="sidenavli  "><a href="/docs/usecases.html" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">Use Cases</a></li>
+        
+          <li class="sidenavli  "><a href="/docs/terminology.html" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">Terminology</a></li>
+        
+          <li class="sidenavli  "><a href="/docs/ecosystem.html" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">Ecosystem</a></li>
+        
+          <li class="sidenavli  "><a href="/docs/community.html" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">Community</a></li>
+        
+          <li class="sidenavli  "><a href="/docs/FAQ.html" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">FAQ</a></li>
+        
+        <li class="divider"></li>
+       
+        <li class="heading">Documentations</li>
+        
+          <li class="sidenavli  "><a href="/docs/latest/" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">Latest version 
(v0.5.0)</a></li>
+        
+        <li class="divider"></li>
+       
+        <li class="heading">Download</li>
+        
+          <li class="sidenavli  "><a href="/docs/download-latest.html" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">Latest version 
(v0.5.0)</a></li>
+        
+          <li class="sidenavli  "><a href="/docs/download.html" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">Archived</a></li>
+        
+        <li class="divider"></li>
+       
+        <li class="heading">Supplement</li>
+        
+          <li class="sidenavli  "><a href="/docs/security.html" 
data-permalink="/docs/jmx-metric-monitoring.html" id="">Security</a></li>
+        
+        <li class="divider"></li>
+      
+        <li class="sidenavli">
+          <a href="mailto:d...@eagle.apache.org"; target="_blank">Need Help?</a>
+        </li>
+        </ul>
+      </div>
+      <div class="col-xs-6 col-sm-9 page-main-content" style="margin-left: 
-15px" id="loadcontent">
+        <h1 class="page-header" style="margin-top: 0px">JMX Metric 
Monitoring</h1>
+        <p>JMX metric for Apache Hadoop namenode url <a 
href="http://127.0.0.1:50070/jmx";>http://127.0.0.1:50070/jmx</a> can be 
monitored using Apache Eagle (called Eagle in the following). Follow below 
steps to enable this feature in Eagle.</p>
+
+<ol>
+  <li>Install Python script (To populate JMX metric values to Kafka<sup 
id="fnref:KAFKA"><a href="#fn:KAFKA" class="footnote">1</a></sup> topic 
periodically).</li>
+  <li>Deploy “hadoopjmx” Storm<sup id="fnref:STORM"><a href="#fn:STORM" 
class="footnote">2</a></sup> topology.</li>
+  <li>Create new site and policy in UI.</li>
+  <li>Validate policy alert.</li>
+</ol>
+
+<p><br /></p>
+
+<h3 id="prerequisite"><strong>Prerequisite</strong></h3>
+<ul>
+  <li>Complete the setup from <a href="/docs/deployment-env.html">Setup 
Environment</a></li>
+</ul>
+
+<p><br /></p>
+
+<h3 id="setup"><strong>Setup</strong></h3>
+<p>From Hortonworks sandbox just run below setup script to Install Pyton JMX 
script, Create Kafka topic, update Apache Hbase tables and deploy 
“hadoopjmx” Storm topology.</p>
+
+<pre><code>$ /usr/hdp/current/eagle/examples/hadoop-metric-sandbox-starter.sh
+$ /usr/hdp/current/eagle/examples/hadoop-metric-policy-create.sh  
+</code></pre>
+
+<p><br /></p>
+
+<h3 id="application-setup-in-ui"><strong>Application Setup in UI</strong></h3>
+<ol>
+  <li>Login to Eagle UI <a 
href="http://localhost:9099/eagle-service/";>http://localhost:9099/eagle-service/</a>
 using username and password as “admin” and “secret”</li>
+  <li>Click on “Admin” from top right and click “Management” 
button.</li>
+  <li>On Admin management page add “New Site” name 
“hadoopJmxMetricDataSource”, by clicking on “New Site” link.
+<img src="/images/docs/new-jmx-site.png" alt="add superuser" /></li>
+  <li>Save the changes.</li>
+  <li>On eagle home page you should see new tab called “METRIC”, beside 
“DAM”.</li>
+  <li>Click on “JmxMetricMonitor” under “METRIC”.</li>
+</ol>
+
+<p>You should see policy with name “safeModePolicy”.</p>
+
+<p><br /></p>
+
+<h3 id="demo"><strong>Demo</strong></h3>
+
+<ul>
+  <li>
+    <p>First make sure that Kafka topic “nn_jmx_metric_sandbox” is 
populated with JMX metric data periodically.(To make sure that python script is 
running)</p>
+
+    <pre><code>  $ /usr/hdp/2.2.4.2-2/kafka/bin/kafka-console-consumer.sh 
--zookeeper sandbox.hortonworks.com:2181 --topic nn_jmx_metric_sandbox
+</code></pre>
+  </li>
+  <li>
+    <p>Genrate Alert by producing alert triggering message into Kafka 
topic.</p>
+
+    <pre><code>  $ /usr/hdp/2.2.4.2-2/kafka/bin/kafka-console-producer.sh 
--broker-list sandbox.hortonworks.com:6667 --topic nn_jmx_metric_sandbox
+  $ {"host": "localhost", "timestamp": 1457033916718, "metric": 
"hadoop.namenode.fsnamesystemstate.fsstate", "component": "namenode", "site": 
"sandbox", "value": 1.0}
+</code></pre>
+  </li>
+</ul>
+
+<hr />
+
+<h4 id="footnotes"><em>Footnotes</em></h4>
+
+<div class="footnotes">
+  <ol>
+    <li id="fn:KAFKA">
+      <p><em>All mentions of “kafka” on this page represent Apache 
Kafka.</em> <a href="#fnref:KAFKA" class="reversefootnote">&#8617;</a></p>
+    </li>
+    <li id="fn:STORM">
+      <p><em>All mentions of “storm” on this page represent Apache 
Storm.</em> <a href="#fnref:STORM" class="reversefootnote">&#8617;</a></p>
+    </li>
+  </ol>
+</div>
+
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+Copyright © 2015 <a href="http://www.apache.org";>The Apache Software 
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+</div>
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+Apache Eagle, Eagle, Apache Hadoop, Hadoop, Apache HBase, HBase, Apache Hive, 
Hive, Apache Ambari, Ambari, Apache Spark, Spark, Apache Kafka, Kafka, Apache 
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