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From damian...@apache.org
Subject [02/10] kafka-site git commit: Update site for 0.11.0.1 release
Date Wed, 13 Sep 2017 12:25:19 GMT
http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/org/apache/kafka/streams/processor/StateStoreSupplier.html
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http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/org/apache/kafka/streams/processor/StreamPartitioner.html
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+<!-- Generated by javadoc (version 1.7.0_79) on Tue Sep 05 19:20:56 BST 2017 -->
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http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/org/apache/kafka/streams/processor/TaskId.html
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http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/org/apache/kafka/streams/processor/TimestampExtractor.html
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http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/org/apache/kafka/streams/processor/TopologyBuilder.AutoOffsetReset.html
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http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/org/apache/kafka/streams/processor/TopologyBuilder.TopicsInfo.html
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 <html lang="en">
 <head>
-<!-- Generated by javadoc (version 1.7.0_80) on Thu Jun 22 23:10:09 BST 2017 -->
-<title>org.apache.kafka.streams.state (kafka 0.11.0.0 API)</title>
-<meta name="date" content="2017-06-22">
+<!-- Generated by javadoc (version 1.7.0_79) on Tue Sep 05 19:20:59 BST 2017 -->
+<title>org.apache.kafka.streams.state (kafka 0.11.0.1 API)</title>
+<meta name="date" content="2017-09-05">
 <link rel="stylesheet" type="text/css" href="../../../../../stylesheet.css" title="Style">
 </head>
 <body>

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/org/apache/kafka/streams/state/package-summary.html
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diff --git a/0110/javadoc/org/apache/kafka/streams/state/package-summary.html b/0110/javadoc/org/apache/kafka/streams/state/package-summary.html
index d528df0..85b1b8a 100644
--- a/0110/javadoc/org/apache/kafka/streams/state/package-summary.html
+++ b/0110/javadoc/org/apache/kafka/streams/state/package-summary.html
@@ -2,15 +2,15 @@
 <!-- NewPage -->
 <html lang="en">
 <head>
-<!-- Generated by javadoc (version 1.7.0_80) on Thu Jun 22 23:10:09 BST 2017 -->
-<title>org.apache.kafka.streams.state (kafka 0.11.0.0 API)</title>
-<meta name="date" content="2017-06-22">
+<!-- Generated by javadoc (version 1.7.0_79) on Tue Sep 05 19:20:59 BST 2017 -->
+<title>org.apache.kafka.streams.state (kafka 0.11.0.1 API)</title>
+<meta name="date" content="2017-09-05">
 <link rel="stylesheet" type="text/css" href="../../../../../stylesheet.css" title="Style">
 </head>
 <body>
 <script type="text/javascript"><!--
     if (location.href.indexOf('is-external=true') == -1) {
-        parent.document.title="org.apache.kafka.streams.state (kafka 0.11.0.0 API)";
+        parent.document.title="org.apache.kafka.streams.state (kafka 0.11.0.1 API)";
     }
 //-->
 </script>

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/org/apache/kafka/streams/state/package-tree.html
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diff --git a/0110/javadoc/org/apache/kafka/streams/state/package-tree.html b/0110/javadoc/org/apache/kafka/streams/state/package-tree.html
index 8d5080c..42bb22e 100644
--- a/0110/javadoc/org/apache/kafka/streams/state/package-tree.html
+++ b/0110/javadoc/org/apache/kafka/streams/state/package-tree.html
@@ -2,15 +2,15 @@
 <!-- NewPage -->
 <html lang="en">
 <head>
-<!-- Generated by javadoc (version 1.7.0_80) on Thu Jun 22 23:10:09 BST 2017 -->
-<title>org.apache.kafka.streams.state Class Hierarchy (kafka 0.11.0.0 API)</title>
-<meta name="date" content="2017-06-22">
+<!-- Generated by javadoc (version 1.7.0_79) on Tue Sep 05 19:20:59 BST 2017 -->
+<title>org.apache.kafka.streams.state Class Hierarchy (kafka 0.11.0.1 API)</title>
+<meta name="date" content="2017-09-05">
 <link rel="stylesheet" type="text/css" href="../../../../../stylesheet.css" title="Style">
 </head>
 <body>
 <script type="text/javascript"><!--
     if (location.href.indexOf('is-external=true') == -1) {
-        parent.document.title="org.apache.kafka.streams.state Class Hierarchy (kafka 0.11.0.0 API)";
+        parent.document.title="org.apache.kafka.streams.state Class Hierarchy (kafka 0.11.0.1 API)";
     }
 //-->
 </script>

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index ff15719..2135095 100644
--- a/0110/javadoc/overview-frame.html
+++ b/0110/javadoc/overview-frame.html
@@ -2,9 +2,9 @@
 <!-- NewPage -->
 <html lang="en">
 <head>
-<!-- Generated by javadoc (version 1.7.0_80) on Thu Jun 22 23:10:09 BST 2017 -->
-<title>Overview List (kafka 0.11.0.0 API)</title>
-<meta name="date" content="2017-06-22">
+<!-- Generated by javadoc (version 1.7.0_79) on Tue Sep 05 19:20:59 BST 2017 -->
+<title>Overview List (kafka 0.11.0.1 API)</title>
+<meta name="date" content="2017-09-05">
 <link rel="stylesheet" type="text/css" href="stylesheet.css" title="Style">
 </head>
 <body>

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/overview-summary.html
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index 3d94626..2ea3670 100644
--- a/0110/javadoc/overview-summary.html
+++ b/0110/javadoc/overview-summary.html
@@ -2,15 +2,15 @@
 <!-- NewPage -->
 <html lang="en">
 <head>
-<!-- Generated by javadoc (version 1.7.0_80) on Thu Jun 22 23:10:09 BST 2017 -->
-<title>Overview (kafka 0.11.0.0 API)</title>
-<meta name="date" content="2017-06-22">
+<!-- Generated by javadoc (version 1.7.0_79) on Tue Sep 05 19:20:59 BST 2017 -->
+<title>Overview (kafka 0.11.0.1 API)</title>
+<meta name="date" content="2017-09-05">
 <link rel="stylesheet" type="text/css" href="stylesheet.css" title="Style">
 </head>
 <body>
 <script type="text/javascript"><!--
     if (location.href.indexOf('is-external=true') == -1) {
-        parent.document.title="Overview (kafka 0.11.0.0 API)";
+        parent.document.title="Overview (kafka 0.11.0.1 API)";
     }
 //-->
 </script>
@@ -62,7 +62,7 @@
 </a></div>
 <!-- ========= END OF TOP NAVBAR ========= -->
 <div class="header">
-<h1 class="title">kafka 0.11.0.0 API</h1>
+<h1 class="title">kafka 0.11.0.1 API</h1>
 </div>
 <div class="contentContainer">
 <table class="overviewSummary" border="0" cellpadding="3" cellspacing="0" summary="Packages table, listing packages, and an explanation">

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/overview-tree.html
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index 8376df5..e3414dd 100644
--- a/0110/javadoc/overview-tree.html
+++ b/0110/javadoc/overview-tree.html
@@ -2,15 +2,15 @@
 <!-- NewPage -->
 <html lang="en">
 <head>
-<!-- Generated by javadoc (version 1.7.0_80) on Thu Jun 22 23:10:09 BST 2017 -->
-<title>Class Hierarchy (kafka 0.11.0.0 API)</title>
-<meta name="date" content="2017-06-22">
+<!-- Generated by javadoc (version 1.7.0_79) on Tue Sep 05 19:20:59 BST 2017 -->
+<title>Class Hierarchy (kafka 0.11.0.1 API)</title>
+<meta name="date" content="2017-09-05">
 <link rel="stylesheet" type="text/css" href="stylesheet.css" title="Style">
 </head>
 <body>
 <script type="text/javascript"><!--
     if (location.href.indexOf('is-external=true') == -1) {
-        parent.document.title="Class Hierarchy (kafka 0.11.0.0 API)";
+        parent.document.title="Class Hierarchy (kafka 0.11.0.1 API)";
     }
 //-->
 </script>

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/javadoc/serialized-form.html
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index d265f33..67813a0 100644
--- a/0110/javadoc/serialized-form.html
+++ b/0110/javadoc/serialized-form.html
@@ -2,15 +2,15 @@
 <!-- NewPage -->
 <html lang="en">
 <head>
-<!-- Generated by javadoc (version 1.7.0_80) on Thu Jun 22 23:10:09 BST 2017 -->
-<title>Serialized Form (kafka 0.11.0.0 API)</title>
-<meta name="date" content="2017-06-22">
+<!-- Generated by javadoc (version 1.7.0_79) on Tue Sep 05 19:20:59 BST 2017 -->
+<title>Serialized Form (kafka 0.11.0.1 API)</title>
+<meta name="date" content="2017-09-05">
 <link rel="stylesheet" type="text/css" href="stylesheet.css" title="Style">
 </head>
 <body>
 <script type="text/javascript"><!--
     if (location.href.indexOf('is-external=true') == -1) {
-        parent.document.title="Serialized Form (kafka 0.11.0.0 API)";
+        parent.document.title="Serialized Form (kafka 0.11.0.1 API)";
     }
 //-->
 </script>

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/js/templateData.js
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diff --git a/0110/js/templateData.js b/0110/js/templateData.js
index 2f32444..5356e4d 100644
--- a/0110/js/templateData.js
+++ b/0110/js/templateData.js
@@ -18,5 +18,7 @@ limitations under the License.
 // Define variables for doc templates
 var context={
     "version": "0110",
-    "dotVersion": "0.11.0"
-};
\ No newline at end of file
+    "dotVersion": "0.11.0",
+    "fullDotVersion": "0.11.0.1",
+    "scalaVersion": "2.11"
+};

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/ops.html
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diff --git a/0110/ops.html b/0110/ops.html
index 85a6e10..32d4bbd 100644
--- a/0110/ops.html
+++ b/0110/ops.html
@@ -24,7 +24,7 @@
 
   <h4><a id="basic_ops_add_topic" href="#basic_ops_add_topic">Adding and removing topics</a></h4>
 
-  You have the option of either adding topics manually or having them be created automatically when data is first published to a non-existent topic. If topics are auto-created then you may want to tune the default <a href="#topic-config">topic configurations</a> used for auto-created topics.
+  You have the option of either adding topics manually or having them be created automatically when data is first published to a non-existent topic. If topics are auto-created then you may want to tune the default <a href="#topicconfigs">topic configurations</a> used for auto-created topics.
   <p>
   Topics are added and modified using the topic tool:
   <pre class="brush: bash;">
@@ -37,7 +37,7 @@
   <p>
   Each sharded partition log is placed into its own folder under the Kafka log directory. The name of such folders consists of the topic name, appended by a dash (-) and the partition id. Since a typical folder name can not be over 255 characters long, there will be a limitation on the length of topic names. We assume the number of partitions will not ever be above 100,000. Therefore, topic names cannot be longer than 249 characters. This leaves just enough room in the folder name for a dash and a potentially 5 digit long partition id.
   <p>
-  The configurations added on the command line override the default settings the server has for things like the length of time data should be retained. The complete set of per-topic configurations is documented <a href="#topic-config">here</a>.
+  The configurations added on the command line override the default settings the server has for things like the length of time data should be retained. The complete set of per-topic configurations is documented <a href="#topicconfigs">here</a>.
 
   <h4><a id="basic_ops_modify_topic" href="#basic_ops_modify_topic">Modifying topics</a></h4>
 
@@ -687,7 +687,7 @@
 
   <h3><a id="monitoring" href="#monitoring">6.6 Monitoring</a></h3>
 
-  Kafka uses Yammer Metrics for metrics reporting in both the server and the client. This can be configured to report stats using pluggable stats reporters to hook up to your monitoring system.
+  Kafka uses Yammer Metrics for metrics reporting in the server and Scala clients. The Java clients use Kafka Metrics, a built-in metrics registry that minimizes transitive dependencies pulled into client applications. Both expose metrics via JMX and can be configured to report stats using pluggable stats reporters to hook up to your monitoring system.
   <p>
   The easiest way to see the available metrics is to fire up jconsole and point it at a running kafka client or server; this will allow browsing all metrics with JMX.
   <p>
@@ -1229,7 +1229,19 @@
 
   <h4><a id="kafka_streams_monitoring" href="#kafka_streams_monitoring">Streams Monitoring</a></h4>
 
-  A Kafka Streams instance contains all the producer and consumer metrics as well as additional metrics specific to streams. By default Kafka Streams has metrics with two recording levels: debug and info. The debug level records all metrics, while the info level records only the thread-level metrics.  Use the following configuration option to specify which metrics you want collected:
+  A Kafka Streams instance contains all the producer and consumer metrics as well as additional metrics specific to streams.
+  By default Kafka Streams has metrics with two recording levels: debug and info. The debug level records all metrics, while
+  the info level records only the thread-level metrics.
+
+  <p>
+    Note that the metrics have a 3-layer hierarchy. At the top level there are per-thread metrics. Each thread has tasks, with their
+    own metrics. Each task has a number of processor nodes, with their own metrics. Each task also has a number of state stores
+    and record caches, all with their own metrics.
+  </p>
+  
+  Use the following configuration option to specify which metrics
+  you want collected:
+
 <pre>metrics.recording.level="info"</pre>
 
 <h5><a id="kafka_streams_thread_monitoring" href="#kafka_streams_thread_monitoring">Thread Metrics</a></h5>
@@ -1241,30 +1253,80 @@ All the following metrics have a recording level of ``info``:
         <th>Description</th>
         <th>Mbean name</th>
       </tr>
-      <tr>
-        <td>[commit | poll | process | punctuate]-latency-[avg | max]</td>
-        <td>The [average | maximum] execution time in ms, for the respective operation, across all running tasks of this thread.</td>
-        <td>kafka.streams:type=stream-metrics,thread.client-id=([-.\w]+)</td>
-      </tr>
-      <tr>
-        <td>[commit | poll | process | punctuate]-rate</td>
-        <td>The average number of respective operations per second across all tasks.</td>
-        <td>kafka.streams:type=stream-metrics,thread.client-id=([-.\w]+)</td>
+       <tr>
+        <td>commit-latency-avg</td>
+        <td>The average execution time in ms for committing, across all running tasks of this thread.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+        <tr>
+        <td>commit-latency-max</td>
+        <td>The maximum execution time in ms for committing across all running tasks of this thread.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+       <tr>
+        <td>poll-latency-avg</td>
+        <td>The average execution time in ms for polling, across all running tasks of this thread.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+        <tr>
+        <td>poll-latency-max</td>
+        <td>The maximum execution time in ms for polling across all running tasks of this thread.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+       <tr>
+        <td>process-latency-avg</td>
+        <td>The average execution time in ms for processing, across all running tasks of this thread.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+       <tr>
+        <td>process-latency-max</td>
+        <td>The maximum execution time in ms for processing across all running tasks of this thread.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+       <tr>
+        <td>punctuate-latency-avg</td>
+        <td>The average execution time in ms for punctuating, across all running tasks of this thread.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+       <tr>
+        <td>punctuate-latency-max</td>
+        <td>The maximum execution time in ms for punctuating across all running tasks of this thread.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+       <tr>
+        <td>commit-rate</td>
+        <td>The average number of commits per second across all tasks.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+       <tr>
+        <td>poll-rate</td>
+        <td>The average number of polls per second across all tasks.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+       <tr>
+        <td>process-rate</td>
+        <td>The average number of process calls per second across all tasks.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
+       </tr>
+       <tr>
+        <td>punctuate-rate</td>
+        <td>The average number of punctuates per second across all tasks.</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
       </tr>
       <tr>
         <td>task-created-rate</td>
         <td>The average number of newly created tasks per second.</td>
-        <td>kafka.streams:type=stream-metrics,thread.client-id=([-.\w]+)</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
       </tr>
       <tr>
         <td>task-closed-rate</td>
         <td>The average number of tasks closed per second.</td>
-        <td>kafka.streams:type=stream-metrics,thread.client-id=([-.\w]+)</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
       </tr>
       <tr>
         <td>skipped-records-rate</td>
         <td>The average number of skipped records per second. </td>
-        <td>kafka.streams:type=stream-metrics,thread.client-id=([-.\w]+)</td>
+        <td>kafka.streams:type=stream-metrics,client-id=([-.\w]+)</td>
       </tr>
  </tbody>
 </table>
@@ -1279,14 +1341,19 @@ All the following metrics have a recording level of ``debug``:
         <th>Mbean name</th>
       </tr>
       <tr>
-        <td>commit-latency-[avg | max]</td>
-        <td>The [average | maximum] commit time in ns for this task. </td>
-        <td>kafka.streams:type=stream-task-metrics,streams-task-id=([-.\w]+)</td>
+        <td>commit-latency-avg</td>
+        <td>The average commit time in ns for this task. </td>
+        <td>kafka.streams:type=stream-task-metrics,client-id=([-.\w]+),task-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>commit-latency-max</td>
+        <td>The maximum commit time in ns for this task. </td>
+        <td>kafka.streams:type=stream-task-metrics,client-id=([-.\w]+),task-id=([-.\w]+)</td>
       </tr>
       <tr>
         <td>commit-rate</td>
         <td>The average number of commit calls per second. </td>
-        <td>kafka.streams:type=stream-task-metrics,streams-task-id=([-.\w]+)</td>
+        <td>kafka.streams:type=stream-task-metrics,client-id=([-.\w]+),task-id=([-.\w]+)</td>
       </tr>
  </tbody>
 </table>
@@ -1301,19 +1368,69 @@ All the following metrics have a recording level of ``debug``:
         <th>Mbean name</th>
       </tr>
       <tr>
-        <td>[process | punctuate | create | destroy]-latency-[avg | max]</td>
-        <td>The [average | maximum] execution time in ns, for the respective operation. </td>
-        <td>kafka.streams:type=stream-processor-node-metrics, processor-node-id=([-.\w]+)</td>
+        <td>process-latency-avg</td>
+        <td>The average process execution time in ns. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>process-latency-max</td>
+        <td>The maximum process execution time in ns. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>punctuate-latency-avg</td>
+        <td>The average punctuate execution time in ns. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>punctuate-latency-max</td>
+        <td>The maximum punctuate execution time in ns. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
       </tr>
       <tr>
-        <td>[process | punctuate | create | destroy]-rate</td>
-        <td>The average number of respective operations per second. </td>
-        <td>kafka.streams:type=stream-processor-node-metrics, processor-node-id=([-.\w]+)</td>
+        <td>create-latency-avg</td>
+        <td>The average create execution time in ns. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>create-latency-max</td>
+        <td>The maximum create execution time in ns. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>destroy-latency-avg</td>
+        <td>The average destroy execution time in ns. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>destroy-latency-max</td>
+        <td>The maximum destroy execution time in ns. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>process-rate</td>
+        <td>The average number of process operations per second. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>punctuate-rate</td>
+        <td>The average number of punctuate operations per second. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>create-rate</td>
+        <td>The average number of create operations per second. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>destroy-rate</td>
+        <td>The average number of destroy operations per second. </td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
       </tr>
       <tr>
         <td>forward-rate</td>
         <td>The average rate of records being forwarded downstream, from source nodes only, per second. </td>
-        <td>kafka.streams:type=stream-processor-node-metrics, processor-node-id=([-.\w]+)</td>
+        <td>kafka.streams:type=stream-processor-node-metrics,client-id=([-.\w]+),task-id=([-.\w]+),processor-node-id=([-.\w]+)</td>
       </tr>
  </tbody>
  </table>
@@ -1329,16 +1446,140 @@ All the following metrics have a recording level of ``debug``:
         <th>Mbean name</th>
       </tr>
       <tr>
-        <td>[put | put-if-absent | get | delete | put-all | all | range | flush | restore]-latency-[avg | max]</td>
-        <td>The average execution time in ns, for the respective operation. </td>
-        <td>kafka.streams:type=stream-[store-type]-metrics</td>
+        <td>put-latency-avg</td>
+        <td>The average put execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
       </tr>
-        <tr>
-        <td>[put | put-if-absent | get | delete | put-all | all | range | flush | restore]-rate</td>
-        <td>The average rate of respective operations per second for this store.</td>
-        <td>kafka.streams:type=stream-[store-type]-metrics</td>
+      <tr>
+        <td>put-latency-max</td>
+        <td>The maximum put execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>put-if-absent-latency-avg</td>
+        <td>The average put-if-absent execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>put-if-absent-latency-max</td>
+        <td>The maximum put-if-absent execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>get-latency-avg</td>
+        <td>The average get execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>get-latency-max</td>
+        <td>The maximum get execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>delete-latency-avg</td>
+        <td>The average delete execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>delete-latency-max</td>
+        <td>The maximum delete execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>put-all-latency-avg</td>
+        <td>The average put-all execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>put-all-latency-max</td>
+        <td>The maximum put-all execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>all-latency-avg</td>
+        <td>The average all operation execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>all-latency-max</td>
+        <td>The maximum all operation execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>range-latency-avg</td>
+        <td>The average range execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>range-latency-max</td>
+        <td>The maximum range execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+       <tr>
+        <td>flush-latency-avg</td>
+        <td>The average flush execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>flush-latency-max</td>
+        <td>The maximum flush execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>restore-latency-avg</td>
+        <td>The average restore execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>restore-latency-max</td>
+        <td>The maximum restore execution time in ns. </td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>put-rate</td>
+        <td>The average put rate for this store.</td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>put-if-absent-rate</td>
+        <td>The average put-if-absent rate for this store.</td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>get-rate</td>
+        <td>The average get rate for this store.</td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>delete-rate</td>
+        <td>The average delete rate for this store.</td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>put-all-rate</td>
+        <td>The average put-all rate for this store.</td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>all-rate</td>
+        <td>The average all operation rate for this store.</td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>range-rate</td>
+        <td>The average range rate for this store.</td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>flush-rate</td>
+        <td>The average flush rate for this store.</td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>restore-rate</td>
+        <td>The average restore rate for this store.</td>
+        <td>kafka.streams:type=stream-[store-type]-state-metrics,client-id=([-.\w]+),task-id=([-.\w]+),[store-type]-state-id=([-.\w]+)</td>
       </tr>
-      
     </tbody>
  </table>
 
@@ -1353,9 +1594,19 @@ All the following metrics have a recording level of ``debug``:
         <th>Mbean name</th>
       </tr>
       <tr>
-        <td>hitRatio-[avg | min | max]</td>
-        <td>The cache hit ratio defined as the ratio of cache read hits over the total cache read requests. </td>
-        <td>kafka.streams:type=stream-record-cache-metrics, record-cache-id=([-.\w]+)</td>
+        <td>hitRatio-avg</td>
+        <td>The average cache hit ratio defined as the ratio of cache read hits over the total cache read requests. </td>
+        <td>kafka.streams:type=stream-record-cache-metrics,client-id=([-.\w]+),task-id=([-.\w]+),record-cache-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>hitRatio-min</td>
+        <td>The mininum cache hit ratio. </td>
+        <td>kafka.streams:type=stream-record-cache-metrics,client-id=([-.\w]+),task-id=([-.\w]+),record-cache-id=([-.\w]+)</td>
+      </tr>
+      <tr>
+        <td>hitRatio-max</td>
+        <td>The maximum cache hit ratio. </td>
+        <td>kafka.streams:type=stream-record-cache-metrics,client-id=([-.\w]+),task-id=([-.\w]+),record-cache-id=([-.\w]+)</td>
       </tr>
     </tbody>
  </table>

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/quickstart.html
----------------------------------------------------------------------
diff --git a/0110/quickstart.html b/0110/quickstart.html
index 6509f75..c50df29 100644
--- a/0110/quickstart.html
+++ b/0110/quickstart.html
@@ -25,11 +25,11 @@ Since Kafka console scripts are different for Unix-based and Windows platforms,
 
 <h4><a id="quickstart_download" href="#quickstart_download">Step 1: Download the code</a></h4>
 
-<a href="https://www.apache.org/dyn/closer.cgi?path=/kafka/0.10.2.0/kafka_2.11-0.10.2.0.tgz" title="Kafka downloads">Download</a> the 0.10.2.0 release and un-tar it.
+<a href="https://www.apache.org/dyn/closer.cgi?path=/kafka/{{fullDotVersion}}/kafka_2.11-{{fullDotVersion}}.tgz" title="Kafka downloads">Download</a> the {{fullDotVersion}} release and un-tar it.
 
 <pre class="brush: bash;">
-&gt; tar -xzf kafka_2.11-0.10.2.0.tgz
-&gt; cd kafka_2.11-0.10.2.0
+&gt; tar -xzf kafka_2.11-{{fullDotVersion}}.tgz
+&gt; cd kafka_2.11-{{fullDotVersion}}
 </pre>
 
 <h4><a id="quickstart_startserver" href="#quickstart_startserver">Step 2: Start the server</a></h4>
@@ -187,7 +187,7 @@ my test message 2
 On Windows use:
 <pre class="brush: bash;">
 &gt; wmic process get processid,caption,commandline | find "java.exe" | find "server-1.properties"
-java.exe    java  -Xmx1G -Xms1G -server -XX:+UseG1GC ... build\libs\kafka_2.11-0.10.2.0.jar"  kafka.Kafka config\server-1.properties    644
+java.exe    java  -Xmx1G -Xms1G -server -XX:+UseG1GC ... build\libs\kafka_2.11-{{fullDotVersion}}.jar"  kafka.Kafka config\server-1.properties    644
 &gt; taskkill /pid 644 /f
 </pre>
 
@@ -280,169 +280,14 @@ data in the topic (or use custom consumer code to process it):
 <h4><a id="quickstart_kafkastreams" href="#quickstart_kafkastreams">Step 8: Use Kafka Streams to process data</a></h4>
 
 <p>
-Kafka Streams is a client library of Kafka for real-time stream processing and analyzing data stored in Kafka brokers.
-This quickstart example will demonstrate how to run a streaming application coded in this library. Here is the gist
-of the <code><a href="https://github.com/apache/kafka/blob/{{dotVersion}}/streams/examples/src/main/java/org/apache/kafka/streams/examples/wordcount/WordCountDemo.java">WordCountDemo</a></code> example code (converted to use Java 8 lambda expressions for easy reading).
-</p>
-<pre class="brush: bash;">
-// Serializers/deserializers (serde) for String and Long types
-final Serde&lt;String&gt; stringSerde = Serdes.String();
-final Serde&lt;Long&gt; longSerde = Serdes.Long();
-
-// Construct a `KStream` from the input topic ""streams-file-input", where message values
-// represent lines of text (for the sake of this example, we ignore whatever may be stored
-// in the message keys).
-KStream&lt;String, String&gt; textLines = builder.stream(stringSerde, stringSerde, "streams-file-input");
-
-KTable&lt;String, Long&gt; wordCounts = textLines
-    // Split each text line, by whitespace, into words.
-    .flatMapValues(value -> Arrays.asList(value.toLowerCase().split("\\W+")))
-
-    // Group the text words as message keys
-    .groupBy((key, value) -> value)
-
-    // Count the occurrences of each word (message key).
-    .count("Counts")
-
-// Store the running counts as a changelog stream to the output topic.
-wordCounts.to(stringSerde, longSerde, "streams-wordcount-output");
-</pre>
-
-<p>
-It implements the WordCount
-algorithm, which computes a word occurrence histogram from the input text. However, unlike other WordCount examples
-you might have seen before that operate on bounded data, the WordCount demo application behaves slightly differently because it is
-designed to operate on an <b>infinite, unbounded stream</b> of data. Similar to the bounded variant, it is a stateful algorithm that
-tracks and updates the counts of words. However, since it must assume potentially
-unbounded input data, it will periodically output its current state and results while continuing to process more data
-because it cannot know when it has processed "all" the input data.
-</p>
-<p>
-As the first step, we will prepare input data to a Kafka topic, which will subsequently be processed by a Kafka Streams application.
-</p>
-
-<!--
-<pre>
-&gt; <b>./bin/kafka-topics --create \</b>
-            <b>--zookeeper localhost:2181 \</b>
-            <b>--replication-factor 1 \</b>
-            <b>--partitions 1 \</b>
-            <b>--topic streams-file-input</b>
-
-</pre>
-
--->
-
-<pre class="brush: bash;">
-&gt; echo -e "all streams lead to kafka\nhello kafka streams\njoin kafka summit" > file-input.txt
-</pre>
-Or on Windows:
-<pre class="brush: bash;">
-&gt; echo all streams lead to kafka> file-input.txt
-&gt; echo hello kafka streams>> file-input.txt
-&gt; echo|set /p=join kafka summit>> file-input.txt
-</pre>
-
-<p>
-Next, we send this input data to the input topic named <b>streams-file-input</b> using the console producer,
-which reads the data from STDIN line-by-line, and publishes each line as a separate Kafka message with null key and value encoded a string to the topic (in practice,
-stream data will likely be flowing continuously into Kafka where the application will be up and running):
-</p>
-
-<pre class="brush: bash;">
-&gt; bin/kafka-topics.sh --create \
-    --zookeeper localhost:2181 \
-    --replication-factor 1 \
-    --partitions 1 \
-    --topic streams-file-input
-</pre>
-
-
-<pre class="brush: bash;">
-&gt; bin/kafka-console-producer.sh --broker-list localhost:9092 --topic streams-file-input < file-input.txt
-</pre>
-
-<p>
-We can now run the WordCount demo application to process the input data:
-</p>
-
-<pre class="brush: bash;">
-&gt; bin/kafka-run-class.sh org.apache.kafka.streams.examples.wordcount.WordCountDemo
-</pre>
-
-<p>
-The demo application will read from the input topic <b>streams-file-input</b>, perform the computations of the WordCount algorithm on each of the read messages,
-and continuously write its current results to the output topic <b>streams-wordcount-output</b>.
-Hence there won't be any STDOUT output except log entries as the results are written back into in Kafka.
-The demo will run for a few seconds and then, unlike typical stream processing applications, terminate automatically.
-</p>
-<p>
-We can now inspect the output of the WordCount demo application by reading from its output topic:
-</p>
-
-<pre class="brush: bash;">
-&gt; bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 \
-    --topic streams-wordcount-output \
-    --from-beginning \
-    --formatter kafka.tools.DefaultMessageFormatter \
-    --property print.key=true \
-    --property print.value=true \
-    --property key.deserializer=org.apache.kafka.common.serialization.StringDeserializer \
-    --property value.deserializer=org.apache.kafka.common.serialization.LongDeserializer
-</pre>
-
-<p>
-with the following output data being printed to the console:
-</p>
-
-<pre class="brush: bash;">
-all     1
-lead    1
-to      1
-hello   1
-streams 2
-join    1
-kafka   3
-summit  1
-</pre>
-
-<p>
-Here, the first column is the Kafka message key in <code>java.lang.String</code> format, and the second column is the message value in <code>java.lang.Long</code> format.
-Note that the output is actually a continuous stream of updates, where each data record (i.e. each line in the original output above) is
-an updated count of a single word, aka record key such as "kafka". For multiple records with the same key, each later record is an update of the previous one.
-</p>
-
-<p>
-The two diagrams below illustrate what is essentially happening behind the scenes.
-The first column shows the evolution of the current state of the <code>KTable&lt;String, Long&gt;</code> that is counting word occurrences for <code>count</code>.
-The second column shows the change records that result from state updates to the KTable and that are being sent to the output Kafka topic <b>streams-wordcount-output</b>.
-</p>
-
-<img src="/{{version}}/images/streams-table-updates-02.png" style="float: right; width: 25%;">
-<img src="/{{version}}/images/streams-table-updates-01.png" style="float: right; width: 25%;">
-
-<p>
-First the text line “all streams lead to kafka” is being processed.
-The <code>KTable</code> is being built up as each new word results in a new table entry (highlighted with a green background), and a corresponding change record is sent to the downstream <code>KStream</code>.
-</p>
-<p>
-When the second text line “hello kafka streams” is processed, we observe, for the first time, that existing entries in the <code>KTable</code> are being updated (here: for the words “kafka” and for “streams”). And again, change records are being sent to the output topic.
-</p>
-<p>
-And so on (we skip the illustration of how the third line is being processed). This explains why the output topic has the contents we showed above, because it contains the full record of changes.
-</p>
-
-<p>
-Looking beyond the scope of this concrete example, what Kafka Streams is doing here is to leverage the duality between a table and a changelog stream (here: table = the KTable, changelog stream = the downstream KStream): you can publish every change of the table to a stream, and if you consume the entire changelog stream from beginning to end, you can reconstruct the contents of the table.
-</p>
-
-<p>
-Now you can write more input messages to the <b>streams-file-input</b> topic and observe additional messages added
-to <b>streams-wordcount-output</b> topic, reflecting updated word counts (e.g., using the console producer and the
-console consumer, as described above).
+  Kafka Streams is a client library for building mission-critical real-time applications and microservices,
+  where the input and/or output data is stored in Kafka clusters. Kafka Streams combines the simplicity of
+  writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's
+  server-side cluster technology to make these applications highly scalable, elastic, fault-tolerant, distributed,
+  and much more. This <a href="/{{version}}/documentation/streams/quickstart">quickstart example</a> will demonstrate how
+  to run a streaming application coded in this library. 
 </p>
 
-<p>You can stop the console consumer via <b>Ctrl-C</b>.</p>
 
 </script>
 

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/security.html
----------------------------------------------------------------------
diff --git a/0110/security.html b/0110/security.html
index 5e2b202..dab00dd 100644
--- a/0110/security.html
+++ b/0110/security.html
@@ -40,7 +40,7 @@
 
     <ol>
         <li><h4><a id="security_ssl_key" href="#security_ssl_key">Generate SSL key and certificate for each Kafka broker</a></h4>
-            The first step of deploying HTTPS is to generate the key and the certificate for each machine in the cluster. You can use Java's keytool utility to accomplish this task.
+            The first step of deploying one or more brokers with the SSL support is to generate the key and the certificate for each machine in the cluster. You can use Java's keytool utility to accomplish this task.
             We will generate the key into a temporary keystore initially so that we can export and sign it later with CA.
             <pre class="brush: bash;">
             keytool -keystore server.keystore.jks -alias localhost -validity {validity} -genkey -keyalg RSA</pre>

http://git-wip-us.apache.org/repos/asf/kafka-site/blob/a1278d06/0110/streams/architecture.html
----------------------------------------------------------------------
diff --git a/0110/streams/architecture.html b/0110/streams/architecture.html
index f0def6a..0dbb1dc 100644
--- a/0110/streams/architecture.html
+++ b/0110/streams/architecture.html
@@ -126,12 +126,12 @@
         Note that the cost of task (re)initialization typically depends primarily on the time for restoring the state by replaying the state stores' associated changelog topics.
         To minimize this restoration time, users can configure their applications to have <b>standby replicas</b> of local states (i.e. fully replicated copies of the state).
         When a task migration happens, Kafka Streams then attempts to assign a task to an application instance where such a standby replica already exists in order to minimize
-        the task (re)initialization cost. See <code>num.standby.replicas</code> in the <a href="/{{version}}/documentation/#streamsconfigs"><b>Kafka Streams Configs</b></a> Section.
+        the task (re)initialization cost. See <code>num.standby.replicas</code> in the <a href="/{{version}}/documentation/#streamsconfigs"><b>Kafka Streams Configs</b></a> section.
     </p>
 
     <div class="pagination">
         <a href="/{{version}}/documentation/streams/core-concepts" class="pagination__btn pagination__btn__prev">Previous</a>
-        <a href="/{{version}}/documentation/streams/developer-guide" class="pagination__btn pagination__btn__next">Next</a>
+        <a href="/{{version}}/documentation/streams/upgrade-guide" class="pagination__btn pagination__btn__next">Next</a>
     </div>
 </script>
 
@@ -143,7 +143,7 @@
         <!--#include virtual="../../includes/_docs_banner.htm" -->
         <ul class="breadcrumbs">
             <li><a href="/documentation">Documentation</a></li>
-            <li><a href="/documentation/streams">Streams</a></li>
+            <li><a href="/documentation/streams">Kafka Streams API</a></li>
         </ul>
         <div class="p-content"></div>
     </div>


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