Port changes for MM2 docs (KAFKA-8930) to 2.6 docs
diff --git a/26/ops.html b/26/ops.html
index e835341..eb64156 100644
--- a/26/ops.html
+++ b/26/ops.html
@@ -85,32 +85,18 @@
The rack awareness feature spreads replicas of the same partition across different racks. This extends the guarantees Kafka provides for broker-failure to cover rack-failure, limiting the risk of data loss should all the brokers on a rack fail at once. The feature can also be applied to other broker groupings such as availability zones in EC2.
<p></p>
You can specify that a broker belongs to a particular rack by adding a property to the broker config:
- <pre class="language-text"> broker.rack=my-rack-id</code></pre>
+ <pre class="language-text"><code class="language-text"> broker.rack=my-rack-id</code></pre>
When a topic is <a href="#basic_ops_add_topic">created</a>, <a href="#basic_ops_modify_topic">modified</a> or replicas are <a href="#basic_ops_cluster_expansion">redistributed</a>, the rack constraint will be honoured, ensuring replicas span as many racks as they can (a partition will span min(#racks, replication-factor) different racks).
<p></p>
The algorithm used to assign replicas to brokers ensures that the number of leaders per broker will be constant, regardless of how brokers are distributed across racks. This ensures balanced throughput.
<p></p>
However if racks are assigned different numbers of brokers, the assignment of replicas will not be even. Racks with fewer brokers will get more replicas, meaning they will use more storage and put more resources into replication. Hence it is sensible to configure an equal number of brokers per rack.
- <h4 class="anchor-heading"><a id="basic_ops_mirror_maker" class="anchor-link"></a><a href="#basic_ops_mirror_maker">Mirroring data between clusters</a></h4>
+ <h4 class="anchor-heading"><a id="basic_ops_mirror_maker" class="anchor-link"></a><a href="#basic_ops_mirror_maker">Mirroring data between clusters & Geo-replication</a></h4>
- We refer to the process of replicating data <i>between</i> Kafka clusters "mirroring" to avoid confusion with the replication that happens amongst the nodes in a single cluster. Kafka comes with a tool for mirroring data between Kafka clusters. The tool consumes from a source cluster and produces to a destination cluster.
-
- A common use case for this kind of mirroring is to provide a replica in another datacenter. This scenario will be discussed in more detail in the next section.
<p>
- You can run many such mirroring processes to increase throughput and for fault-tolerance (if one process dies, the others will take overs the additional load).
- <p>
- Data will be read from topics in the source cluster and written to a topic with the same name in the destination cluster. In fact the mirror maker is little more than a Kafka consumer and producer hooked together.
- <p>
- The source and destination clusters are completely independent entities: they can have different numbers of partitions and the offsets will not be the same. For this reason the mirror cluster is not really intended as a fault-tolerance mechanism (as the consumer position will be different); for that we recommend using normal in-cluster replication. The mirror maker process will, however, retain and use the message key for partitioning so order is preserved on a per-key basis.
- <p>
- Here is an example showing how to mirror a single topic (named <i>my-topic</i>) from an input cluster:
- <pre class="line-numbers"><code class="language-bash"> > bin/kafka-mirror-maker.sh
- --consumer.config consumer.properties
- --producer.config producer.properties --whitelist my-topic</code></pre>
- Note that we specify the list of topics with the <code>--whitelist</code> option. This option allows any regular expression using <a href="http://docs.oracle.com/javase/7/docs/api/java/util/regex/Pattern.html">Java-style regular expressions</a>. So you could mirror two topics named <i>A</i> and <i>B</i> using <code>--whitelist 'A|B'</code>. Or you could mirror <i>all</i> topics using <code>--whitelist '*'</code>. Make sure to quote any regular expression to ensure the shell doesn't try to expand it as a file path. For convenience we allow the use of ',' instead of '|' to specify a list of topics.
-
- Combining mirroring with the configuration <code>auto.create.topics.enable=true</code> makes it possible to have a replica cluster that will automatically create and replicate all data in a source cluster even as new topics are added.
+ Kafka administrators can define data flows that cross the boundaries of individual Kafka clusters, data centers, or geographical regions. Please refer to the section on <a href="#georeplication">Geo-Replication</a> for further information.
+ </p>
<h4 class="anchor-heading"><a id="basic_ops_consumer_lag" class="anchor-link"></a><a href="#basic_ops_consumer_lag">Checking consumer position</a></h4>
Sometimes it's useful to see the position of your consumers. We have a tool that will show the position of all consumers in a consumer group as well as how far behind the end of the log they are. To run this tool on a consumer group named <i>my-group</i> consuming a topic named <i>my-topic</i> would look like this:
@@ -472,12 +458,12 @@
<p><i>(2) Ensuring Progress:</i></p>
<p>If the throttle is set too low, in comparison to the incoming write rate, it is possible for replication to not
make progress. This occurs when:</p>
- <pre><code>max(BytesInPerSec) > throttle</code></pre>
+ <pre>max(BytesInPerSec) > throttle</code></pre>
<p>
Where BytesInPerSec is the metric that monitors the write throughput of producers into each broker. </p>
<p>The administrator can monitor whether replication is making progress, during the rebalance, using the metric:</p>
- <pre><code>kafka.server:type=FetcherLagMetrics,name=ConsumerLag,clientId=([-.\w]+),topic=([-.\w]+),partition=([0-9]+)</code></pre>
+ <pre>kafka.server:type=FetcherLagMetrics,name=ConsumerLag,clientId=([-.\w]+),topic=([-.\w]+),partition=([0-9]+)</code></pre>
<p>The lag should constantly decrease during replication. If the metric does not decrease the administrator should
increase the
@@ -541,7 +527,7 @@
<h3 class="anchor-heading"><a id="datacenters" class="anchor-link"></a><a href="#datacenters">6.2 Datacenters</a></h3>
- Some deployments will need to manage a data pipeline that spans multiple datacenters. Our recommended approach to this is to deploy a local Kafka cluster in each datacenter with application instances in each datacenter interacting only with their local cluster and mirroring between clusters (see the documentation on the <a href="#basic_ops_mirror_maker">mirror maker tool</a> for how to do this).
+ Some deployments will need to manage a data pipeline that spans multiple datacenters. Our recommended approach to this is to deploy a local Kafka cluster in each datacenter, with application instances in each datacenter interacting only with their local cluster and mirroring data between clusters (see the documentation on <a href="#georeplication">Geo-Replication</a> for how to do this).
<p>
This deployment pattern allows datacenters to act as independent entities and allows us to manage and tune inter-datacenter replication centrally. This allows each facility to stand alone and operate even if the inter-datacenter links are unavailable: when this occurs the mirroring falls behind until the link is restored at which time it catches up.
<p>
@@ -553,7 +539,558 @@
<p>
It is generally <i>not</i> advisable to run a <i>single</i> Kafka cluster that spans multiple datacenters over a high-latency link. This will incur very high replication latency both for Kafka writes and ZooKeeper writes, and neither Kafka nor ZooKeeper will remain available in all locations if the network between locations is unavailable.
- <h3 class="anchor-heading"><a id="config" class="anchor-link"></a><a href="#config">6.3 Kafka Configuration</a></h3>
+ <h3 class="anchor-heading"><a id="georeplication" class="anchor-link"></a><a href="#georeplication">6.3 Geo-Replication (Cross-Cluster Data Mirroring)</a></h3>
+
+ <h4 class="anchor-heading"><a id="georeplication-overview" class="anchor-link"></a><a href="#georeplication-overview">Geo-Replication Overview</a></h4>
+
+ <p>
+ Kafka administrators can define data flows that cross the boundaries of individual Kafka clusters, data centers, or geo-regions. Such event streaming setups are often needed for organizational, technical, or legal requirements. Common scenarios include:
+ </p>
+
+ <ul>
+ <li>Geo-replication</li>
+ <li>Disaster recovery</li>
+ <li>Feeding edge clusters into a central, aggregate cluster</li>
+ <li>Physical isolation of clusters (such as production vs. testing)</li>
+ <li>Cloud migration or hybrid cloud deployments</li>
+ <li>Legal and compliance requirements</li>
+ </ul>
+
+ <p>
+ Administrators can set up such inter-cluster data flows with Kafka's MirrorMaker (version 2), a tool to replicate data between different Kafka environments in a streaming manner. MirrorMaker is built on top of the Kafka Connect framework and supports features such as:
+ </p>
+
+ <ul>
+ <li>Replicates topics (data plus configurations)</li>
+ <li>Replicates consumer groups including offsets to migrate applications between clusters</li>
+ <li>Replicates ACLs</li>
+ <li>Preserves partitioning</li>
+ <li>Automatically detects new topics and partitions</li>
+ <li>Provides a wide range of metrics, such as end-to-end replication latency across multiple data centers/clusters</li>
+ <li>Fault-tolerant and horizontally scalable operations</li>
+ </ul>
+
+ <p>
+ <em>Note: Geo-replication with MirrorMaker replicates data across Kafka clusters. This inter-cluster replication is different from Kafka's <a href="#replication">intra-cluster replication</a>, which replicates data within the same Kafka cluster.</em>
+ </p>
+
+ <h4 class="anchor-heading"><a id="georeplication-flows" class="anchor-link"></a><a href="#georeplication-flows">What Are Replication Flows</a></h4>
+
+ <p>
+ With MirrorMaker, Kafka administrators can replicate topics, topic configurations, consumer groups and their offsets, and ACLs from one or more source Kafka clusters to one or more target Kafka clusters, i.e., across cluster environments. In a nutshell, MirrorMaker uses Connectors to consume from source clusters and produce to target clusters.
+ </p>
+
+ <p>
+ These directional flows from source to target clusters are called replication flows. They are defined with the format <code>{source_cluster}->{target_cluster}</code> in the MirrorMaker configuration file as described later. Administrators can create complex replication topologies based on these flows.
+ </p>
+
+ <p>
+ Here are some example patterns:
+ </p>
+
+ <ul>
+ <li>Active/Active high availability deployments: <code>A->B, B->A</code></li>
+ <li>Active/Passive or Active/Standby high availability deployments: <code>A->B</code></li>
+ <li>Aggregation (e.g., from many clusters to one): <code>A->K, B->K, C->K</code></li>
+ <li>Fan-out (e.g., from one to many clusters): <code>K->A, K->B, K->C</code></li>
+ <li>Forwarding: <code>A->B, B->C, C->D</code></li>
+ </ul>
+
+ <p>
+ By default, a flow replicates all topics and consumer groups. However, each replication flow can be configured independently. For instance, you can define that only specific topics or consumer groups are replicated from the source cluster to the target cluster.
+ </p>
+
+ <p>
+ Here is a first example on how to configure data replication from a <code>primary</code> cluster to a <code>secondary</code> cluster (an active/passive setup):
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Basic settings
+clusters = primary, secondary
+primary.bootstrap.servers = broker3-primary:9092
+secondary.bootstrap.servers = broker5-secondary:9092
+
+# Define replication flows
+primary->secondary.enable = true
+primary->secondary.topics = foobar-topic, quux-.*
+</code></pre>
+
+
+ <h4 class="anchor-heading"><a id="georeplication-mirrormaker" class="anchor-link"></a><a href="#georeplication-mirrormaker">Configuring Geo-Replication</a></h4>
+
+ <p>
+ The following sections describe how to configure and run a dedicated MirrorMaker cluster. If you want to run MirrorMaker within an existing Kafka Connect cluster or other supported deployment setups, please refer to <a href="https://cwiki.apache.org/confluence/display/KAFKA/KIP-382%3A+MirrorMaker+2.0">KIP-382: MirrorMaker 2.0</a> and be aware that the names of configuration settings may vary between deployment modes.
+ </p>
+
+ <p>
+ Beyond what's covered in the following sections, further examples and information on configuration settings are available at:
+ </p>
+
+ <ul>
+ <li><a href="https://github.com/apache/kafka/blob/trunk/connect/mirror/src/main/java/org/apache/kafka/connect/mirror/MirrorMakerConfig.java">MirrorMakerConfig</a>, <a href="https://github.com/apache/kafka/blob/trunk/connect/mirror/src/main/java/org/apache/kafka/connect/mirror/MirrorConnectorConfig.java">MirrorConnectorConfig</a></li>
+ <li><a href="https://github.com/apache/kafka/blob/trunk/connect/mirror/src/main/java/org/apache/kafka/connect/mirror/DefaultTopicFilter.java">DefaultTopicFilter</a> for topics, <a href="https://github.com/apache/kafka/blob/trunk/connect/mirror/src/main/java/org/apache/kafka/connect/mirror/DefaultGroupFilter.java">DefaultGroupFilter</a> for consumer groups</li>
+ <li>Example configuration settings in <a href="https://github.com/apache/kafka/blob/trunk/config/connect-mirror-maker.properties">connect-mirror-maker.properties</a>, <a href="https://cwiki.apache.org/confluence/display/KAFKA/KIP-382%3A+MirrorMaker+2.0">KIP-382: MirrorMaker 2.0</a></li>
+ </ul>
+
+ <h5 class="anchor-heading"><a id="georeplication-config-syntax" class="anchor-link"></a><a href="#georeplication-config-syntax">Configuration File Syntax</a></h5>
+
+ <p>
+ The MirrorMaker configuration file is typically named <code>connect-mirror-maker.properties</code>. You can configure a variety of components in this file:
+ </p>
+
+ <ul>
+ <li>MirrorMaker settings: global settings including cluster definitions (aliases), plus custom settings per replication flow</li>
+ <li>Kafka Connect and connector settings</li>
+ <li>Kafka producer, consumer, and admin client settings</li>
+ </ul>
+
+ <p>
+ Example: Define MirrorMaker settings (explained in more detail later).
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Global settings
+clusters = us-west, us-east # defines cluster aliases
+us-west.bootstrap.servers = broker3-west:9092
+us-east.bootstrap.servers = broker5-east:9092
+
+topics = .* # all topics to be replicated by default
+
+# Specific replication flow settings (here: flow from us-west to us-east)
+us-west->us-east.enable = true
+us-west->us.east.topics = foo.*, bar.* # override the default above
+</code></pre>
+
+ <p>
+ MirrorMaker is based on the Kafka Connect framework. Any Kafka Connect, source connector, and sink connector settings as described in the <a href="#connectconfigs">documentation chapter on Kafka Connect</a> can be used directly in the MirrorMaker configuration, without having to change or prefix the name of the configuration setting.
+ </p>
+
+ <p>
+ Example: Define custom Kafka Connect settings to be used by MirrorMaker.
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Setting Kafka Connect defaults for MirrorMaker
+tasks.max = 5
+</code></pre>
+
+ <p>
+ Most of the default Kafka Connect settings work well for MirrorMaker out-of-the-box, with the exception of <code>tasks.max</code>. In order to evenly distribute the workload across more than one MirrorMaker process, it is recommended to set <code>tasks.max</code> to at least <code>2</code> (preferably higher) depending on the available hardware resources and the total number of topic-partitions to be replicated.
+ </p>
+
+ <p>
+ You can further customize MirrorMaker's Kafka Connect settings <em>per source or target cluster</em> (more precisely, you can specify Kafka Connect worker-level configuration settings "per connector"). Use the format of <code>{cluster}.{config_name}</code> in the MirrorMaker configuration file.
+ </p>
+
+ <p>
+ Example: Define custom connector settings for the <code>us-west</code> cluster.
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># us-west custom settings
+us-west.offset.storage.topic = my-mirrormaker-offsets
+</code></pre>
+
+ <p>
+ MirrorMaker internally uses the Kafka producer, consumer, and admin clients. Custom settings for these clients are often needed. To override the defaults, use the following format in the MirrorMaker configuration file:
+ </p>
+
+ <ul>
+ <li><code>{source}.consumer.{consumer_config_name}</code></li>
+ <li><code>{target}.producer.{producer_config_name}</code></li>
+ <li><code>{source_or_target}.admin.{admin_config_name}</code></li>
+ </ul>
+
+ <p>
+ Example: Define custom producer, consumer, admin client settings.
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># us-west cluster (from which to consume)
+us-west.consumer.isolation.level = read_committed
+us-west.admin.bootstrap.servers = broker57-primary:9092
+
+# us-east cluster (to which to produce)
+us-east.producer.compression.type = gzip
+us-east.producer.buffer.memory = 32768
+us-east.admin.bootstrap.servers = broker8-secondary:9092
+</code></pre>
+
+ <h5 class="anchor-heading"><a id="georeplication-flow-create" class="anchor-link"></a><a href="#georeplication-flow-create">Creating and Enabling Replication Flows</a></h5>
+
+ <p>
+ To define a replication flow, you must first define the respective source and target Kafka clusters in the MirrorMaker configuration file.
+ </p>
+
+ <ul>
+ <li><code>clusters</code> (required): comma-separated list of Kafka cluster "aliases"</li>
+ <li><code>{clusterAlias}.bootstrap.servers</code> (required): connection information for the specific cluster; comma-separated list of "bootstrap" Kafka brokers
+ </ul>
+
+ <p>
+ Example: Define two cluster aliases <code>primary</code> and <code>secondary</code>, including their connection information.
+ </p>
+
+<pre class="line-numbers"><code class="language-text">clusters = primary, secondary
+primary.bootstrap.servers = broker10-primary:9092,broker-11-primary:9092
+secondary.bootstrap.servers = broker5-secondary:9092,broker6-secondary:9092
+</code></pre>
+
+ <p>
+ Secondly, you must explicitly enable individual replication flows with <code>{source}->{target}.enabled = true</code> as needed. Remember that flows are directional: if you need two-way (bidirectional) replication, you must enable flows in both directions.
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Enable replication from primary to secondary
+primary->secondary.enable = true
+</code></pre>
+
+ <p>
+ By default, a replication flow will replicate all but a few special topics and consumer groups from the source cluster to the target cluster, and automatically detect any newly created topics and groups. The names of replicated topics in the target cluster will be prefixed with the name of the source cluster (see section further below). For example, the topic <code>foo</code> in the source cluster <code>us-west</code> would be replicated to a topic named <code>us-west.foo</code> in the target cluster <code>us-east</code>.
+ </p>
+
+ <p>
+ The subsequent sections explain how to customize this basic setup according to your needs.
+ </p>
+
+ <h5 class="anchor-heading"><a id="georeplication-flow-configure" class="anchor-link"></a><a href="#georeplication-flow-configure">Configuring Replication Flows</a></h5>
+
+ <p>
+The configuration of a replication flow is a combination of top-level default settings (e.g., <code>topics</code>), on top of which flow-specific settings, if any, are applied (e.g., <code>us-west->us-east.topics</code>). To change the top-level defaults, add the respective top-level setting to the MirrorMaker configuration file. To override the defaults for a specific replication flow only, use the syntax format <code>{source}->{target}.{config.name}</code>.
+ </p>
+
+ <p>
+ The most important settings are:
+ </p>
+
+ <ul>
+ <li><code>topics</code>: list of topics or a regular expression that defines which topics in the source cluster to replicate (default: <code>topics = .*</code>)
+ <li><code>topics.exclude</code>: list of topics or a regular expression to subsequently exclude topics that were matched by the <code>topics</code> setting (default: <code>topics.exclude = .*[\-\.]internal, .*\.replica, __.*</code>)
+ <li><code>groups</code>: list of topics or regular expression that defines which consumer groups in the source cluster to replicate (default: <code>groups = .*</code>)
+ <li><code>groups.exclude</code>: list of topics or a regular expression to subsequently exclude consumer groups that were matched by the <code>groups</code> setting (default: <code>groups.exclude = console-consumer-.*, connect-.*, __.*</code>)
+ <li><code>{source}->{target}.enable</code>: set to <code>true</code> to enable the replication flow (default: <code>false</code>)
+ </ul>
+
+ <p>
+ Example:
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Custom top-level defaults that apply to all replication flows
+topics = .*
+groups = consumer-group1, consumer-group2
+
+# Don't forget to enable a flow!
+us-west->us-east.enable = true
+
+# Custom settings for specific replication flows
+us-west->us-east.topics = foo.*
+us-west->us-east.groups = bar.*
+us-west->us-east.emit.heartbeats = false
+</code></pre>
+
+ <p>
+ Additional configuration settings are supported, some of which are listed below. In most cases, you can leave these settings at their default values. See <a href="https://github.com/apache/kafka/blob/trunk/connect/mirror/src/main/java/org/apache/kafka/connect/mirror/MirrorMakerConfig.java">MirrorMakerConfig</a> and <a href="https://github.com/apache/kafka/blob/trunk/connect/mirror/src/main/java/org/apache/kafka/connect/mirror/MirrorConnectorConfig.java">MirrorConnectorConfig</a> for further details.
+ </p>
+
+ <ul>
+ <li><code>refresh.topics.enabled</code>: whether to check for new topics in the source cluster periodically (default: true)
+ <li><code>refresh.topics.interval.seconds</code>: frequency of checking for new topics in the source cluster; lower values than the default may lead to performance degradation (default: 6000, every ten minutes)
+ <li><code>refresh.groups.enabled</code>: whether to check for new consumer groups in the source cluster periodically (default: true)
+ <li><code>refresh.groups.interval.seconds</code>: frequency of checking for new consumer groups in the source cluster; lower values than the default may lead to performance degradation (default: 6000, every ten minutes)
+ <li><code>sync.topic.configs.enabled</code>: whether to replicate topic configurations from the source cluster (default: true)
+ <li><code>sync.topic.acls.enabled</code>: whether to sync ACLs from the source cluster (default: true)
+ <li><code>emit.heartbeats.enabled</code>: whether to emit heartbeats periodically (default: true)
+ <li><code>emit.heartbeats.interval.seconds</code>: frequency at which heartbeats are emitted (default: 5, every five seconds)
+ <li><code>heartbeats.topic.replication.factor</code>: replication factor of MirrorMaker's internal heartbeat topics (default: 3)
+ <li><code>emit.checkpoints.enabled</code>: whether to emit MirrorMaker's consumer offsets periodically (default: true)
+ <li><code>emit.checkpoints.interval.seconds</code>: frequency at which checkpoints are emitted (default: 60, every minute)
+ <li><code>checkpoints.topic.replication.factor</code>: replication factor of MirrorMaker's internal checkpoints topics (default: 3)
+ <li><code>sync.group.offsets.enabled</code>: whether to periodically write the translated offsets of replicated consumer groups (in the source cluster) to <code>__consumer_offsets</code> topic in target cluster, as long as no active consumers in that group are connected to the target cluster (default: true)
+ <li><code>sync.group.offsets.interval.seconds</code>: frequency at which consumer group offsets are synced (default: 60, every minute)
+ <li><code>offset-syncs.topic.replication.factor</code>: replication factor of MirrorMaker's internal offset-sync topics (default: 3)
+ </ul>
+
+ <h5 class="anchor-heading"><a id="georeplication-flow-secure" class="anchor-link"></a><a href="#georeplication-flow-secure">Securing Replication Flows</a></h5>
+
+ <p>
+ MirrorMaker supports the same <a href="#connectconfigs">security settings as Kafka Connect</a>, so please refer to the linked section for further information.
+ </p>
+
+ <p>
+ Example: Encrypt communication between MirrorMaker and the <code>us-east</code> cluster.
+ </p>
+
+<pre class="line-numbers"><code class="language-text">us-east.security.protocol=SSL
+us-east.ssl.truststore.location=/path/to/truststore.jks
+us-east.ssl.truststore.password=my-secret-password
+us-east.ssl.keystore.location=/path/to/keystore.jks
+us-east.ssl.keystore.password=my-secret-password
+us-east.ssl.key.password=my-secret-password
+</code></pre>
+
+ <h5 class="anchor-heading"><a id="georeplication-topic-naming" class="anchor-link"></a><a href="#georeplication-topic-naming">Custom Naming of Replicated Topics in Target Clusters</a></h5>
+
+ <p>
+ Replicated topics in a target cluster—sometimes called <em>remote</em> topics—are renamed according to a replication policy. MirrorMaker uses this policy to ensure that events (aka records, messages) from different clusters are not written to the same topic-partition. By default as per <a href="https://github.com/apache/kafka/blob/trunk/connect/mirror-client/src/main/java/org/apache/kafka/connect/mirror/DefaultReplicationPolicy.java">DefaultReplicationPolicy</a>, the names of replicated topics in the target clusters have the format <code>{source}.{source_topic_name}</code>:
+ </p>
+
+<pre class="line-numbers"><code class="language-text">us-west us-east
+========= =================
+ bar-topic
+foo-topic --> us-west.foo-topic
+</code></pre>
+
+ <p>
+ You can customize the separator (default: <code>.</code>) with the <code>replication.policy.separator</code> setting:
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Defining a custom separator
+us-west->us-east.replication.policy.separator = _
+</code></pre>
+
+ <p>
+ If you need further control over how replicated topics are named, you can implement a custom <code>ReplicationPolicy</code> and override <code>replication.policy.class</code> (default is <code>DefaultReplicationPolicy</code>) in the MirrorMaker configuration.
+ </p>
+
+ <h5 class="anchor-heading"><a id="georeplication-config-conflicts" class="anchor-link"></a><a href="#georeplication-config-conflicts">Preventing Configuration Conflicts</a></h5>
+
+ <p>
+ MirrorMaker processes share configuration via their target Kafka clusters. This behavior may cause conflicts when configurations differ among MirrorMaker processes that operate against the same target cluster.
+ </p>
+
+ <p>
+ For example, the following two MirrorMaker processes would be racy:
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Configuration of process 1
+A->B.enabled = true
+A->B.topics = foo
+
+# Configuration of process 2
+A->B.enabled = true
+A->B.topics = bar
+</code></pre>
+
+ <p>
+ In this case, the two processes will share configuration via cluster <code>B</code>, which causes a conflict. Depending on which of the two processes is the elected "leader", the result will be that either the topic <code>foo</code> or the topic <code>bar</code> is replicated, but not both.
+ </p>
+
+ <p>
+ It is therefore important to keep the MirrorMaker configration consistent across replication flows to the same target cluster. This can be achieved, for example, through automation tooling or by using a single, shared MirrorMaker configuration file for your entire organization.
+ </p>
+
+ <h5 class="anchor-heading"><a id="georeplication-best-practice" class="anchor-link"></a><a href="#georeplication-best-practice">Best Practice: Consume from Remote, Produce to Local</a></h5>
+
+ <p>
+To minimize latency ("producer lag"), it is recommended to locate MirrorMaker processes as close as possible to their target clusters, i.e., the clusters that it produces data to. That's because Kafka producers typically struggle more with unreliable or high-latency network connections than Kafka consumers.
+ </p>
+
+<pre class="line-numbers"><code class="language-text">First DC Second DC
+========== =========================
+primary --------- MirrorMaker --> secondary
+(remote) (local)
+</code></pre>
+
+ <p>
+To run such a "consume from remote, produce to local" setup, run the MirrorMaker processes close to and preferably in the same location as the target clusters, and explicitly set these "local" clusters in the <code>--clusters</code> command line parameter (blank-separated list of cluster aliases):
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Run in secondary's data center, reading from the remote `primary` cluster
+$ ./bin/connect-mirror-maker.sh connect-mirror-maker.properties --clusters secondary
+</code></pre>
+
+The <code>--clusters secondary</code> tells the MirrorMaker process that the given cluster(s) are nearby, and prevents it from replicating data or sending configuration to clusters at other, remote locations.
+
+ <h5 class="anchor-heading"><a id="georeplication-example-active-passive" class="anchor-link"></a><a href="#georeplication-example-active-passive">Example: Active/Passive High Availability Deployment</a></h5>
+
+ <p>
+The following example shows the basic settings to replicate topics from a primary to a secondary Kafka environment, but not from the secondary back to the primary. Please be aware that most production setups will need further configuration, such as security settings.
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Unidirectional flow (one-way) from primary to secondary cluster
+primary.bootstrap.servers = broker1-primary:9092
+secondary.bootstrap.servers = broker2-secondary:9092
+
+primary->secondary.enabled = true
+secondary->primary.enabled = false
+
+primary->secondary.topics = foo.* # only replicate some topics
+</code></pre>
+
+ <h5 class="anchor-heading"><a id="georeplication-example-active-active" class="anchor-link"></a><a href="#georeplication-example-active-active">Example: Active/Active High Availability Deployment</a></h5>
+
+ <p>
+ The following example shows the basic settings to replicate topics between two clusters in both ways. Please be aware that most production setups will need further configuration, such as security settings.
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Bidirectional flow (two-way) between us-west and us-east clusters
+clusters = us-west, us-east
+us-west.bootstrap.servers = broker1-west:9092,broker2-west:9092
+Us-east.bootstrap.servers = broker3-east:9092,broker4-east:9092
+
+us-west->us-east.enabled = true
+us-east->us-west.enabled = true
+</code></pre>
+
+ <p>
+ <em>Note on preventing replication "loops" (where topics will be originally replicated from A to B, then the replicated topics will be replicated yet again from B to A, and so forth)</em>: As long as you define the above flows in the same MirrorMaker configuration file, you do not need to explicitly add <code>topics.exclude</code> settings to prevent replication loops between the two clusters.
+ </p>
+
+ <h5 class="anchor-heading"><a id="georeplication-example-multi-cluster" class="anchor-link"></a><a href="#georeplication-example-multi-cluster">Example: Multi-Cluster Geo-Replication</a></h5>
+
+ <p>
+ Let's put all the information from the previous sections together in a larger example. Imagine there are three data centers (west, east, north), with two Kafka clusters in each data center (e.g., <code>west-1</code>, <code>west-2</code>). The example in this section shows how to configure MirrorMaker (1) for Active/Active replication within each data center, as well as (2) for Cross Data Center Replication (XDCR).
+ </p>
+
+ <p>
+ First, define the source and target clusters along with their replication flows in the configuration:
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Basic settings
+clusters: west-1, west-2, east-1, east-2, north-1, north-2
+west-1.bootstrap.servers = ...
+west-2.bootstrap.servers = ...
+east-1.bootstrap.servers = ...
+east-2.bootstrap.servers = ...
+north-1.bootstrap.servers = ...
+north-2.bootstrap.servers = ...
+
+# Replication flows for Active/Active in West DC
+west-1->west-2.enabled = true
+west-2->west-1.enabled = true
+
+# Replication flows for Active/Active in East DC
+east-1->east-2.enabled = true
+east-2->east-1.enabled = true
+
+# Replication flows for Active/Active in North DC
+north-1->north-2.enabled = true
+north-2->north-1.enabled = true
+
+# Replication flows for XDCR via west-1, east-1, north-1
+west-1->east-1.enabled = true
+west-1->north-1.enabled = true
+east-1->west-1.enabled = true
+east-1->north-1.enabled = true
+north-1->west-1.enabled = true
+north-1->east-1.enabled = true
+</code></pre>
+
+ <p>
+ Then, in each data center, launch one or more MirrorMaker as follows:
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># In West DC:
+$ ./bin/connect-mirror-maker.sh connect-mirror-maker.properties --clusters west-1 west-2
+
+# In East DC:
+$ ./bin/connect-mirror-maker.sh connect-mirror-maker.properties --clusters east-1 east-2
+
+# In North DC:
+$ ./bin/connect-mirror-maker.sh connect-mirror-maker.properties --clusters north-1 north-2
+</code></pre>
+
+ <p>
+ With this configuration, records produced to any cluster will be replicated within the data center, as well as across to other data centers. By providing the <code>--clusters</code> parameter, we ensure that each MirrorMaker process produces data to nearby clusters only.
+ </p>
+
+ <p>
+ <em>Note:</em> The <code>--clusters</code> parameter is, technically, not required here. MirrorMaker will work fine without it. However, throughput may suffer from "producer lag" between data centers, and you may incur unnecessary data transfer costs.
+ </p>
+
+<h4 class="anchor-heading"><a id="georeplication-starting" class="anchor-link"></a><a href="#georeplication-starting">Starting Geo-Replication</a></h4>
+
+ <p>
+ You can run as few or as many MirrorMaker processes (think: nodes, servers) as needed. Because MirrorMaker is based on Kafka Connect, MirrorMaker processes that are configured to replicate the same Kafka clusters run in a distributed setup: They will find each other, share configuration (see section below), load balance their work, and so on. If, for example, you want to increase the throughput of replication flows, one option is to run additional MirrorMaker processes in parallel.
+ </p>
+
+ <p>
+ To start a MirrorMaker process, run the command:
+ </p>
+
+<pre class="line-numbers"><code class="language-text">$ ./bin/connect-mirror-maker.sh connect-mirror-maker.properties
+</code></pre>
+
+ <p>
+ After startup, it may take a few minutes until a MirrorMaker process first begins to replicate data.
+ </p>
+
+ <p>
+ Optionally, as described previously, you can set the parameter <code>--clusters</code> to ensure that the MirrorMaker process produces data to nearby clusters only.
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># Note: The cluster alias us-west must be defined in the configuration file
+$ ./bin/connect-mirror-maker.sh connect-mirror-maker.properties \
+ --clusters us-west
+</code></pre>
+
+ <p>
+ <em>Note when testing replication of consumer groups:</em> By default, MirrorMaker does not replicate consumer groups created by the <code>kafka-console-consumer.sh</code> tool, which you might use to test your MirrorMaker setup on the command line. If you do want to replicate these consumer groups as well, set the <code>groups.exclude</code> configuration accordingly (default: <code>groups.exclude = console-consumer-.*, connect-.*, __.*</code>). Remember to update the configuration again once you completed your testing.
+ </p>
+
+<h4 class="anchor-heading"><a id="georeplication-stopping" class="anchor-link"></a><a href="#georeplication-stopping">Stopping Geo-Replication</a></h4>
+
+ <p>
+ You can stop a running MirrorMaker process by sending a SIGTERM signal with the command:
+ </p>
+
+<pre class="line-numbers"><code class="language-text">$ kill <MirrorMaker pid>
+</code></pre>
+
+<h4 class="anchor-heading"><a id="georeplication-apply-config-changes" class="anchor-link"></a><a href="#georeplication-apply-config-changes">Applying Configuration Changes</a></h4>
+
+ <p>
+ To make configuration changes take effect, the MirrorMaker process(es) must be restarted.
+ </p>
+
+<h4 class="anchor-heading"><a id="georeplication-monitoring" class="anchor-link"></a><a href="#georeplication-monitoring">Monitoring Geo-Replication</a></h4>
+
+ <p>
+ It is recommended to monitor MirrorMaker processes to ensure all defined replication flows are up and running correctly. MirrorMaker is built on the Connect framework and inherits all of Connect's metrics, such <code>source-record-poll-rate</code>. In addition, MirrorMaker produces its own metrics under the <code>kafka.connect.mirror</code> metric group. Metrics are tagged with the following properties:
+ </p>
+
+ <ul>
+ <li><code>source</code>: alias of source cluster (e.g., <code>primary</code>)</li>
+ <li><code>target</code>: alias of target cluster (e.g., <code>secondary</code>)</li>
+ <li><code>topic</code>: replicated topic on target cluster</li>
+ <li><code>partition</code>: partition being replicated</li>
+ </ul>
+
+ <p>
+ Metrics are tracked for each replicated topic. The source cluster can be inferred from the topic name. For example, replicating <code>topic1</code> from <code>primary->secondary</code> will yield metrics like:
+ </p>
+
+ <ul>
+ <li><code>target=secondary</code>
+ <li><code>topic=primary.topic1</code>
+ <li><code>partition=1</code>
+ </ul>
+
+ <p>
+ The following metrics are emitted:
+ </p>
+
+<pre class="line-numbers"><code class="language-text"># MBean: kafka.connect.mirror:type=MirrorSourceConnector,target=([-.w]+),topic=([-.w]+),partition=([0-9]+)
+
+record-count # number of records replicated source -> target
+record-age-ms # age of records when they are replicated
+record-age-ms-min
+record-age-ms-max
+record-age-ms-avg
+replication-latency-ms # time it takes records to propagate source->target
+replication-latency-ms-min
+replication-latency-ms-max
+replication-latency-ms-avg
+byte-rate # average number of bytes/sec in replicated records
+
+# MBean: kafka.connect.mirror:type=MirrorCheckpointConnector,source=([-.w]+),target=([-.w]+)
+
+checkpoint-latency-ms # time it takes to replicate consumer offsets
+checkpoint-latency-ms-min
+checkpoint-latency-ms-max
+checkpoint-latency-ms-avg
+</code></pre>
+
+ <p>
+ These metrics do not differentiate between created-at and log-append timestamps.
+ </p>
+
+
+ <h3 class="anchor-heading"><a id="config" class="anchor-link"></a><a href="#config">6.4 Kafka Configuration</a></h3>
<h4 class="anchor-heading"><a id="clientconfig" class="anchor-link"></a><a href="#clientconfig">Important Client Configurations</a></h4>
@@ -586,7 +1123,7 @@
Our client configuration varies a fair amount between different use cases.
- <h3 class="anchor-heading"><a id="java" class="anchor-link"></a><a href="#java">6.4 Java Version</a></h3>
+ <h3 class="anchor-heading"><a id="java" class="anchor-link"></a><a href="#java">6.5 Java Version</a></h3>
Java 8 and Java 11 are supported. Java 11 performs significantly better if TLS is enabled, so it is highly recommended (it also includes a number of other
performance improvements: G1GC, CRC32C, Compact Strings, Thread-Local Handshakes and more).
@@ -609,7 +1146,7 @@
All of the brokers in that cluster have a 90% GC pause time of about 21ms with less than 1 young GC per second.
- <h3 class="anchor-heading"><a id="hwandos" class="anchor-link"></a><a href="#hwandos">6.5 Hardware and OS</a></h3>
+ <h3 class="anchor-heading"><a id="hwandos" class="anchor-link"></a><a href="#hwandos">6.6 Hardware and OS</a></h3>
We are using dual quad-core Intel Xeon machines with 24GB of memory.
<p>
You need sufficient memory to buffer active readers and writers. You can do a back-of-the-envelope estimate of memory needs by assuming you want to be able to buffer for 30 seconds and compute your memory need as write_throughput*30.
@@ -694,7 +1231,7 @@
<li>delalloc: Delayed allocation means that the filesystem avoid allocating any blocks until the physical write occurs. This allows ext4 to allocate a large extent instead of smaller pages and helps ensure the data is written sequentially. This feature is great for throughput. It does seem to involve some locking in the filesystem which adds a bit of latency variance.
</ul>
- <h3 class="anchor-heading"><a id="monitoring" class="anchor-link"></a><a href="#monitoring">6.6 Monitoring</a></h3>
+ <h3 class="anchor-heading"><a id="monitoring" class="anchor-link"></a><a href="#monitoring">6.7 Monitoring</a></h3>
Kafka uses Yammer Metrics for metrics reporting in the server. 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>
@@ -767,6 +1304,11 @@
<td>Number of records which required message format conversion.</td>
</tr>
<tr>
+ <td>Request Queue Size</td>
+ <td>kafka.network:type=RequestChannel,name=RequestQueueSize</td>
+ <td>Size of the request queue.</td>
+ </tr>
+ <tr>
<td>Byte out rate to clients</td>
<td>kafka.server:type=BrokerTopicMetrics,name=BytesOutPerSec</td>
<td></td>
@@ -2143,7 +2685,7 @@
On the client side, we recommend monitoring the message/byte rate (global and per topic), request rate/size/time, and on the consumer side, max lag in messages among all partitions and min fetch request rate. For a consumer to keep up, max lag needs to be less than a threshold and min fetch rate needs to be larger than 0.
- <h3 class="anchor-heading"><a id="zk" class="anchor-link"></a><a href="#zk">6.7 ZooKeeper</a></h3>
+ <h3 class="anchor-heading"><a id="zk" class="anchor-link"></a><a href="#zk">6.8 ZooKeeper</a></h3>
<h4 class="anchor-heading"><a id="zkversion" class="anchor-link"></a><a href="#zkversion">Stable version</a></h4>
The current stable branch is 3.5. Kafka is regularly updated to include the latest release in the 3.5 series.
diff --git a/26/toc.html b/26/toc.html
index b8c977a..8d15b2b 100644
--- a/26/toc.html
+++ b/26/toc.html
@@ -86,13 +86,23 @@
<li><a href="#basic_ops_increase_replication_factor">Increasing replication factor</a>
</ul>
<li><a href="#datacenters">6.2 Datacenters</a>
- <li><a href="#config">6.3 Important Configs</a>
+ <li><a href="#georeplication">6.3 Geo-Replication (Cross-Cluster Data Mirroring)</a></li>
+ <ul>
+ <li><a href="#georeplication-overview">Geo-Replication Overview</a></li>
+ <li><a href="#georeplication-flows">What Are Replication Flows</a></li>
+ <li><a href="#georeplication-mirrormaker">Configuring Geo-Replication</a></li>
+ <li><a href="#georeplication-starting">Starting Geo-Replication</a></li>
+ <li><a href="#georeplication-stopping">Stopping Geo-Replication</a></li>
+ <li><a href="#georeplication-apply-config-changes">Applying Configuration Changes</a></li>
+ <li><a href="#georeplication-monitoring">Monitoring Geo-Replication</a></li>
+ </ul>
+ <li><a href="#config">6.4 Important Configs</a>
<ul>
<li><a href="#clientconfig">Important Client Configs</a>
<li><a href="#prodconfig">A Production Server Configs</a>
</ul>
- <li><a href="#java">6.4 Java Version</a>
- <li><a href="#hwandos">6.5 Hardware and OS</a>
+ <li><a href="#java">6.5 Java Version</a>
+ <li><a href="#hwandos">6.6 Hardware and OS</a>
<ul>
<li><a href="#os">OS</a>
<li><a href="#diskandfs">Disks and Filesystems</a>
@@ -100,7 +110,7 @@
<li><a href="#linuxflush">Linux Flush Behavior</a>
<li><a href="#ext4">Ext4 Notes</a>
</ul>
- <li><a href="#monitoring">6.6 Monitoring</a>
+ <li><a href="#monitoring">6.7 Monitoring</a>
<ul>
<li><a href="#selector_monitoring">Selector Monitoring</a></li>
<li><a href="#common_node_monitoring">Common Node Monitoring</a></li>
@@ -110,7 +120,7 @@
<li><a href="#kafka_streams_monitoring">Streams Monitoring</a></li>
<li><a href="#others_monitoring">Others</a></li>
</ul>
- <li><a href="#zk">6.7 ZooKeeper</a>
+ <li><a href="#zk">6.8 ZooKeeper</a>
<ul>
<li><a href="#zkversion">Stable Version</a>
<li><a href="#zkops">Operationalization</a>
