How to use Kafka MirrorMaker 2.0 in data migration, replication and the use-cases

MirrorMaker 2.0 (MM2) is designed to make it easier to mirror or replicate topics from one Kafka cluster to another. It uses the Kafka Connect framework to simplify configuration and scaling. It dynamically detects changes to topics and ensures source and target topic properties are synchronized, including offsets and partitions.

In this article, you'll learn how to use Kafka MirrorMaker 2.0 in data migration/replication and the use-cases.


  • Environment with at least two HDI Kafka clusters.
  • Kafka version higher than 2.4 (HDI 4.0)
  • The source cluster should have data points and topics to test various features of the MirrorMaker 2.0 replication process

Use case

Simulation of MirrorMaker 2.0 to replicate data points/offsets between two Kafka clusters in HDInsight. The same can be used for scenarios like required data replication between two or more Kafka Clusters like Disaster Recovery, Cloud Adaption, Geo-replication, Data Isolation, and Data Aggregation.

Offset replication with MirrorMaker 2.0

MM2 Internals

The MirrorMaker 2.0 tool is composed of different connectors. These connectors are standard Kafka Connect connectors, which can be used directly with Kafka Connect in standalone or distributed mode.

The summary of the broker setup process is as follows:

MirrorSourceConnector :

  1. Replicates remote topics, topic ACLs & configs of a single source cluster.
  2. Emits offset-syncs to an internal topic.


  1. Consumes from the primary cluster and replicate topics to a single target cluster.


  1. Consumes offset-syncsr.
  2. Emits checkpoints to enable failover points.


  1. Emits heartbeats to remote clusters, enabling monitoring of replication process.


  1. script bundled with the Kafka library implements a distributed MM2 cluster, which manages the Connect workers internally based on a config file. Internally MirrorMaker driver creates and handles pairs of each connector – MirrorSourceConnector, MirrorSinkConnector, MirrorCheckpoint connector and MirrorHeartbeatConnector.

  2. Start MirrorMaker 2.0.

    ./bin/ ./config/    


For Kerberos enabled clusters, the JAAS configuration must be exported to the KAFKA_OPTS or must be specified in the MM2 config file.

export KAFKA_OPTS="<path-to-jaas.conf>"    

Sample MirrorMaker 2.0 Configuration file

# specify any number of cluster aliases
clusters = source, destination

# connection information for each cluster
# This is a comma separated host:port pairs for each cluster
# for example. "A_host1:9092, A_host2:9092, A_host3:9092"  and you can see the exact host name on Ambari > Hosts
source.bootstrap.servers =,,
destination.bootstrap.servers =,,

# enable and configure individual replication flows
source->destination.enabled = true

# regex which defines which topics gets replicated. For eg "foo-.*"
source->destination.topics = toa.evehicles-latest-dev

# Setting replication factor of newly created remote topics


SSL configuration

If the setup requires SSL configuration
#keystore location in case client.auth is set to required

Global configurations

Property Default value Description
name required name of the connector, For Example, "us-west->us-east"
topics empty string regex of topics to replicate, for example "topic1, topic2, topic3". Comma-separated lists are also supported.
topics.blacklist "..internal, ..replica, __consumer_offsets" or similar topics to exclude from replication
groups empty string regex of groups to replicate, For Example, ".*"
groups.blacklist empty string groups to exclude from replication
source.cluster.alias required name of the cluster being replicated
target.cluster.alias required name of the downstream Kafka cluster
source.cluster.bootstrap.servers required upstream cluster to replicate
target.cluster.bootstrap.servers required downstream cluster
sync.topic.configs.enabled true whether or not to monitor source cluster for configuration changes
sync.topic.acls.enabled true whether to monitor source cluster ACLs for changes
emit.heartbeats.enabled true connector should periodically emit heartbeats
emit.heartbeats.interval.seconds true frequency of heartbeats
emit.checkpoints.enabled true connector should periodically emit consumer offset information
emit.checkpoints.interval.seconds 5 (seconds) frequency of checkpoints
refresh.topics.enabled true connector should periodically check for new consumer groups
refresh.topics.interval.seconds 5 (seconds) frequency to check source cluster for new consumer groups
refresh.groups.enabled true connector should periodically check for new consumer groups
refresh.groups.interval.seconds 5 (seconds) frequency to check source cluster for new consumer groups
readahead.queue.capacity 500 (records) number of records to let consumer get ahead of producer
replication.policy.class org.apache.kafka.connect.mirror.DefaultReplicationPolicy use LegacyReplicationPolicy to mimic legacy MirrorMaker one day used when creating heartbeat topics for the first time one day used when creating checkpoint topics for the first time max long used when creating offset sync topic for the first time
replication.factor two used when creating the remote topics

Frequently asked questions

Why do we see a difference in the last offset on source and destination cluster post replication of a topic?

It's possible that the source topic’s data points might have been purged due to which the actual record count would be less than the last offset value. This results in the difference between last offset on source and destination cluster post replication, as the replication will always start from offset-0 of the destination cluster.

How will the consumers behave on migration, if that the destination cluster may have a different offset mapping to data points?

The MirrorMaker 2.0 MirrorCheckpointConnector feature automatically stores consumer group offset checkpoints for consumer groups on the source cluster. Each checkpoint contains a mapping of the last committed offset for each group in the source cluster to the equivalent offset in destination cluster. So on migration the consumers that start consuming from same topic on the destination cluster will be able to resume receiving messages from the last offset they committed on the source cluster.

How can we retain the exact topic name in destination cluster, as the source alias is prefixed with all the topics replicated?

This is the default behavior in MirrorMaker 2.0 to avoid data overriding in complex mirroring topologies. Customization of this needs to be done carefully in terms of replication flow design and topic management to avoid data loss. This can be done by using a custom replication policy class against “replication.policy.class”.

Why do we see new internal topics created in my source and destination Kafka?

MirrorMaker 2.0 internal topics are created by the Connectors to keep track of the replication process, monitoring, offset mapping and checkpointing.

Why does MirrorMaker create only two replicas of the topic in the destination cluster while the source has more?

MirrorMaker 2 doesn’t replicate the replication factor of topics to target clusters. This can be controlled from MM2 config, by specifying the required number of “replication.factor”. The default value for the same is two.

How to use custom replication policy in MirrorMaker 2.0?

Custom Replication Policy can be created by implementing the interface below.

/** Defines which topics are "remote topics", e.g. "us-west.topic1". */
public interface ReplicationPolicy {

    /** How to rename remote topics; generally should be like us-west.topic1. */
    String formatRemoteTopic(String sourceClusterAlias, String topic);
    /** Source cluster alias of given remote topic, e.g. "us-west" for "us-west.topic1".
        Returns null if not a remote topic.
    String topicSource(String topic);
    /** Name of topic on the source cluster, e.g. "topic1" for "us-west.topic1".
        Topics may be replicated multiple hops, so the immediately upstream topic
        may itself be a remote topic.
        Returns null if not a remote topic.
    String upstreamTopic(String topic);
    /** The name of the original source-topic, which may have been replicated multiple hops.
        Returns the topic if it is not a remote topic.
    String originalTopic(String topic);
    /** Internal topics are never replicated. */
    boolean isInternalTopic(String topic);

The implementation needs to be added to the Kafka classpath for the class reference to be used against replication.policy.class in MM2 properties.

Next steps

What is Apache Kafka on HDInsight?


MirrorMaker 2.0 Changes Apache Doc

Client certificates setup for HDI Kafka

HDInsight Kafka

Apache Kafka 2.4 Documentation

Connect an on-premises network to Azure