Consumer group rebalancing
Consumer group rebalancing is the redistribution of topic-partition assignments among consumer group members after membership or partition availability changes.
Apache Kafka in Action
A rebalance is the redistribution of consumer-group partition assignments after membership, partition, or consumer availability changes.
- How it is used
- Redistributes partitions among consumer-group members when membership, partitions, or consumer availability changes.
- How deep it goes
- Explains broker and consumer roles, assignment strategies, disruption-reduction methods, and monitoring; does not specify a complete protocol message sequence.
- Examples
- Compares three consumers sharing two two-partition topics under Range Assignor and illustrates Cooperative Sticky Assignor’s two-round reassignment.
- What you can do after
- Operate/configure it by choosing a consistent assignment strategy and monitoring polling delays, rebalance failures, and latency.
Read how Apache Kafka in Action explains consumer group rebalancing →
Kafka Streams in Action, Second Edition
A consumer group rebalance is the redistribution of Kafka topic partitions among consumers in a consumer group.
- How it is used
- Coordinates partition ownership among consumers sharing a group ID when members fail, join, or return.
- How deep it goes
- Explains failure and timeout triggers, partition reassignment, eager and cooperative protocols, and Kafka Streams metadata sharing.
- Examples
- Uses six topic partitions shared by three consumers and a Java sales consumer polling ProductTransaction records.
- What you can do after
- Operate/configure it by setting group IDs and poll timing, then selecting cooperative rebalancing to reduce reassignment downtime.
Read how Kafka Streams in Action, Second Edition explains consumer group rebalancing →
Kafka for Architects
Consumer group rebalancing is the redistribution of topic-partition assignments among consumer group members when membership or partition availability changes.
- How it is used
- Keeps partitions assigned to healthy consumer-group members as instances join, leave, or fail.
- How deep it goes
- Explains triggers, eager-rebalance interruption, static membership, and timeout tuning; does not detail the rebalance protocol.
- Examples
- Illustrates reassignment after consumer failure with a partition diagram and a multi-instance Kafka Streams application.
- What you can do after
- Operate/configure consumer groups to limit avoidable rebalances while retaining failure detection and partition takeover.
Read how Kafka for Architects explains consumer group rebalancing →
Related concepts
- rolling updateproduced by · A rolling update is a deployment or upgrade technique that updates or replaces instances or resources incrementally rather than all at once, allowing the rest of the system to continue operating during the change.
- static group membershipaddressed by · Static group membership is a consumer-group mode in which instances retain stable identities across restarts to avoid unnecessary rebalancing.
- group coordinatorproduced by · A group coordinator is the Kafka broker responsible for managing a consumer group’s membership, liveness, partition assignments, and committed offsets.
- Kafka Streamsused by · Kafka Streams is a client library for building applications that continuously process data from and write data to Apache Kafka topics.
- partitionproduced by · A partition is a distinct subdivision of a larger data, storage, or work unit that can be stored, managed, or processed separately.
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