Any concept.
clear in 60 seconds.

Eager rebalancing revokes all assignments, while cooperative allows incremental changes.

Kafka rebalances consumer groups to manage partition assignments effectively.

Kafka rebalance can lead to lost or duplicated work if not handled carefully.

Kafka's static membership allows consumers to maintain stable identities, reducing unnecessary rebalances.

Kafka Rebalance Listeners help manage state during partition changes in consumer groups.

Kafka uses different strategies to assign partitions to consumers in a group efficiently.

Kafka consumer reprocessing involves safely replaying events to correct system states.

Kafka consumers resume processing from the last committed offset after a crash.

Distributed backpressure helps manage the flow of work between services to prevent overload.