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Kafka rebalances consumer groups to manage partition assignments effectively.

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

Kafka's subscribe() lets the group manage partitions, while assign() gives control to the application.

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

Kafka's parallel processing depends on partitions, not just consumers or threads.

Kafka Streams offers higher-level abstractions, while Kafka Consumer provides direct control.

Kafka consumers have three important states: Position, Committed Offset, and Application State.

Monitoring Kafka consumer lag helps prevent production problems by ensuring consumers keep up with message traffic.