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

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

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

Kafka consumers can use multiple threads to speed up message processing, but it complicates ordering and offset management.

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

Kafka uses partitions to allow parallel processing while ensuring message order with keys.

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

Kafka's assign() method allows manual control of partition assignments for consumers.

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

Kafka's commitSync waits for confirmation, while commitAsync continues immediately.