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

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

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

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

Kafka's `seek()` lets you replay only specific messages, saving time.

Kafka's pause temporarily stops reading messages, while seek changes the reading position.

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

Kafka consumers can pause and resume message processing to handle backpressure effectively.

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

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

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

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

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