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Kafka uses retries and Dead Letter Queues to manage message processing failures.

Kafka can help ensure messages are processed once, but requires careful design.

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

Kafka uses retry topics and delayed retries to manage message failures efficiently.

Poison messages in Kafka can cause infinite retries, risking system stability.

Kafka producers use ACKs, retries, and idempotence to ensure reliable message delivery.

Kafka commit strategies determine how offsets are managed during message processing.

Kafka allows safe message reprocessing by resetting consumer positions without altering data.

Classifying failures and using controlled retries in Kafka prevents outages.

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

Kafka uses replication and in-sync replicas to ensure data is always available.

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

Kafka uses Dead Letter Topics to handle messages that repeatedly fail processing.