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Kafka Delivery Semantics clarifies when events may be duplicated or lost under retries, partitioning, and failures. The focus is on producer settings, consumer offsets, transactions, and idempotence so consumers can achieve consistent processing despite concurrent event streams.
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Kafka delivery semantics describe whether a message is processed never, once, or potentially more than once under defined failure conditions.
The semantics grew from the need to make delivery risks in distributed messaging explicit. Apache Kafka first centered on at-least-once processing and added idempotent producers and transactions to provide stronger exactly-once guarantees within defined boundaries.
Imagine a parcel service: without an acknowledgement a parcel may vanish, retries may deliver it twice, and acknowledgement plus idempotency can make a retry safe to recognize. Kafka combines such mechanisms through configuration.
It states which losses or duplicates system behavior permits.
It prevents send retries from writing the same message repeatedly to Kafka.
Delivery semantics help teams design failure behavior in event-driven systems deliberately. They connect producer, broker, and consumer settings to the business consequences of loss and duplication.
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