In distributed systems, the guarantee of "exactly-once" processing is a myth when side effects are involved. While Kafka Streams offers exactly-once semantics for internal state, this guarantee evaporates the moment your service needs to make an external HTTP call (e.g., charging a credit card via Stripe) or write to a database that isn't part of the transaction log. The default delivery semantic for Kafka is At-Least-Once . This means your system is architecturally destined to process duplicate messages. Without an idempotency strategy, you risk data corruption and financial loss. The Root Cause: Why Duplicates Occur To solve duplicate processing, we must understand where the duplicates originate. They primarily stem from two failures in the commitment protocol: Producer Retries (Network Jitter): A producer sends a message to the broker. The broker writes it successfully, but the network acknowledgement (ACK) fails to reach the producer. The producer, assuming failur...
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