Kafka delivers messages like clockwork, but loves duplicates: idempotency or bust your production nightmare

Kafka, a popular messaging system, guarantees delivery of messages but not uniqueness, leading to potential duplicates during retries. This is a deliberate design choice, prioritizing reliability over uniqueness to prevent data loss. To address this, developers can implement idempotency, which ensures that processing a message multiple times has the same effect as processing it once. Producer-side idempotency in Kafka prevents duplicate writes, but it does not guarantee uniqueness across different producers or at the consumer level. Application-level idempotency, which assigns a unique identity to each event, is necessary to detect duplicates. Consumers must also implement idempotency to prevent duplicates from causing incorrect side effects. While achieving "exactly-once" delivery is a practical goal, it is not a mathematical guarantee due to the complexities of distributed systems. By designing systems with idempotency in mind, developers can ensure correctness and prevent errors, even in the presence of retries and duplicates.