exactly once

Pipelines fail and retry, so the real question is whether a retry corrupts your data. What interviewers look for is idempotent writes (not 'exactly-once delivery') alongside watermarks for late data. Here is how to keep re-runs safe without double-counting.

At-least-once creates duplicates and at-most-once drops data; everyone asks for exactly-once yet few can explain how Kafka provides it. The signal is idempotent producers, transactional read-process-write, and the read-committed isolation that binds them together.

In payments, a duplicate charge or a lost credit is not a bug, it is a financial incident. The design turns on idempotency keys, double-entry bookkeeping, and an append-only ledger you can audit and reconcile. Here is how money systems stay correct.

Background jobs fail, retry, and get redelivered. If a job sends an email or charges a card, running it twice is a real problem. The design combines at-least-once delivery with idempotent handlers, visibility timeouts, and dead-letter queues. Here is how to make jobs safe.