Idempotency
Designing actions so they can run multiple times without creating duplicates or inconsistent state.
Idempotency ensures that running the same operation multiple times yields the same result—no duplicates, no corruption. It is crucial for retries and fault tolerance.
In operations, it prevents double-charging, duplicate records, or repeated notifications when APIs are retried or workflows resume after failures.
It fits into systems via idempotency keys, upserts, and checks before writes. Idempotent design makes automation safe under retries, backfills, and concurrent runs.
Frequently Asked Questions
How do I make an API idempotent?
Accept an idempotency key, store results by key, and return the same outcome on repeat calls. Avoid side effects without checking existing state.
When is idempotency most important?
During retries, backfills, concurrent processing, and multi-step workflows where steps may partially succeed.
How do I handle partial failures?
Use transactional writes where possible, or stage changes and commit atomically. On failure, ensure replays do not duplicate work.
Does idempotency slow systems down?
Minimal overhead for storing keys/checks. The reliability gain outweighs the small cost.
Can idempotency be applied to emails or notifications?
Yes—track sends per recipient/event and avoid resending unless explicitly allowed. Include dedupe keys in your messaging layer.
How do I test idempotency?
Call endpoints multiple times with the same key and varied timing. Simulate network retries and verify state remains consistent.
What about database operations?
Use upserts, unique constraints, and compare-and-set semantics. Avoid blind inserts without checks.
How long should I keep idempotency keys?
Long enough to cover retries and client timeouts—typically minutes to days, depending on use case and storage limits.
Can idempotency coexist with side effects?
Yes, if side effects are guarded by checks or compensating actions. Log external calls and avoid repeating them on retries.
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