An idempotency header can help an API recognize a repeated request, but it does not make an entire workflow execute only once. Safe retries require separate protections at each boundary: HTTP method semantics, a durable record for the logical operation, concurrency-safe mutation handling, and duplicate detection in message consumers and downstream services.
What HTTP idempotency does—and does not—mean
RFC 9110 defines an idempotent method by its intended effect: sending the same request multiple times has the same intended effect on the server as sending it once. PUT, DELETE, and safe methods are idempotent under the standard. This is a property of the requested effect, not a promise that every internal side effect occurs once; a server may log each request or record multiple revisions.
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The standard gives clients a protocol-level basis for retrying, not an application-wide deduplication system. A POST endpoint can be implemented so the same logical operation is safe to repeat. Conversely, a PUT endpoint might trigger an email, payment, or downstream job that needs its own duplicate protection. The method name alone does not describe the endpoint’s entire side-effect chain. A client should not automatically retry a non-idempotent request unless it knows the operation is actually idempotent or can determine that the original request was not applied.
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Give each logical mutation a durable identity
For a mutation that might be retried, use one stable identifier for the logical operation—not a new identifier for each network attempt. The service can use it to distinguish a new operation, one currently being processed, and one already completed. For a completed operation, it can return the saved result rather than perform the mutation again. AWS reliability guidance describes this lookup-and-replay pattern and recommends coordinating token recording with the mutation using mechanisms such as transactions, locks, or optimistic concurrency control.
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The important design question is not simply where to accept a key, but how its record and the business change stay consistent. If two requests with the same key arrive together, both must not observe “new operation” and independently apply the mutation. If the service crashes between recording the key and applying the change—or between applying the change and saving the result—the recovery path must still be unambiguous. Choose storage and transaction boundaries that make those states explicit.
Set a clear key contract
- Scope: Define which caller and business operation the key identifies. Scope it so unrelated customers or operations cannot collide.
- Payload matching: Do not silently treat the same key with different parameters as the same request. Reject a mismatch or define another explicit conflict behavior.
- Retention: Keep deduplication state for the period in which retries or replays are expected. After that period, a repeated key may no longer protect the operation.
- Exposure: Avoid putting sensitive information in the key itself; treat it as an opaque identifier.
- Replay response: Specify whether a repeat returns the original status and body, a current resource representation, or another documented result.
These are application contract choices, not universal properties of idempotency keys. Clients must follow the specific API’s scope, mismatch, and retention rules.
Carry the identity into queues and downstream calls
An HTTP request may enqueue work that is delivered more than once. Retries, redelivery, or multiple consumers can cause a message to be processed again even when the initial API request was handled safely. AWS guidance recommends identifying messages, tracking processed work in consumers, and propagating the operation identity to downstream services. Its Lambda and DynamoDB guidance describes persistent transaction attributes and conditional writes as ways to reject duplicate mutations.
Trace one operation through the whole path: client, API, database, queue, consumer, and any external provider. At every boundary, decide what identifier survives, where completion is recorded, and what the system should do if it restarts at that point. An HTTP header does not automatically become a queue deduplication record or a provider request key; the application must deliberately map and propagate the operation identity.
Check every failure boundary
- Before the API mutation: A retry can be treated as a new attempt only if no effect has yet been accepted, or if the same stable key lets the API determine the existing operation.
- After the database commit but before the response: The caller may not know whether the mutation succeeded. A repeat should retrieve the recorded outcome rather than apply it again.
- After enqueueing but before acknowledging: The queue can redeliver. The consumer needs durable duplicate detection, not just an in-memory flag.
- After an external effect but before recording success: The caller may be unable to tell whether the provider completed the action. Recovery may depend on the provider’s idempotency contract, a stable business reference, a query or reconciliation path, or workflow-specific compensation.
There is no universal fix for the last case. The design must match the external system’s capabilities and the consequences of repeating or not repeating the effect.
Exactly-once delivery is not an end-to-end guarantee
Idempotency can ensure that repeated attempts within a defined operation scope do not change the outcome beyond the first accepted operation. It does not make a transport deliver a message exactly once, nor does it guarantee that a multi-service workflow executes only once. AWS’s durable execution guidance explains that retry semantics apply per attempt and do not by themselves provide an end-to-end exactly-once workflow; interrupted work may run again.
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Design retry behavior around the side effect. If repeating it is safe because the receiving service deduplicates a stable operation identity, retrying may be appropriate. If a single execution attempt is the intended policy, use a no-retry strategy and plan how to detect and resolve an uncertain outcome. “Exactly once” should describe a carefully bounded business guarantee, not an assumption about the whole network path.
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Stripe’s idempotent request documentation is one concrete provider contract, not a general rule for all APIs. Stripe says it saves the first status code and response body for a key, including a 500 response, and returns that saved result on later requests with the same key. It compares the new request’s parameters with the original and errors when they differ.
Stripe also says keys can be pruned once they are at least 24 hours old; reusing a pruned key creates a new request. It does not save a result when validation fails or when a concurrent request conflict prevents endpoint execution. These details affect how a client should retry and how long it can rely on a key. For any provider, check its current documentation rather than assuming another service follows Stripe’s behavior.
Quick Recap
A practical design checklist
- Identify the business operation whose duplicate execution would cause harm.
- Assign a stable operation key and define its caller scope, payload-mismatch behavior, and retention period.
- Persist operation state so concurrent requests cannot both perform the mutation; coordinate the state change and business effect with transactions or an appropriate concurrency-control mechanism.
- Save enough outcome data to respond safely to a repeat after the original request has completed.
- Propagate the operation identity into queued messages and downstream calls, and give each consumer durable duplicate detection.
- For external effects, document the uncertain-outcome recovery path: provider idempotency, lookup and reconciliation, or a defined compensation.
- Set retries according to the effect and the system’s actual guarantees; do not infer end-to-end exactly-once execution from an HTTP method or header.
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