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Retries are safe only when every layer that can repeat work recognizes the same logical operation and handles it consistently. An HTTP method’s idempotency semantics help guide client retries, but they do not deduplicate a business operation across an API, database, queue, worker, and external provider. That requires durable operation identity, concurrency-safe state, and duplicate handling at each boundary.
What HTTP idempotency does—and does not—mean
Under RFC 9110, Section 9.2.2, a method is idempotent when multiple identical requests have the same intended effect on the server as one request. PUT, DELETE, and safe methods are idempotent by that definition. It concerns the requested effect, not every consequence of handling a request: a server may log each attempt or create revision-history entries.
This protocol-level property helps a client decide whether it can repeat a request after an uncertain outcome. A client should not automatically retry a non-idempotent method unless it knows the operation is actually idempotent or can determine the original request was not applied. Conversely, a POST endpoint can be designed to make repeated requests safe. The method name alone does not reveal whether downstream effects—such as sending a payment or publishing a message—are protected against duplicates.
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For a mutation that may be retried, use an application-level operation key that stays the same across attempts. It identifies one intended business action, not one HTTP connection or network attempt. The service needs enough durable state to distinguish a new operation, one still in progress, and one already completed.
A typical flow is to look up the key, return the saved outcome if the operation is complete, and otherwise coordinate recording the key with applying the mutation. AWS guidance on making retries safe describes this pattern and the need for transactions, locks, or optimistic concurrency control where necessary. Without coordination, two simultaneous requests can both observe an unused key and apply the mutation twice.
- Choose the scope deliberately. Scope a key to the caller and business operation where appropriate, so unrelated actions cannot collide.
- Bind it to the request meaning. Reusing a key with different parameters can be ambiguous or dangerous. Define whether mismatched parameters are rejected.
- Retain state for the retry window. Decide how long a key and its outcome remain available; after expiration, a delayed retry may be treated as new.
- Keep keys non-sensitive. Do not encode private identifiers or secrets in a value that may appear in logs or diagnostics.
Key scope, conflict handling, and retention are application-contract choices, not universal properties of idempotency keys.
Carry the operation identity across asynchronous work
An HTTP request may enqueue work that is delivered more than once. Queue or stream delivery guarantees do not by themselves prevent a consumer from applying a duplicate mutation. AWS Lambda best practices discusses duplicate events and idempotent processing; AWS transactional outbox guidance covers reliable propagation of database changes to messages.
Trace a single operation through each boundary:
- Client to API: the client creates or receives a stable operation key and reuses it for retries of that same intended action.
- API to database: the API atomically associates the key with the mutation and its result, or uses concurrency control that prevents duplicate application.
- Database to queue: the message carries the operation identity (or a stable event identity linked to it). Do not assume an HTTP header is automatically propagated.
- Queue to consumer: the consumer records processed identities durably and checks them before applying the effect. Redelivery should produce a safe replay or a no-op, not a second mutation.
- Consumer to another service: pass an appropriate stable identity downstream and follow that service’s own deduplication contract.
At each step, define what happens if a process crashes after an effect succeeds but before success is recorded. For a database mutation, a transaction may make the mutation and deduplication record atomic. For an external call, the local database cannot generally make the remote effect and local record one atomic transaction; recovery needs a contract or reconciliation strategy.
Why this is not end-to-end “exactly once”
Idempotency can make repeated attempts within a defined scope produce no additional business effect. It does not mean messages are delivered once, nor does it guarantee that a multi-service workflow executes only once. AWS’s durable execution guidance distinguishes retry behavior per attempt and warns that neither retry semantics alone guarantees an end-to-end exactly-once workflow; interrupted work may run again.
For an external side effect, a particularly important failure window is: the provider completes the request, then the calling service crashes before saving that success. Retrying may repeat the effect unless the provider recognizes a stable idempotency key or business reference. Depending on the provider and workflow, safe recovery may require querying the original operation, reconciling state, or applying a workflow-specific compensation. There is no single mechanism that resolves this window for every external system.
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Provider keys follow provider-specific contracts
Stripe’s idempotent request documentation is one concrete example, not a template that applies to all APIs. Stripe documents that it saves the first status code and response body for a key, including a 500 response, and replays that result on later requests using the key. It compares parameters with the original request and errors if they differ. It may prune keys after they are at least 24 hours old; reusing a pruned key creates a new request. Stripe also says it does not save a result when validation fails or a concurrent request conflict prevents endpoint execution.
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Quick Recap
Best Value
A practical retry-safety checklist
- Define the business operation that must not be duplicated, independently of the transport request.
- Use one stable identity for retries of that operation, and specify its scope and retention.
- Make the deduplication record and local mutation concurrency-safe.
- Persist or propagate the identity through messages and downstream calls; implement duplicate detection in consumers.
- For each external side effect, identify the crash window and specify provider-key behavior, a query/reconciliation path, or a workflow-specific recovery policy.
- Set retry behavior around the side effect. If policy requires one execution attempt, use a no-retry strategy rather than assuming idempotency or transport guarantees will enforce it.
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