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A write can commit on the server even when its response never reaches the caller. If the client retries that operation as new work, the service may apply the side effect twice. The fix is not simply to retry less: give each logical operation a stable identity, make the service handle repeats safely, and define exactly what a repeated request returns.
Why a timeout can turn one write into two
A timeout reports what the caller knows, not necessarily what the server did. The connection can fail after the server commits a write but before the caller receives confirmation. From the caller’s perspective, the outcome is unknown; the timeout alone does not establish that the write failed.
- The client submits a mutating request.
- The server performs the write or side effect.
- The response is delayed or lost, or the connection breaks.
- The client sees a timeout without knowing whether the write committed.
- If it resubmits the operation as a new request, the server may perform the side effect again.
This is why a retry is a delivery policy, not proof that the first attempt did nothing. AWS and Stripe both describe this ambiguous-failure problem in their guidance on idempotent APIs and idempotency.
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How to retry one logical write safely
Assign one stable operation key
Create a unique identifier for the logical operation and send that same identifier on every attempt. Do not generate a fresh key each time the client retries: a new key tells the service that the retry is different work and defeats deduplication.
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For example, a client might submit a payment-creation request with an Idempotency-Key. If the response is lost, it retries with the same key. The key identifies the operation, not just its payload. Two intentional requests with identical fields may represent two separate operations, so collapsing requests solely because their payloads match can be incorrect. AWS recommends a caller-provided request identifier and describes pairing it with caller identity to recognize repeats safely.
Make the write and deduplication decision consistent
The service must persist the operation’s deduplication state in coordination with the mutation. AWS’s design guidance says the token record and related mutations need ACID properties: the service should not record a token as completed without creating the resource, or create the resource without recording the token.
If the marker and the write are separate operations with no transaction or recovery mechanism, a crash between them can leave the service in a misleading state. It might report a request as already handled when no resource exists, or repeat a side effect because no marker was saved. For workflows that span services or external side effects, one database transaction may not cover the whole path; identify where the durable operation identity lives and how each side effect recognizes a repeat.
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Specify what a repeated key returns
Deduplicating the side effect is only part of the API contract. A repeated request can return the original stored result or a semantically equivalent result, depending on the API’s documented behavior. Callers need to know which behavior to expect.
Stripe’s API reference documents that subsequent requests with a given idempotency key return the first status code and body, including when the first result was a 500. Check the current Stripe idempotent-requests reference for the behavior of its API. Other services should document their own response behavior rather than assuming all keys work the same way.
What the key contract must define
A key needs a clear namespace and lifetime. Define how it is scoped so unrelated callers or operations do not collide, how long the service retains it, and what happens if the same key is reused with a different payload. These details are API-specific; there is no universal retention window or payload-mismatch rule established by the cited guidance.
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Document the contract where clients can rely on it: which mutating operations accept keys, how callers create and reuse them, whether a repeated request replays the original response or returns an equivalent one, and when a key stops being effective. If a client may retry after the service has forgotten a key, a delayed retry could be treated as new work, so retention and the caller’s retry horizon need to be considered together.
Retry only appropriate failures, and control the pace
Idempotency addresses repeated effects; backoff and jitter address retry load. Neither substitutes for the other. AWS and Stripe recommend exponential backoff and jitter to reduce synchronized bursts and avoid hammering a degraded service. AWS guidance also says retries should target transient errors and that retried operations need to be idempotent.
- Classify failures: retry only errors that may be transient and for which retrying is appropriate. A permanent validation or authorization failure generally needs a corrected request, not another attempt.
- Use backoff and jitter: increase the delay between attempts and vary it so many clients do not retry in lockstep. See the AWS retry with backoff pattern and exponential backoff and jitter guidance.
- Bound the retry window: choose attempt and elapsed-time limits that fit the operation and caller’s deadline. These are system-specific design choices, not universal values prescribed by the cited sources.
- Observe ambiguous outcomes: monitor timeouts, retries, repeated-key hits, and operations whose final outcome remains unknown. These signals help distinguish transport trouble from duplicate-effect defects.
Backoff reduces pressure on a struggling service; it does not make a non-idempotent write safe. The service’s operation-identity contract is what lets a retry avoid repeating the effect.
Why “exactly once” is not the right blanket promise
A distributed system can make a single request, or keep retrying until it receives confirmation, but guaranteeing that an action executes exactly once across failures is harder. AWS Well-Architected guidance recommends making mutating operations idempotent and reusing the same token for repeated requests; it does not treat a transport retry as an exactly-once guarantee. Describe the practical promise narrowly: repeated delivery with the same valid key has no additional side effect within the system’s documented scope and retention rules.
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