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A reliable API integration should retry only when the operation is safe to repeat, the failure may be temporary, and another attempt fits within a defined time and load budget. A timeout does not prove the server did nothing: it may have completed the work before the response was lost. The key design question is therefore not just how many times to retry, but whether repeating this particular operation can cause duplicate effects.
When should an API request be retried?
Retry when the error is plausibly temporary, the operation can safely be repeated (or the API provides a safeguard), and another attempt fits within the request’s deadline. Do not retry every error simply because it looks like a network problem. A failed response or missing response can leave the operation’s outcome unknown.
A request may fail before it leaves the client, in transit, after the server receives it, or after the server finishes the work but before its response reaches the client. If the client sees a timeout or dropped connection, it may not know which point was reached. Repeating a write in that situation can create a duplicate action, such as a second charge or record.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11RFC 9110, the HTTP Semantics standard, allows automatic retry of idempotent requests when a connection fails before a response arrives, but cautions against automatically retrying non-idempotent requests without a safeguard. Decide based on the operation’s effects, not just the transport error.
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Can the operation be repeated safely?
Idempotency describes the intended effect of repeated identical requests: making the request multiple times has the same intended effect as making it once. RFC 9110 identifies PUT, DELETE, and safe methods as idempotent. This is a useful baseline, not a guarantee that every endpoint behaves correctly in practice; consult the API contract for the operation you are calling.
The method name alone does not make a POST operation safe to repeat. An API can define a POST operation as repeatable through its contract or safeguards, but a client needs to know that before retrying after an ambiguous failure. RFC 9110 says a client should not automatically retry a non-idempotent request unless it knows that the semantics are actually idempotent or can detect that the original request was never applied.
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Before enabling retries for a write, establish what the API guarantees when the same operation is submitted again. If it does not provide a documented way to prevent or detect duplicate effects, treat an uncertain outcome as unresolved rather than assuming a retry is harmless. Provider-specific idempotency-key behavior is not universal; follow that provider’s current documentation.
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Retry only errors that the endpoint’s contract identifies, or that your integration can reasonably classify, as transient. AWS Prescriptive Guidance on the retry-with-backoff pattern discusses temporary service unavailability and throttling, including HTTP 429, as possible retry contexts. It also recommends failing fast when an error is known to be non-transient.
There is no universal status-code list that makes a retry safe for every API. A 429 may signal throttling, while a 503 may indicate temporary unavailability, but the right response and timing depend on the endpoint and provider. Authorization, validation, conflict, and rate-limit errors can also have API-specific meanings. Check the current API documentation rather than applying a blanket rule to all endpoints.
- Potentially transient: temporary service unavailability or throttling, when the API’s contract and the operation’s safety permit another attempt.
- Usually not helped by repetition: a known permanent failure, such as an invalid request or credentials that need correction. Fix the cause instead of sending the same request again.
- Outcome unknown: a timeout or lost connection after sending a non-idempotent request. Do not infer that the operation was never applied.
How should a retry schedule work?
Use progressively longer waits between attempts rather than sending them in rapid succession. Exponential backoff increases the wait across attempts; jitter adds variation to those waits so many clients are less likely to retry in lockstep. AWS recommends backoff, jitter, retry limits, and a maximum elapsed time as ways to avoid adding load to a service that may already be strained. See its guidance on controlling and limiting retry calls.
There is no standard universal number of attempts or single timing formula. Choose limits that fit the request deadline, the service’s behavior, and the business cost of delay or failure. Bound both the number of attempts and the total time spent retrying: a retry loop that can wait indefinitely may hold work open, consume resources, and make recovery slower.
Respect Retry-After
RFC 9110 defines the Retry-After header as either an HTTP date or a delay in seconds. The server uses it to indicate how long the user agent ought to wait before a follow-up request. Parse the value and incorporate it into the retry schedule, while keeping the overall deadline and retry policy in force. A server’s timing instruction does not require a client to retry beyond its own limits.
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What should an integration do when retries run out?
Retries are a bounded recovery measure, not a promise that every request will eventually succeed. Decide what the caller or operator should see when the deadline or attempt limit is reached, and make the final failure distinguishable from the individual attempts that preceded it.
- Set an overall deadline and an attempt limit appropriate to the operation.
- Record enough information to identify the operation, the failure class, the number of attempts, and whether the outcome is known or uncertain.
- Define what happens to unsuccessful work after the retry budget is exhausted. Queueing, dead-letter handling, and reconciliation may be appropriate, but their design depends on the system and is not a universal retry rule.
Retries consume bandwidth and other resources, can worsen degradation, and increase the time a user waits. Monitoring exhaustion and failure classes helps distinguish a transient recovery from a persistent integration or service problem; repeating requests without those bounds can turn a small disruption into additional load.
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