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What “duplicate alert” means determines the key
First define what should count as the same work. It could be the same source observation, the same underlying incident, the same notification to a recipient, or the same API call. Those are different identities: an incident may produce legitimate new notifications after it changes or is resolved, even if the source entity is unchanged.
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Decide whether an alert may recur after resolution, a state change, or a suppression window. The key must reflect that policy. A key that is too broad can suppress distinct work; one that includes attempt-specific data can allow every retry through.
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Choose a stable key for the logical operation
A key identifies the work, not the polling attempt. Reuse it for retries and replays of that same work. A useful conceptual shape is source + entity/event identity + operation/version. Add a time bucket only when the product definition treats work in separate buckets as distinct. This is design guidance, not a provider-mandated format.
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Prefer an immutable upstream identity
If the source supplies a trustworthy event ID that represents the unit of work, use it or derive a namespaced key from it. Google Cloud says a CloudEvent is considered a duplicate when its source and id match, and recommends using the event ID as an idempotency key for APIs that accept one. See Google Cloud’s retry guidance.
Derive a deterministic key when there is no event ID
For a polling API without event IDs, derive the key from immutable source identity and the intended operation or window. Do not use the time of each attempt: clock skew and collisions make timestamps risky, and a changing timestamp can turn a retry into apparently new work. AWS also warns against inconsistent key generation. Its Well-Architected guidance recommends unique tokens and passing them to downstream services that support idempotency.
Detect changed content under a reused key
The same key with the same business content is a duplicate. The same key with changed content is an integrity conflict, not an ordinary duplicate. Store or derive a canonical request hash, or compare immutable fields, and route mismatches to an error or dead-letter path for investigation rather than silently suppressing them. Stripe documents parameter comparison for its API: while a key is retained, a request using it with different parameters errors instead of being treated as the original request. That behavior is specific to Stripe, not a universal protocol.
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Use four states to define the work lifecycle
The following four-state model is a practical synthesis, not an industry standard or a protocol mandated by AWS. AWS describes tracking states such as pending, completed, and failed; “unseen” below means no durable record exists. A system may need additional states, such as terminal failure, or fewer, depending on its recovery semantics.
Unseen
No durable record exists for the logical key. A worker may attempt to claim it.
In progress
A worker has durably claimed the key. Other workers must not repeat the protected side effect; they can wait, skip, or inspect the result according to the policy. Define a lease, heartbeat, timeout, or safe reclaim rule so a crashed worker does not leave the item stuck forever.
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Completed
The durable outcome is recorded. A matching duplicate should return or reuse the stored result, or be acknowledged as a no-op, rather than sending the alert or repeating the protected side effect.
Failed/retryable
The attempt failed in a way that permits another attempt. Decide whether to retain the error and reclaim the record, transition it back to unseen, or use another explicit retry policy. A permanent data conflict should not be treated as transient work; route it to a terminal error path and make it visible.
Make claiming atomic, then record the outcome
A check-then-act sequence is unsafe: two pollers can both observe that a key is absent and both perform the work. Use a uniqueness constraint, atomic create, transaction, lock, or equivalent serialization mechanism supported by the store. The durable claim must be visible to every worker that can process the same key.
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- Read and identify: read the source item and derive its stable logical key.
- Claim atomically: create or claim the key as in progress. If another worker owns it, wait, skip, or consult its durable result under the lease and state policy.
- Perform protected work: only after the claim is durable, perform side effects. Pass the same key to downstream APIs that support idempotency.
- Commit the outcome: persist completion and its result. When possible, commit the dedupe record and related business writes together.
- Handle failure deliberately: retain enough state to retry transient failures safely. Quarantine and alert on changed payload under an existing key.
- Handle redelivery: for a completed key with matching content, return the stored result or acknowledge a no-op.
For synchronized writes, Microsoft’s Idempotent Consumer pattern describes placing the dedupe key and business documents in one transactional batch and partition. It also treats a uniqueness conflict as a duplicate only after comparing stored request data, avoiding a marker that says “done” while the corresponding business write was not committed.
Plan for crashes at each boundary
Crash after claim, before the side effect
The key may remain in progress although no alert was sent. An expiring lease, heartbeat, or safe reclaim procedure should let another worker resume without allowing two live workers to act concurrently.
Side effect succeeds, but completion was not recorded
A retry cannot infer from its own missing completion record that the side effect failed. Reuse the same downstream idempotency key if supported, or reconcile the downstream outcome before repeating the effect. Otherwise, duplicate side effects remain possible at that boundary.
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Two workers claim at once
Enforce uniqueness or equivalent atomic serialization in the shared store. A prior read that finds no record is not a claim.
A delayed replay arrives after the marker expires
The old work can run again if its dedupe record has been removed. Retention must cover the real retry and replay horizon, including manual backfills where relevant, and the record must be visible wherever processing can occur. Do not generalize one provider’s retention window to other systems.
A provider returns a cached failure
Check the provider’s documented semantics: an idempotency key may replay a saved failure rather than attempt fresh work. Stripe, for example, saves the first result after endpoint execution begins and returns that result for subsequent calls with the same retained key, including a 500 response. Stripe says keys may be pruned once they are at least 24 hours old; reuse after pruning can start a new request. Validation failures and certain concurrent execution conflicts are not saved as idempotent results. These are Stripe-specific behaviors, not general retention advice. See Stripe’s idempotent requests documentation.
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Retries and idempotency work together: retries help a system recover, while idempotency makes repeated attempts safe for a defined operation. Neither a retry policy nor a key alone makes every step across a distributed workflow execute once. A worker can protect its database write while a notification provider still receives a repeated request, unless that downstream boundary also supports idempotency or can be reconciled.
“In a distributed system, it is relatively simple to perform an action at most once (client makes only one request) or at least once (keep requesting until you get confirmation of success). It is more difficult to guarantee an action is performed exactly once, such that making multiple identical requests has the same effect as making a single request.” — AWS Well-Architected Framework, REL04-BP04
AWS Durable Execution documentation distinguishes at-least-once and at-most-once behavior per retry and cautions that neither by itself guarantees workflow-wide exactly-once execution. Its guidance demonstrates retaining the same token across replay. See AWS retry and idempotency guidance. State your guarantee narrowly: for example, “the alert record is written once per logical incident key” or “the downstream call is idempotent for this key while its provider retains the key.”
Quick Recap
Implementation checklist
- Define exactly what constitutes the same alert and when a legitimate repeat is allowed.
- Derive a stable key from immutable identity and the intended operation; reuse it across retries and replays.
- Use atomic uniqueness or equivalent concurrency control for the claim.
- Compare content when an existing key is presented; quarantine mismatches and make them observable.
- Define lease expiry, reclaim, retryable failure, and terminal failure behavior.
- Persist the result and related writes atomically where possible; propagate the key downstream where supported.
- Set retention according to the actual replay horizon, and document which operation boundary the deduplication protects.
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