A client retry created duplicate records in production. How would you investigate and prevent it?

Duplicate resource created after a client retry

Investigate and fix an API where client retries create duplicate orders, payments, or records.

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I first identify what was duplicated, how many records are affected, and whether there were external side effects like payments or messages. Then I check logs, timestamps, client retry behavior, and whether the API had idempotency keys or uniqueness constraints. I would contain the issue before cleanup. Then I would plan safe data repair.

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idempotency, unique constraints, retry behavior, request logging, side effects, and data repair planning

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Why this question matters
Investigate and fix an API where client retries create duplicate orders, payments, or records. It matters in real backend work because the team needs observability, ownership, and rollback room to recover without guessing. The practical angle is idempotency, unique constraints, retry behavior, request logging, side effects, and data repair planning, tied to a concrete production decision.
I first identify what was duplicated, how many records are affected, and whether there were external side effects like payments or messages. Then I check logs, timestamps, client retry behavior, and whether the API had idempotency keys or uniqueness constraints. I would contain the issue before cleanup. Then I would plan safe data repair.
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This often happens when the server commits the operation but the client times out before receiving the response. The client retries and the API treats it as a new request. I prevent that with idempotency keys, unique business constraints, or both. The trade-off is extra storage and logic, but it is much safer than assuming network calls happen exactly once.

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Details

Deleting duplicate rows without understanding side effects
Blaming only the client
Using in-memory duplicate checks
Relying on disabled buttons
Not adding unique constraints where appropriate

A client retry created duplicate records in production. How would you investigate and prevent it?

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