What is a Retry Logic?

Many failures in distributed systems are transient: a network blip, a momentarily overloaded server, a brief database lock. Failing the entire operation on the first error, when a second attempt a moment later would likely succeed, produces unnecessary user-facing errors. Retry logic re-issues the failed call automatically, usually with exponential backoff (waiting progressively longer between attempts) and jitter (a small random delay) so that many clients retrying simultaneously don't all hammer the recovering service at the exact same instant and cause a second wave of failures. Good retry logic distinguishes between retryable and non-retryable failures: a rate-limit response or a timeout is worth retrying, but a validation error or an authorization failure will fail identically every time and should surface immediately rather than being retried pointlessly. Retries also need to respect idempotency — retrying a payment charge without an idempotency key, for instance, risks charging a customer twice — so retry logic and idempotent operation design are usually built together. Retry logic is the safety net beneath rate limiting and queue-based automation alike: when a downstream call is throttled or a worker crashes mid-job, retry logic is what turns that into a delayed success instead of a lost task.