Retries

Software Engineering 12 Sep 2026 8 min read

Retry Amplification and the Role of Jitter

Retry Amplification and the Role of Jitter A failed request can create more traffic than a successful one. If a caller immediately repeats an operation after a transient error, the original unit of demand becomes two attempts. Add another retrying layer above that caller, and a single logical request can fan out into several physical attempts before any component has recovered. Retries are often described as a way to tolerate temporary faults. That description is incomplete because retry behavior also changes load. The mechanism sits inside a feedback loop: failure triggers another attempt, another attempt consumes capacity, and consumed capacity can affect the conditions that produced the failure.

Software Engineering Distributed Systems

Go 01 Sep 2026 6 min read

Exponential Backoff with Jitter in Go

Retries can make distributed systems more resilient, but immediate retries can also make an outage worse. If thousands of clients retry at the same moment, a recovering dependency receives another synchronized burst of traffic before it has time to stabilize. A common solution is exponential backoff with jitter: increase the maximum delay after each failure, then randomize the actual wait. This article builds that pattern with Go’s standard library and shows where retry logic belongs—and where it does not.

Golang Retries