Modern LLM serving is hard to tune because each deployment is a stack of interacting choices: model backend, tensor-parallel shape, prefill/decode split…
Stopping duplicate requests is only part of the idempotency problem. This piece looks at why replay windows should be based on business intent and workflow lifetime, not generic middleware defaults that happen to be easy to apply.