The Queue is Durable. Your Worker is Not

Durable execution preserves queued work and step state, but it does not by itself ensure that application workers remain available, complete work promptly, or execute side effects exactly once during outages, deploys, bursts, and retries. The article distinguishes durable queues from worker availability and recommends diagnosing incidents through scheduled-versus-started runs and step completion metrics, while using live traces for immediate triage. It compares HTTP-based “serve” deployments, where load balancers and platform timeouts manage availability, with WebSocket-based “connect” workers, which support worker draining, version-aware rolling releases, and per-worker concurrency caps. Key resilience practices include keeping steps short, placing explicit timeouts on downstream calls, allowing pods enough graceful-shutdown time, deploying canaries with fast rollback paths, separating critical functions from bulk workloads, prioritizing and isolating latency-sensitive queues, applying tenant-specific concurrency controls, and batching or cancelling stale nonurgent work. Because failures and capacity rejections can re-run incomplete steps, external effects such as charges, inventory updates, and customer records must be idempotent, while p99 critical-path queue time is presented as a more useful indicator of burst-related risk than overall success rates.

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