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Performance 19 errors

Performance & Latency Errors

GC pauses, thread pool starvation and event loop blocking.

Understanding Performance errors

Performance failures rarely produce an error message. They produce timeouts elsewhere. The three classic causes are stop-the-world garbage collection, thread pool starvation (all workers blocked on I/O so new requests queue), and event loop blocking in single-threaded runtimes. All three look identical from outside: latency climbs, then upstream timeouts fire. Distinguishing them requires looking inside the process.

How to debug Performance errors

  1. Measure the p99, not the mean. Averages hide exactly the pauses that cause timeouts.
  2. For the JVM, enable GC logging (-Xlog:gc*) and correlate pause durations with latency spikes before tuning anything.
  3. For thread pools, log active versus queued task counts. A queue that grows while CPU is idle is starvation, and the fix is asynchronous I/O, not more threads.
  4. In Node.js, measure event loop lag directly (perf_hooks.monitorEventLoopDelay). Any synchronous work over a few milliseconds per request will show up here.
  5. Profile before optimising. pprof, async-profiler, py-spy and Chrome's profiler all point at the real hot path, which is rarely where intuition suggests.

Tools worth reaching for

  • async-profiler
  • go tool pprof
  • py-spy
  • perf_hooks.monitorEventLoopDelay
  • -Xlog:gc*

All 19 Performance errors

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