Performance New Added 2 October 2026

Go: high tail latency in a container, GOMAXPROCS above the CPU limit

Before Go 1.25, GOMAXPROCS defaulted to the number of CPUs on the node and ignored the container's CPU limit. A pod limited to 2 CPUs on a 64 core node would run 64 threads, burn through its CFS quota in a few milliseconds and then be throttled for the rest of the period. Go 1.25 reads the cgroup limit, but only when go.mod says go 1.25 or later.

Quick fix

Read the commands before running them. Anything that restarts a service, deletes data or changes permissions should be tried on a non-production system first.

Quick fix

# What does the process use? Log it at startup:
#   log.Println("GOMAXPROCS", runtime.GOMAXPROCS(0))

# Is it throttled?
cat /sys/fs/cgroup/cpu.stat | grep throttled

# Fix 1: build with Go 1.25+ and set go 1.25 in go.mod
go mod edit -go=1.25

# Fix 2 (older Go): set it from the limit
env:
  - name: GOMAXPROCS
    valueFrom:
      resourceFieldRef: { resource: limits.cpu }

How to diagnose 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.

If the quick fix above does not resolve it, work through these steps. They apply to this whole class of error, not just to this one message, which is usually what saves the time.

Measure the p99, not the mean. Averages hide exactly the pauses that cause timeouts.
For the JVM, enable GC logging (-Xlog:gc*) and correlate pause durations with latency spikes before tuning anything.
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.
In Node.js, measure event loop lag directly (perf_hooks.monitorEventLoopDelay). Any synchronous work over a few milliseconds per request will show up here.
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*

Authoritative references

Primary documentation for this error, worth reading before applying any fix in production.

go.dev pkg.go.dev

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