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Performance New Added 2 October 2026

watchdog: BUG: soft lockup - CPU#3 stuck for 22s!

A CPU spent over twice the watchdog threshold in kernel code without letting the scheduler run. On physical hardware that points to a driver or kernel bug. On a virtual machine it is usually the host: the vCPU was not scheduled because the host is overcommitted, or the guest was paused for a snapshot or migration, so the guest saw time jump.

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
# Read the trace that follows: which function was the CPU in?
sudo dmesg -T | grep -A 30 'soft lockup'

# VM: how much time is the hypervisor taking? (st column)
vmstat 1 10
mpstat -P ALL 1 5

# Correlate the timestamp with backups, snapshots or vMotion on the host

# The threshold in seconds (lockups fire at twice this)
cat /proc/sys/kernel/watchdog_thresh

# Bare metal: update the kernel and firmware, note the driver in the trace

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.

  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*

Authoritative references

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

docs.kernel.org

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