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Performance New Added 17 October 2026

INFO: task kworker blocked for more than 120 seconds

The hung task detector found a process stuck in uninterruptible sleep (D state) for two minutes, almost always waiting on I/O. The task it names is the victim, not the cause: look at the storage behind it. Typical culprits are an NFS or iSCSI server that went away, a saturated or failing disk, or a huge dirty page cache being flushed all at once on a machine with lots of RAM.

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
# The stack trace under the message shows what it was waiting for
dmesg -T | grep -A20 "blocked for more than"

# Which processes are in D state right now?
ps -eo pid,stat,wchan:32,cmd | awk '$2 ~ /D/'

# Is a disk saturated (util near 100%, high await)?
iostat -xz 2 5

# Hung network mounts show up here
mount -t nfs,nfs4,cifs; timeout 5 stat /mnt/share || echo "mount not responding"

# Large writeback stalls: flush earlier and in smaller chunks
sysctl vm.dirty_ratio vm.dirty_background_ratio
sudo sysctl -w vm.dirty_background_bytes=268435456 vm.dirty_bytes=1073741824

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 docs.kernel.org

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