Q: You see high CPU usage in one pod, but logs look clean. What next?
Root cause analysis workflow for diagnosing a Kubernetes pod pinning 100% CPU when application logs contain zero errors or anomalies.
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🛠️ Production Runbook & Step-by-Step Resolution
Identify Whether All Cores or Single Core Are Pinned
Exec into the pod or the underlying host node. Run `top` or `htop` and press `1` to see per-core CPU usage, and `H` to show thread-level CPU usage. Identify the exact thread ID (TID) consuming the CPU.
kubectl exec -it <pod-name> -- top -H
# Note the high CPU PID/TID: e.g. PID 42 using 99.8% CPUCapture Thread Dumps or CPU Stack Traces
Convert the thread ID to hexadecimal and inspect thread stacks:
- **Java / JVM**: Use `jstack
# For JVM:
printf "%x\n" 42 # Output: 2a
jstack <pid> | grep -A 20 "nid=0x2a"
# For Go:
curl http://localhost:6060/debug/pprof/profile?seconds=30 > cpu.pprof
go tool pprof -http=:8080 cpu.pprofCheck Garbage Collection Thrashing & Memory Pressure
Inspect memory allocation. If the application heap is 98% full and JVM Garbage Collector threads (`VM Thread`, `GC task thread#0`) are running continuously attempting to reclaim unreachable objects, CPU will pin at 100% while application code is suspended.
jstat -gcutil <pid> 1000 5
# Inspect FGC (Full GC count) and FGCT (Full GC time)Inspect Kernel Syscalls with strace / perf
If thread dumps cannot be gathered, attach `perf` or `strace` from the node to see what system calls the thread is executing (e.g. spinning on `futex` or non-blocking socket reads).
- Run top -H inside the container to identify the exact thread ID (TID) consuming CPU.
- Capture thread dumps (jstack) and correlate the hex TID to find the exact code line.
- Verify memory utilization to rule out continuous JVM Garbage Collection thrashing.
- Preserve thread dumps and heap telemetry for post-incident root cause analysis before pod restarts.