Linux Process Stopped Suddenly? Here’s How you Debug Like an SRE Pro! 🚨

Have you ever faced a situation where a critical Linux process performing computations and writing to disk just… stopped? As an AWS DevOps & SRE expert, I’ve encountered this in production systems. Troubleshooting quickly is crucial. Here’s my step-by-step approach to diagnose and resolve such incidents:

🔍 Step 1: Is the Process Still Running?

• Check if it crashed:
• ps aux | grep process_name
• pgrep -fl process_name – Double-check memory presence.
• Look for system messages:
• dmesg -T | tail -50 – Check for segmentation faults or OOM kills.

💡Ask: Why did it stop if missing?

🔍 Step 2: Check System Logs for Clues

• Inspect recent logs:
• journalctl -xe --no-pager -n 50
• tail -f /var/log/syslog

💡Check for: SIGKILL or SIGTERM – was it manually stopped or system-killed?

🔍 Step 3: CPU & Memory – Was It Overloaded?

• Analyze resource usage:
• top -o %CPU
• top -o %MEM
• dmesg | grep -i "oom" – Termination by OOM Killer?

💡Consider: Scaling up or optimizing if killed due to resource exhaustion.

🔍 Step 4: Disk Issues – Is It Full or Too Slow?

• Examine disk status:
• df -h
• iostat -xm 1
• dmesg | grep -i "error"

💡Decide on: Cleaning up, expanding storage, or optimizing writes.

🔍 Step 5: Are There Locked or Deleted Files?

• Identify file issues:
• lsof -p <PID>
• lsof | grep -iE "deleted|locked"

💡Determine if: Locks need releasing or dependent processes need restarting.

🔍 Step 6: Was It Killed by an External Source?

• Check for external kills:
• journalctl -u process_name --no-pager -n 50
• lastcomm | grep process_name

💡Assess: Intentional stop or monitoring tool misfire.

🔍 Step 7: Real-Time Debugging – What’s It Doing?

• Inspect live process state:
• strace -p <PID>
• gdb -p <PID>

💡Decide: Whether to restart, reconfigure, or investigate further if hung.

🔥 Final Thoughts – Why This Matters!

As an SRE & Cloud Expert, ensuring high availability, reliability, and observability is critical. Efficiently debugging failures is key, whether on AWS, Kubernetes, or high-performance computing workloads.