Debugging & Troubleshooting: Scenario-Based Questions

Intermittent 500 Internal Server Errors can be challenging as they do not consistently occur. A methodical approach is required to isolate and resolve the root cause.

🔍 Step-by-Step Investigation

• Check Application Logs: Look for stack traces, uncaught exceptions, or timeout warnings around the timestamps of the errors.
• Enable Debug Logging (Temporarily): Add more context if logs are insufficient.
• Review Web Server Logs (e.g., Nginx, Apache): Validate that the server isn’t rejecting upstream responses or hitting timeouts.
• Correlate with Metrics: Use APM tools (Datadog, New Relic, Prometheus) to detect memory spikes, CPU pressure, or error rate anomalies.
• Check Load Balancer Health: See if specific instances are more error-prone (implying node-level problems).

🛠 Common Root Causes

• Uncaught Exceptions: Unhandled edge cases in code (e.g., division by zero, null dereferencing).
• Resource Exhaustion: Insufficient memory/CPU causing thread starvation or service crashes.
• Timeouts: Upstream services (DB, APIs) not responding in time.
• Code Deploy Regressions: Recently deployed features or patches introducing bugs.

🧪 Example Commands and Tools

• journalctl -u myservice: System log inspection on Linux.
• docker logs [container_id]: View logs of Dockerized services.
• kubectl logs pod-name: For Kubernetes environments.
• Check tracing tools: e.g., Jaeger or OpenTelemetry traces for request spans.

✅ Resolution & Best Practices

• Fix the root cause in code and write regression tests for it.
• Introduce circuit breakers or retry mechanisms where applicable.
• Set alerts for error rates exceeding thresholds (e.g., >1% 500s).
• Document the root cause and remediation in a shared incident report.

🚫 Common Pitfalls

• Restarting services without identifying the root cause.
• Ignoring random errors assuming they’re “glitches.”
• Lack of correlation between monitoring and logs.

📌 Real-World Insight

At many tech companies, identifying the root cause of 500s is seen as a test of operational maturity. Having structured incident response and good observability greatly accelerates root cause identification.