AdvancedTechnical
5 min
Investigating High CPU Usage in Kubernetes Pods
KubernetesPerformanceTroubleshooting
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Interview Question
Your production Kubernetes cluster shows unusually high CPU usage in multiple pods. Walk me through your investigation and mitigation steps.
Key Points to Cover
- Check resource requests/limits via kubectl describe pod
- Use metrics-server or Prometheus/Grafana dashboards for CPU patterns
- Check logs and profiling data for hot loops or unoptimized code
- Verify HPA configuration and scaling triggers
- Apply resource throttling or code optimizations as needed
Evaluation Rubric
Collects relevant CPU usage metrics30% weight
Identifies possible causes like loops or misconfigurations30% weight
Provides short-term remediation strategies20% weight
Suggests long-term prevention like HPA tuning20% weight
Hints
- 💡Check resource limits, HPA behavior, and code bottlenecks.
Common Pitfalls to Avoid
- ⚠️**Lack of Systematic Approach:** Randomly trying fixes or restarting pods without a structured investigation, which can mask the true problem or introduce new issues.
- ⚠️**Ignoring Application-Level Root Causes:** Focusing solely on Kubernetes infrastructure (e.g., scaling, limits) and overlooking inefficient code, unoptimized database queries, or excessive logging within the application itself.
- ⚠️**Insufficient Use of Observability Tools:** Failing to leverage comprehensive metrics (Prometheus/Grafana) and detailed logs to identify patterns, scope the problem, and gather essential context, instead relying on anecdotal evidence or basic `kubectl` commands.
- ⚠️**Neglecting Profiling for Deep Dives:** Stopping at log analysis or basic metrics when the root cause points to CPU-intensive code paths, without utilizing profiling tools to identify hot loops or unoptimized algorithms.
- ⚠️**Confusing Mitigation with Permanent Remediation:** Applying temporary fixes (e.g., scaling up, increasing limits) without understanding and addressing the underlying cause, leading to recurring problems or unnecessary resource consumption.
Potential Follow-up Questions
- ❓How would you proactively avoid similar spikes?
- ❓Which monitoring alerts would you configure?
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