What to Do If Your Application Causes High Load in Kubernetes

When an application inside your Kubernetes cluster starts consuming too much CPU or memory, it can lead to degraded node performance, evicted pods, or even node instability. Here’s how to troubleshoot and fix it.

1. Identify the Culprit

Use kubectl top to check which pods are consuming the most resources:

kubectl top pods --all-namespaces

To dive deeper:

kubectl describe pod <pod-name> -n <namespace>

Check for high CPU/Memory and events like OOMKilled.

2. Check Resource Requests and Limits

Ensure your pods have appropriate resource requests and limits set:

resources:
  requests:
    cpu: "200m"
    memory: "256Mi"
  limits:
    cpu: "500m"
    memory: "512Mi"

Pods without limits can consume all available resources on a node.

3. Use Resource Quotas and LimitRanges

To prevent future issues, configure LimitRange and ResourceQuota in your namespace.

kubectl create quota dev-quota --hard=cpu=2,memory=4Gi --namespace=dev

4. Enable HPA or VPA

Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) can help manage dynamic load.

kubectl autoscale deployment my-app --cpu-percent=80 --min=1 --max=5

5. Profile the Application

Use tools like:

  • kubectl exec + top or htop
  • Application-level profiling (e.g., Java Flight Recorder, Go pprof)
  • Logging and metrics via Prometheus + Grafana

6. Optimize the Code

Common issues:

  • Inefficient loops
  • Blocking I/O
  • Memory leaks
  • Missing connection pooling

Fix the code and redeploy.

7. Consider Resource Classes

Use node selectors or taints/tolerations to isolate heavy workloads.

nodeSelector:
  workload: high-performance

Conclusion

High load from an application in Kubernetes usually stems from lack of resource control or inefficient code. With the right monitoring and Kubernetes configuration, you can contain and resolve these issues effectively.