Common GKE Issues and Solutions

1. Cluster Provisioning Failures

GKE clusters may fail to provision due to resource limitations, misconfigurations, or quota restrictions.

Root Causes:

• Insufficient resource quotas in Google Cloud.
• Invalid cluster configurations in gcloud CLI.
• Network or IAM policy restrictions preventing cluster creation.

Solution:

Check project quotas:

gcloud compute project-info describe --project=my-project

Ensure cluster configurations are correct:

gcloud container clusters create my-cluster --num-nodes=3 --region=us-central1

Verify IAM permissions:

gcloud projects get-iam-policy my-project

2. Pods Not Scheduling

Pods may get stuck in Pending state due to resource constraints, node selector conflicts, or taint restrictions.

Root Causes:

• Insufficient CPU or memory resources.
• Node affinity rules preventing scheduling.
• Taints applied without tolerations.

Solution:

Check pod scheduling status:

kubectl describe pod my-pod

Verify node resource availability:

kubectl describe nodes

Remove taints if they are blocking pod scheduling:

kubectl taint nodes node-name key=value:NoSchedule-

3. Network Connectivity Issues

Network failures in GKE can cause pods, services, or ingress controllers to become unreachable.

Root Causes:

• Incorrect Network Policy blocking traffic.
• Misconfigured firewall rules in Google Cloud.
• Issues with Kubernetes service types (ClusterIP, NodePort, LoadBalancer).

Solution:

Check firewall rules:

gcloud compute firewall-rules list

Verify Kubernetes service endpoints:

kubectl get services -o wide

Inspect Network Policies:

kubectl get networkpolicy -A

4. Persistent Volume Claims (PVC) Not Binding

Persistent storage may not attach correctly to pods due to storage class misconfigurations.

Root Causes:

• Incorrect StorageClass configuration.
• PV and PVC binding mismatch.
• GKE persistent disk quota exceeded.

Solution:

Check PVC status:

kubectl get pvc

Ensure the correct StorageClass is used:

kubectl get sc

Manually bind a PV to a PVC if needed:

kubectl patch pvc my-pvc -p '{"spec":{"volumeName":"my-pv"}}'

5. High Resource Usage and Performance Issues

GKE clusters may experience high CPU/memory usage, leading to performance degradation.

Root Causes:

• Pods consuming excessive CPU/memory.
• Lack of horizontal pod autoscaling (HPA).
• Unoptimized container images causing long startup times.

Solution:

Monitor pod resource usage:

kubectl top pods

Enable Horizontal Pod Autoscaling (HPA):

kubectl autoscale deployment my-app --cpu-percent=70 --min=2 --max=10

Use optimized base images for faster startup:

FROM gcr.io/distroless/base

Best Practices for GKE

• Regularly monitor cluster health using kubectl top and GCP metrics.
• Use Horizontal Pod Autoscaling to manage workloads efficiently.
• Implement proper Network Policies to control traffic flow.
• Set up logging and monitoring with Google Cloud Logging.

Conclusion

By addressing cluster provisioning failures, pod scheduling issues, network problems, persistent storage errors, and performance bottlenecks, developers can maintain a stable and scalable GKE environment. Implementing best practices ensures high availability and reliability.

FAQs

1. Why is my GKE cluster failing to provision?

Check resource quotas, IAM permissions, and ensure correct cluster configurations.

2. How do I fix pod scheduling issues in GKE?

Verify resource availability, node affinity rules, and remove unnecessary taints.

3. Why is my GKE service not reachable?

Inspect firewall rules, service configurations, and Network Policies.

4. How do I troubleshoot persistent storage issues?

Check PVC status, verify StorageClass configurations, and ensure PV bindings are correct.

5. How can I improve GKE performance?

Use Horizontal Pod Autoscaling, optimize container images, and monitor resource usage.