Kubernetes Mastery : Day 5 : Troubleshooting begins
Published in
2 min readMay 6, 2024
So, in this article we will be looking at some problems, solutions and resolutions and ofc commands to resolve it;
Issue 1 : Investigating Pod Startup Failure
Scenario: An application pod is failing to start, causing service downtime.
Troubleshooting Steps:
- Use the ‘kubectl describe pod’ command to inspect the pod’s status, events, and conditions.
- Check container logs using ‘kubectl logs’ to identify error messages or initialization failures.
- Review Kubernetes system logs (‘kubelet’, ‘kube-scheduler’, ‘kube-apiserver’) for any scheduling or runtime issues.
- Validate pod specifications (e.g., PodSpec, environment variables) against the deployment manifest for correctness.
- Utilize the Kubernetes API to retrieve additional information about the pod’s state and associated resources.
Resolution:
- Correct the misconfiguration in the pod’s deployment manifest.
- Verify the pod’s successful startup by monitoring its status and logs.
- Implement measures to prevent similar issues in the future, such as incorporating automated testing and validation into the CI/CD pipeline.
Issue 2 : Scaling Application Pods
Scenario: An application experiences increased demand, necessitating the scaling of its pod replicas.
Troubleshooting Steps:
- Monitor resource utilization metrics (CPU, memory) for application pods and cluster nodes using Prometheus and Grafana.
- Identify pod autoscaling events and scaling activities in Kubernetes events and logs.
- Evaluate the impact of increased demand on pod scheduling and cluster capacity.
- Review Kubernetes Horizontal Pod Autoscaler (HPA) configuration and metrics to ensure proper scaling criteria and thresholds.
Resolution:
- If manual intervention is required, manually scale the application pods using the ‘kubectl scale’ command or by updating the deployment’s replica count.
- Configure Horizontal Pod Autoscaler (HPA) to automatically adjust the number of pod replicas based on predefined metrics and thresholds.
- Monitor the effectiveness of autoscaling policies and adjust parameters as needed to optimize resource utilization and application performance.
Issue 3 : Debugging Network Connectivity Issues
Scenario: Pods within a Kubernetes service are unable to communicate with each other.
Troubleshooting Steps:
- Verify pod connectivity by attempting to ping or establish connections between pods using ‘kubectl exec’ or ‘kubectl port-forward’.
- Inspect service endpoints and cluster DNS configuration using ‘kubectl get endpoints’ and ‘kubectl get svc’.
- Review network policies, firewall rules, and ingress/egress configurations affecting pod-to-pod communication.
- Analyze network traffic and packet captures using tools like Wireshark or tcpdump to diagnose network-level issues.
Resolution:
- Correct misconfigured service definitions, endpoint subsets, or DNS settings to ensure proper service discovery and communication.
- Update network policies or firewall rules to allow necessary traffic flows between application components.
- Implement service mesh solutions (e.g., Istio, Linkerd) to enhance network observability, security, and reliability.