What are the most common issues when debugging a Kubernetes deployment?

1 Misconfigured resources

One of the most common issues when debugging a Kubernetes deployment is misconfigured resources. Resources are the objects that define the desired state and configuration of your cluster, such as pods, services, deployments, and config maps. If you have errors or typos in your resource definitions, or if you use incompatible or outdated versions of the Kubernetes API, you may encounter unexpected behavior or failures in your cluster. To avoid this issue, you should always validate your resource definitions before applying them, using tools such as kubectl, kubeadm, or helm. You should also review the Kubernetes documentation and best practices for each resource type, and use labels and annotations to provide additional metadata and context.

2 Networking issues

When debugging a Kubernetes deployment, networking issues are often encountered. These can affect communication and connectivity between pods, services, nodes, and external sources. Causes of these issues can include incorrect or missing network policies, misconfigured or incompatible network plugins, firewall rules or security groups blocking traffic, DNS resolution errors, or service discovery failures. To troubleshoot networking issues, tools such as ping, curl, traceroute, nslookup, and iptables should be used to test the connectivity and routing. Additionally, the logs and events of network components like kube-proxy and kube-dns should be checked. Lastly, the configuration of network policies, plugins, firewall rules, and security groups should be verified to ensure consistency across the cluster.

3 Pod failures

Debugging a Kubernetes deployment can be complicated due to pod failures, which may be caused by insufficient resources, application errors, liveness or readiness probe failures, image pull errors, or security issues. To troubleshoot pod failures, kubectl describe, kubectl logs, kubectl exec, and kubectl get are useful tools for inspecting the status, logs, events, and metrics of your pods. Additionally, kubectl top, kubectl describe quota, and kubectl describe limitrange can help monitor resource usage and limits. It is also important to check the application code, configuration, dependencies, environment variables, image registry, image tag, image pull policy and image pull secrets of your pods to ensure they are consistent and compatible with your cluster. Lastly, verify that the security policies, roles and permissions of your pods are adequate and secure.

4 Cluster issues

A fourth common issue when debugging a Kubernetes deployment is cluster issues, which can affect the availability, performance, and stability of the entire cluster. Possible causes of cluster issues include node failures, scaling errors, upgrade errors, configuration errors, and security issues. To troubleshoot cluster issues, you should use tools such as kubectl get nodes, kubectl get events, kubectl get componentstatuses, and kubectl cluster-info to check the status of your cluster components. You should also use tools such as kubectl drain, kubectl cordon, kubectl uncordon, and kubectl taint to manage the state and scheduling of your nodes. Additionally, you should use tools such as kubeadm, kops, or eksctl to manage the scaling, upgrading, and configuration of your cluster. Furthermore, you should use tools such as kubectl get secrets, kubectl get serviceaccounts, and kubectl auth can-i to manage the security and access of your cluster.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?