Kubernetes Troubleshooting: Guide For Fixing Common Issues

Kubernetes Troubleshooting: Guide For Fixing Common Issues

Resolve Kubernetes performance issues effectively.

Troubleshoot containers, pods, crashes, and resource problems.

March 7, 2024

What Is Kubernetes Troubleshooting?

Kubernetes troubleshooting is the process of detecting and remediating any type of performance issue that arises within a Kubernetes environment. Common performance problems that you might encounter on Kubernetes include:

Three Pillars of Kubernetes Troubleshooting

Like observability, which is also said to have three "pillars" (metrics, logs, and traces), Kubernetes troubleshooting also depends on three key components: Understanding, Management, and Prevention.

Understanding

Understanding means determining the state of your workloads, identifying when you have an issue, and assessing what it will take to fix the problem.

Manage

Once you understand an issue, you can manage it. Management means taking steps to fix whatever caused the problem.

Prevention

The final key element in troubleshooting is prevention, which means taking steps to prevent the issue (or similar problems) from recurring.

Expert Tip: Crack Kubernetes Troubleshooting with the “Three R’s” Approach

Kubernetes Troubleshooting Challenges

Kubernetes troubleshooting would be easy if Kubernetes were a straightforward, uncomplicated system. Alas, it's not. Kubernetes is a very complex platform that includes a variety of distinct components – an API server, an etcd key-value store, control plane nodes, worker nodes, Pods, various network resources, and more.

Common Kubernetes Errors and Their Fixes

How to Identify Exit Codes and Errors

First, check for exit codes events using the kubectl describe command to request information about Pods.

Exit Code 1

Exit code 1 in Kubernetes means that a container terminated due to an application error.

How to Fix Exit Code 1

Try running the container directly from the command line to verify that it starts properly.

Exit Code 125

Exit code 125 means that a container failed to run because the command that Kubernetes tried to use to run it didn't execute successfully.

How to Fix Exit Code 125

Check the commands inside your container image for typos or undefined arguments or flags.

Exit Code 143

Exit code 143 happens when a container receives the SIGTERM signal, indicating a request to shut down.

Exit Code 137

Exit code 137 indicates that a Pod was terminated by the Linux SIGKILL signal (signal 9), usually due to exceeding memory limits.

CrashLoopBackOff

CrashLoopBackOff occurs if a container repeatedly fails to start. It can be resolved by checking for resource availability, deployment configurations, or application issues.

ImagePullBackOff

An ImagePullBackOff error means that Kubernetes couldn't pull the image for a container. Fix it by ensuring the container image path is correctly configured.

Node Not Ready

Node Not Ready appears when a node in your Kubernetes cluster fails to reach the ready state.

How to Fix Node Not Ready

Check kubelet logs of affected worker nodes for information about why the node is failing.

CreateContainerConfigError

CreateContainerConfigError means that a container in a pending state failed to transition to running state.

Kubernetes OOMKilled

A Kubernetes OOMKilled error indicates that a container was shut down because it was using more memory than allowed.

Getting to the Root Cause Isn’t Always Easy

Kubernetes is a very complex system, which often makes it difficult to get to the root cause of performance problems. However, Kubernetes error codes offer a good starting point for investigating many types of problems. You should also draw on logs, metrics, and any other observability data sources available to you to help pinpoint the main cause of an issue.