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How to Fix Exit Code 137 on Kubernetes?

How to Fix Exit Code 137 on Kubernetes

If you're working with Kubernetes, you may have encountered exit code 137 at some point. This error occurs when a container is killed by the Kubernetes node because it exceeded the memory limit that was set. In this article, we'll explore what exit code 137 means, why it happens, and how you can fix it.

What is Exit Code 137?

Exit code 137 is a signal that the container was killed due to it exceeding the memory limit that was set by Kubernetes. The number 137 is a combination of two signals, SIGKILL (9) and signal 137. This means that Kubernetes sent the SIGKILL signal to the container, which resulted in the exit code 137.

Why Does Exit Code 137 Happen?

Exit code 137 occurs when a container exceeds the memory limit that was set by Kubernetes. When a container uses too much memory, Kubernetes will kill the container to prevent it from using up too many resources on the node. This helps to ensure that other containers on the same node can continue to run smoothly.

How to Fix Exit Code 137?

There are several ways to fix exit code 137. Here are some steps you can take:

  1. Increase the Memory Limit

The first step to fixing exit code 137 is to increase the memory limit for the container. You can do this by updating the resource limits in your Kubernetes manifest file. Here's an example:

apiVersion: v1
kind: Pod
metadata:
name: mypod
spec:
containers:
- name: mycontainer
image: myimage
resources:
limits:
memory: "1Gi"

In the example above, we've set the memory limit for the container to 1 gigabyte. You can adjust this value based on the needs of your application.

  1. Use Resource Requests

In addition to setting resource limits, you can also use resource requests to ensure that your containers have enough resources to run. Resource requests specify the minimum amount of resources that a container requires to run. Here's an example:

apiVersion: v1
kind: Pod
metadata:
name: mypod
spec:
containers:
- name: mycontainer
image: myimage
resources:
requests:
memory: "500Mi"
limits:
memory: "1Gi"

In the example above, we've set a resource request of 500 megabytes and a memory limit of 1 gigabyte. This ensures that the container has enough resources to run, but also prevents it from using too much memory.

  1. Optimize Your Application

If increasing the memory limit and using resource requests doesn't solve the problem, you may need to optimize your application. This could involve reducing the amount of memory that your application uses, or finding ways to improve the efficiency of your code.

  1. Monitor Your Containers

Finally, it's important to monitor your containers to ensure that they're not using too much memory. You can use Kubernetes tools like Prometheus or Grafana to monitor your containers and alert you if they exceed their memory limits.

Exit code 137 can be a frustrating error to encounter in Kubernetes, but it's important to understand why it happens and how to fix it. By increasing memory limits, using resource requests, optimizing your application, and monitoring your containers, you can prevent this error from occurring and ensure that your containers run smoothly.

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  • That's it for this post. Keep practicing and have fun. Leave your comments if any.

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