Kubernetes Error Code 137 can be resolved with a little help from our in-house experts. Read on to learn more. 

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Let’s take a look at how our Support Team is ready to help customers resolve Kubernetes Error Code 137.

How to resolve Kubernetes Error Code 137

Kubernetes error code 137 is also known as the OOMKilled error. This error indicates that a pod or container using more than the allotted memory has been terminated.

Kubernetes pods have the ability to specify the memory limit as well as a memory request. In case the memory usage on the pods or containers exceeds these limits, pod termination occurs.

In this scenario, we can find the error by running the following command:

 kubectl get pods

The result will return the pod status as Terminating.

More about OOM Killer: Kubernetes Error Code 137

The OOMKilled feature, also known as OOM Killer is a feature if Linux Kernel. It helps Kubernetes manage container life cycles. Furthermore, it monitors node memory as well as processes that tend to take up additional memory. According to our Support Engineers, Oom Killer will terminate the process even if free memory is available on the node.

The Linux kernel relies on the oom_score to determine which process to kill. Moreover, oom_score_adj enables us to customize the OOM process, thereby allowing us to decide when to terminate processes.

Fortunately, we can resolve this error with the following troubleshooting tips courtesy of our skilled engineers:

• Check if the application requires additional memory. In this scenario, increasing the memory limit will help resolve the problem.
• Another reason behind the Kubernetes Error 137 is a memory leak. If you notice the memory usage increasing not corresponding with the application loads, it may be a memory leak. At this point, we have to debug the application and resolve the memory leak problem rather than increasing the memory limit.

In some cases, the pod terminates due to overcommit on the node. The overcommit occurs due to pods not being able to schedule on a node in case the memory requests value is lower than the memory available on the node. At this point, we have to adjust the memory requests and limit values to prevent the node from overcommitting.

Let us know which one of these tips helped you resolve the Kubernetes Error Code 137 at your end.

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Conclusion

In a nutshell, our skilled Support Engineers at Bobcares demonstrated how to resolve Kubernetes Error Code 137.