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CKA Practice Question: Cluster Architecture, Installation and Configuration

A pod in the 'production' namespace is in a CrashLoopBackOff state. The pod has been running successfully for several days. You run 'kubectl describe pod app-pod -n production' and see the message: 'OOMKilled'. What is the MOST appropriate action to resolve this issue?

⚠ Common exam trap

CNCF often tests the misconception that restarting or recreating the pod will resolve a CrashLoopBackOff caused by resource limits, but the trap here is that the OOMKilled error is a resource constraint issue, not a transient failure, so only adjusting the memory limit or removing the limit will stop the crash loop.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Increase the memory limit in the pod's container resource specification

The pod is in a CrashLoopBackOff state with an 'OOMKilled' message, which indicates that the container's memory usage exceeded its configured memory limit, causing the kernel's Out-Of-Memory (OOM) killer to terminate the process. Increasing the memory limit in the pod's container resource specification allows the container to use more memory without being killed, directly addressing the root cause of the crash loop.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increase the memory limit in the pod's container resource specification

    Why this is correct

    Increasing the memory limit in the pod's container resource specification directly addresses a CrashLoopBackOff state caused by OOMKilled (Out Of Memory Killed). When a container exceeds its allocated memory limit, the host kernel's OOM killer terminates the process, causing the container to crash. By providing more memory, the application has sufficient resources to operate without being prematurely terminated, allowing the pod to transition to a Running state.

  • Delete the namespace and redeploy all workloads

    Why it's wrong here

    Deleting an entire namespace and redeploying all workloads is an extremely destructive and disproportionate action for resolving a single pod's CrashLoopBackOff issue. This operation would indiscriminately remove all associated resources, including other healthy pods, services, deployments, and persistent data, leading to significant downtime and potential data loss for all applications within that namespace. It's akin to demolishing a building to fix a leaky faucet.

  • Delete and recreate the pod to clear the crash loop

    Why it's wrong here

    Simply deleting and recreating the pod without addressing the root cause of the crash will only provide a temporary respite, if any. Kubernetes controllers, such as Deployments, will immediately recreate the pod with the identical problematic configuration, leading it to crash again and re-enter the CrashLoopBackOff state. This action does not resolve underlying issues like insufficient memory limits, application bugs, or incorrect configurations, making it an ineffective troubleshooting step.

  • Increase the CPU request for the container

    Why it's wrong here

    Increasing the CPU request for the container is irrelevant to resolving a CrashLoopBackOff caused by memory exhaustion, such as an OOMKilled event. CPU requests and limits govern the processing power available to a container, whereas OOMKilled specifically indicates that the container attempted to consume more RAM than its defined memory limit. Adjusting CPU resources will not prevent the container from running out of memory and being terminated by the kernel.

Visual reference

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This CKA practice question is part of Courseiva's free CNCF certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the CKA exam.