Question 210 of 499
DeploymenthardMultiple ChoiceObjective-mapped

CV0-004 Deployment Practice Question

This CV0-004 practice question tests your understanding of deployment. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

Exhibit

Refer to the exhibit.

```
$ kubectl get pods -n production
NAME                      READY   STATUS    RESTARTS   AGE
frontend-5d8f4d9c7-cm2xr   0/1     Pending   0          10m
backend-6b9f7d5e4-lp9qz    1/1     Running   0          15m
$ kubectl describe pod frontend-5d8f4d9c7-cm2xr -n production
...
Events:
  Type     Reason            Age   From               Message
  ----     ------            ----  ----               -------
  Warning  FailedScheduling  10m   default-scheduler  0/3 nodes are available: 1 Insufficient cpu, 2 Insufficient memory.
```

A DevOps engineer is deploying an application on Kubernetes. The exhibit shows the status of pods and a describe output. The frontend pod is stuck in Pending state. Which action should the engineer take to resolve the issue?

Question 1hardmultiple choice
Full question →

Exhibit

Refer to the exhibit.

```
$ kubectl get pods -n production
NAME                      READY   STATUS    RESTARTS   AGE
frontend-5d8f4d9c7-cm2xr   0/1     Pending   0          10m
backend-6b9f7d5e4-lp9qz    1/1     Running   0          15m
$ kubectl describe pod frontend-5d8f4d9c7-cm2xr -n production
...
Events:
  Type     Reason            Age   From               Message
  ----     ------            ----  ----               -------
  Warning  FailedScheduling  10m   default-scheduler  0/3 nodes are available: 1 Insufficient cpu, 2 Insufficient memory.
```

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

Reduce the resource requests in the frontend deployment manifest.

The frontend pod is stuck in Pending state because the cluster nodes lack sufficient resources (CPU or memory) to satisfy the pod's resource requests. Reducing the resource requests in the deployment manifest lowers the scheduling threshold, allowing the pod to fit on an available node. This directly addresses the most common cause of Pending pods: insufficient allocatable resources on any node.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

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

  • Reduce the resource requests in the frontend deployment manifest.

    Why this is correct

    Decreasing requests may allow the pod to fit on a node.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Add a node affinity rule to schedule on nodes with more memory.

    Why it's wrong here

    No node has enough memory; affinity won't create resources.

  • Change the service type from ClusterIP to NodePort.

    Why it's wrong here

    Service type does not affect pod scheduling.

  • Modify the image pull policy to Always.

    Why it's wrong here

    The issue is resource availability, not image pulling.

Common exam traps

Common exam trap: answer the scenario, not the keyword

CompTIA often tests the misconception that changing service types or image pull policies can resolve scheduling failures, when the root cause is almost always resource insufficiency or taints/tolerations.

Detailed technical explanation

How to think about this question

When a pod is Pending, `kubectl describe pod` often shows events like '0/1 nodes are available: 1 Insufficient memory' or '1 Insufficient cpu'. The Kubernetes scheduler uses resource requests (not limits) to determine node fit; reducing requests allows the scheduler to place the pod on a node with fewer available resources. In production, overcommitting resources via requests can lead to CPU throttling or OOM kills, so adjustments should be balanced with actual application needs.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A practitioner preparing for the CV0-004 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Related practice questions

Related CV0-004 practice-question pages

Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

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FAQ

Questions learners often ask

What does this CV0-004 question test?

Deployment — This question tests Deployment — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Reduce the resource requests in the frontend deployment manifest. — The frontend pod is stuck in Pending state because the cluster nodes lack sufficient resources (CPU or memory) to satisfy the pod's resource requests. Reducing the resource requests in the deployment manifest lowers the scheduling threshold, allowing the pod to fit on an available node. This directly addresses the most common cause of Pending pods: insufficient allocatable resources on any node.

What should I do if I get this CV0-004 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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This CV0-004 practice question is part of Courseiva's free CompTIA 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 CV0-004 exam.