Question 316 of 500
Ensuring successful operation of a cloud solutionmediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is to switch the node pool to a memory-optimized machine type like the m2-ultramem series and ensure Pod memory requests are accurate. This is correct because your workload is memory-bound—high memory utilization with low CPU and OOMKilled pods indicates a mismatch in the machine’s memory-to-CPU ratio. Memory-optimized series provide a much higher proportion of memory per vCPU, directly relieving memory pressure and preventing out-of-memory kills, while accurate requests let the scheduler avoid overcommitment. On the Google Associate Cloud Engineer exam, this scenario tests your understanding of GKE resource management and machine family selection; a common trap is choosing a general-purpose or compute-optimized machine, which would waste cost on unused CPU. Remember the memory tip: “High mem, low CPU? Go m2 or m3.”

Google ACE Practice Question: Ensuring successful operation of a cloud solution

This ACE practice question tests your understanding of ensuring successful operation of a cloud solution. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.

A cost-conscious team notices their GKE cluster's node pools have consistently high memory utilization (>90%) while CPU remains at 30%. Pods are occasionally OOMKilled. What should they do to balance resource efficiency and stability?

Question 1mediummultiple choice
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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

Switch node pool machine type to a memory-optimized series (e.g., m2-ultramem) and ensure Pod memory requests are accurate

Option A is correct because the team has a memory-bound workload (high memory utilization, low CPU, OOMKills). Switching to a memory-optimized machine series (e.g., m2-ultramem) provides a higher memory-to-CPU ratio, directly addressing the memory pressure. Ensuring accurate Pod memory requests allows the scheduler to place Pods efficiently and prevents overcommitment, balancing resource efficiency with stability.

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.

  • Switch node pool machine type to a memory-optimized series (e.g., m2-ultramem) and ensure Pod memory requests are accurate

    Why this is correct

    Memory-optimized machine types provide more RAM per vCPU, directly addressing the memory bottleneck. Accurate Pod requests let the scheduler pack Pods efficiently and let the autoscaler add the right type of capacity.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Increase CPU limits for all Pods to use the available CPU capacity

    Why it's wrong here

    The bottleneck is memory, not CPU — increasing CPU limits doesn't help OOMKills caused by insufficient RAM.

  • Enable vertical pod autoscaling (VPA) set to Recreate mode as the only change

    Why it's wrong here

    VPA can adjust resource requests, but Recreate mode restarts Pods to apply changes — not ideal for production. VPA is complementary to, not a replacement for, right-sizing the node type.

  • Reduce the number of replica Pods to lower memory consumption

    Why it's wrong here

    Reducing replicas reduces availability — it's not the right solution for a sizing problem. The cluster needs more memory capacity, not fewer workloads.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google Cloud often tests the misconception that vertical scaling (VPA) alone can fix memory pressure without considering the node's physical resource ratio, leading candidates to pick Option C and overlook the need for a memory-optimized machine type.

Detailed technical explanation

How to think about this question

Memory-optimized machine families like m2-ultramem use up to 12 TB of memory with a high memory-to-vCPU ratio (e.g., 24 GB per vCPU), which is ideal for in-memory databases or large caches. GKE's node auto-provisioning and cluster autoscaler can automatically select these machine types if Pod resource requests are properly set, but manual node pool selection gives more control. Accurate memory requests are critical because the Kubernetes scheduler uses them to determine node fit; underestimating requests leads to overcommitment and OOMKills, while overestimating wastes resources.

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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.

What to study next

Got this wrong? Here's your next step.

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FAQ

Questions learners often ask

What does this ACE question test?

Ensuring successful operation of a cloud solution — This question tests Ensuring successful operation of a cloud solution — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Switch node pool machine type to a memory-optimized series (e.g., m2-ultramem) and ensure Pod memory requests are accurate — Option A is correct because the team has a memory-bound workload (high memory utilization, low CPU, OOMKills). Switching to a memory-optimized machine series (e.g., m2-ultramem) provides a higher memory-to-CPU ratio, directly addressing the memory pressure. Ensuring accurate Pod memory requests allows the scheduler to place Pods efficiently and prevents overcommitment, balancing resource efficiency with stability.

What should I do if I get this ACE 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 ACE practice question is part of Courseiva's free Google Cloud 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 ACE exam.