- A
Cloud Run
Why wrong: Cloud Run does not support GPUs.
- B
Cloud Functions with GPU
Why wrong: Cloud Functions does not support GPUs.
- C
GKE Standard cluster with GPU node pool and cluster autoscaler
GKE Standard can scale GPU node pools to zero when no pods request GPUs, minimizing cost.
- D
Compute Engine with GPUs in a managed instance group
Why wrong: Managed instance groups cannot scale to zero; they have a minimum size of 1.
- E
GKE Autopilot cluster
GKE Autopilot supports GPU workloads and automatically scales nodes, including scaling to zero when no pods need GPUs.
Question 861 of 1,000
Google ACE Planning and Configuring a Cloud Solution Practice Question
This ACE practice question tests your understanding of planning and configuring 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 development team wants to deploy a containerized microservice that requires GPU acceleration for inference. They want to minimize cost while maintaining the ability to scale to zero when not in use. Which two services meet these requirements? (Choose TWO.)
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
✓
GKE Standard cluster with GPU node pool and cluster autoscaler
Option C is correct because GKE Standard with a GPU node pool and cluster autoscaler allows the cluster to scale down to zero nodes when no pods require GPU resources, minimizing cost. The cluster autoscaler automatically removes idle nodes and adds GPU nodes only when GPU-accelerated pods are scheduled, meeting the requirement for scaling to zero.
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.
- ✗
Cloud Run
Why it's wrong here
Cloud Run does not support GPUs.
- ✗
Cloud Functions with GPU
Why it's wrong here
Cloud Functions does not support GPUs.
- ✓
GKE Standard cluster with GPU node pool and cluster autoscaler
Why this is correct
GKE Standard can scale GPU node pools to zero when no pods request GPUs, minimizing cost.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Compute Engine with GPUs in a managed instance group
Why it's wrong here
Managed instance groups cannot scale to zero; they have a minimum size of 1.
- ✓
GKE Autopilot cluster
Why this is correct
GKE Autopilot supports GPU workloads and automatically scales nodes, including scaling to zero when no pods need GPUs.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that serverless services like Cloud Run or Cloud Functions can support GPUs, but in reality, GPU acceleration is only available in container orchestration platforms like GKE or Compute Engine-based solutions.
Detailed technical explanation
How to think about this question
GKE Autopilot manages node lifecycle automatically, including GPU nodes, and can scale down to zero when no GPU workloads are running, making option E correct. The cluster autoscaler in GKE Standard works by monitoring pod resource requests and unschedulable pods, then adding or removing nodes from the node pool accordingly, including GPU nodes. In Autopilot, the control plane handles this scaling transparently, but both options support scaling to zero for GPU workloads when configured properly.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this ACE question test?
Planning and Configuring a Cloud Solution — This question tests Planning and Configuring a Cloud Solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: GKE Standard cluster with GPU node pool and cluster autoscaler — Option C is correct because GKE Standard with a GPU node pool and cluster autoscaler allows the cluster to scale down to zero nodes when no pods require GPU resources, minimizing cost. The cluster autoscaler automatically removes idle nodes and adds GPU nodes only when GPU-accelerated pods are scheduled, meeting the requirement for scaling to zero.
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.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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