This ACE practice question tests your understanding of deploying and implementing a cloud solution. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 company wants to deploy a containerized web application on Google Kubernetes Engine (GKE) with minimal operational overhead. They require automatic scaling based on CPU utilization. Which resource should they configure?
Cluster autoscaler
Why wrong: Resizes the cluster's node pool, not the number of pods.
VerticalPodAutoscaler
Why wrong: Adjusts CPU/memory limits but does not scale pod count.
HorizontalPodAutoscaler
Correctly scales pods based on CPU utilization.
Node auto-provisioning
Why wrong: Automatically creates node pools, does not scale pods.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
HorizontalPodAutoscaler
The HorizontalPodAutoscaler (HPA) is the correct resource because it automatically scales the number of pod replicas in a GKE deployment based on observed CPU utilization (or other custom metrics). This directly meets the requirement for automatic scaling with minimal operational overhead, as HPA is a native Kubernetes controller that adjusts replica counts without manual intervention.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Cluster autoscaler
Why it's wrong here
Resizes the cluster's node pool, not the number of pods.
VerticalPodAutoscaler
Why it's wrong here
Adjusts CPU/memory limits but does not scale pod count.
HorizontalPodAutoscaler
Why this is correct
Correctly scales pods based on CPU utilization.
Related concept
Read the scenario before looking for a memorised answer.
Node auto-provisioning
Why it's wrong here
Automatically creates node pools, does not scale pods.
Common exam traps
Google Cloud often tests the distinction between horizontal scaling (adding/removing pods) and vertical scaling (adjusting pod resources) or infrastructure scaling (adding/removing nodes), leading candidates to confuse the HorizontalPodAutoscaler with the Cluster autoscaler or VerticalPodAutoscaler.
Detailed technical explanation
The HorizontalPodAutoscaler works by querying the Kubernetes Metrics Server (or custom metrics API) at a default interval of 15 seconds, then calculating the desired replica count using the formula: desiredReplicas = ceil(currentReplicas * (currentMetricValue / targetMetricValue)). A subtle behavior is that HPA uses a stabilization window (default 5 minutes) to prevent thrashing, meaning it will not scale down immediately after a brief CPU spike. In real-world scenarios, combining HPA with cluster autoscaler is common to ensure both pod-level and node-level scaling work together seamlessly.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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FAQ
Deploying and implementing a cloud solution — This question tests Deploying and implementing a cloud solution — Read the scenario before looking for a memorised answer..
The correct answer is: HorizontalPodAutoscaler — The HorizontalPodAutoscaler (HPA) is the correct resource because it automatically scales the number of pod replicas in a GKE deployment based on observed CPU utilization (or other custom metrics). This directly meets the requirement for automatic scaling with minimal operational overhead, as HPA is a native Kubernetes controller that adjusts replica counts without manual intervention.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 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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