Google PCA Design and plan a cloud solution architecture Practice Question
This PCA practice question tests your understanding of design and plan a cloud solution architecture. 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 startup is building a web application that experiences unpredictable traffic spikes. They want a scalable solution that minimizes costs. Which Google Cloud service should they use to run their containerized application?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Google Kubernetes Engine (GKE) with autoscaling
Google Kubernetes Engine (GKE) with autoscaling is the correct choice because it combines cluster autoscaling (which adjusts the number of nodes based on pod resource requests) with Horizontal Pod Autoscaling (which scales the number of pod replicas based on CPU/memory utilization or custom metrics). This dual-layer scaling handles unpredictable traffic spikes efficiently while minimizing costs by only provisioning resources when needed, and it is purpose-built for containerized applications.
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.
✗
App Engine Standard Environment
Why it's wrong here
App Engine Standard does not allow custom containers.
✗
Cloud Run for Anthos
Why it's wrong here
Cloud Run is serverless but may have trade-offs in flexibility.
✗
Compute Engine with managed instance groups
Why it's wrong here
Compute Engine scales by adding/removing instances, but it is less efficient for containerized apps.
✓
Google Kubernetes Engine (GKE) with autoscaling
Why this is correct
GKE provides automatic scaling of nodes and pods, ideal for containerized apps with spikes.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose Compute Engine with managed instance groups (Option C) because they think it is the most cost-effective, but they overlook that GKE's autoscaling is more granular (pod-level vs. VM-level) and reduces operational overhead for containerized workloads, making it the better choice for minimizing costs and handling unpredictable spikes.
Detailed technical explanation
How to think about this question
GKE's cluster autoscaler uses the Kubernetes scheduler's pod resource requests to determine when to add or remove nodes, scaling up when pending pods cannot be scheduled due to insufficient capacity and scaling down when nodes are underutilized for a configurable period (default 10 minutes). Horizontal Pod Autoscaling (HPA) uses the metrics-server to collect CPU/memory utilization every 15 seconds and adjusts replica counts based on a target utilization (e.g., 70% CPU), with a cooldown period of 3 minutes to avoid thrashing. In a real-world scenario, a flash sale might trigger HPA to scale pods from 5 to 50 within minutes, while cluster autoscaler adds nodes to accommodate the new pods, then scales down after the spike, ensuring cost efficiency.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this PCA question in full detail.
Design and plan a cloud solution architecture — This question tests Design and plan a cloud solution architecture — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Google Kubernetes Engine (GKE) with autoscaling — Google Kubernetes Engine (GKE) with autoscaling is the correct choice because it combines cluster autoscaling (which adjusts the number of nodes based on pod resource requests) with Horizontal Pod Autoscaling (which scales the number of pod replicas based on CPU/memory utilization or custom metrics). This dual-layer scaling handles unpredictable traffic spikes efficiently while minimizing costs by only provisioning resources when needed, and it is purpose-built for containerized applications.
What should I do if I get this PCA 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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Question Discussion
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