- A
Scale up the Cloud Spanner instance to handle higher peak CPU, as the 80% spikes indicate insufficient capacity.
Why wrong: Spanner CPU at 65% average with spikes to 80% is still within acceptable range; the errors correlate with node CPU, not Spanner.
- B
Change the backend service to use a multi-zone NEG that includes endpoints from all three zones, and ensure the load balancer is configured for cross-zone load balancing.
This ensures traffic is distributed evenly across zones, reducing cross-zone latency and preventing a single zone from being overloaded.
- C
Increase the CPU request for the frontend pods and set a higher target CPU utilization for the Horizontal Pod Autoscaler.
Why wrong: This might reduce node CPU but would not fix cross-zone routing issues that cause latency and health check failures.
- D
Increase the health check interval and timeout settings to give pods more time to respond before being marked unhealthy.
Why wrong: This would mask the problem but not address the root cause of cross-zone traffic and latency.
Quick Answer
The answer is to change the backend service to use a multi-zone NEG with cross-zone load balancing. This resolves the high latency and 502 errors during a flash sale because a regional GKE cluster’s default load balancer can send traffic unevenly across zones, overloading pods in one zone while others remain underutilized, causing node CPU spikes and unhealthy endpoints. On the Google Professional Cloud Architect exam, this scenario tests your understanding of how HTTP load balancers interact with GKE regional clusters and the critical role of multi-zone NEGs in distributing traffic evenly across all three zones. A common trap is assuming Spanner CPU is the bottleneck—at 65-80% utilization it’s not the culprit—or that simply scaling nodes fixes the imbalance. Remember the memory tip: “Multi-zone NEG, cross-zone spread; if your pods are imbalanced, your users are dead.”
Google PCA Manage and provision cloud infrastructure Practice Question
This PCA practice question tests your understanding of manage and provision cloud infrastructure. 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 company runs an e-commerce platform on Google Cloud. The application is deployed on Google Kubernetes Engine (GKE) with a regional cluster (us-central1, three zones). The frontend service is exposed via an HTTP Load Balancer with Cloud CDN. Recently, during a flash sale, users experienced high latency and occasional 502 errors. The backend service is a Java application that reads from Cloud Spanner. The team has observed that Spanner CPU utilization averaged 65% during the sale, with a few spikes to 80%. The number of frontend pods was auto-scaled to 50, each running on n1-standard-2 nodes. The node pool is set to autoscale up to 100 nodes. The errors appear to correlate with periods of high CPU on the nodes, but not always. What is the most likely cause and recommended action?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Clue:
"always"Why it matters: Absolute qualifier. An answer using 'always' is only correct if there are genuinely no exceptions — absolute statements are often wrong in networking.
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
Change the backend service to use a multi-zone NEG that includes endpoints from all three zones, and ensure the load balancer is configured for cross-zone load balancing.
The high latency and 502 errors are likely caused by the HTTP Load Balancer sending requests to unhealthy backend pods due to zone-imbalanced traffic. A regional GKE cluster with a multi-zone NEG and cross-zone load balancing ensures that the load balancer distributes requests evenly across all pods in all three zones, preventing node CPU spikes in a single zone from causing errors. Option B directly addresses this by enabling proper traffic distribution, which is the most probable root cause given that node CPU spikes correlate with errors but not always.
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.
- ✗
Scale up the Cloud Spanner instance to handle higher peak CPU, as the 80% spikes indicate insufficient capacity.
Why it's wrong here
Spanner CPU at 65% average with spikes to 80% is still within acceptable range; the errors correlate with node CPU, not Spanner.
- ✓
Change the backend service to use a multi-zone NEG that includes endpoints from all three zones, and ensure the load balancer is configured for cross-zone load balancing.
Why this is correct
This ensures traffic is distributed evenly across zones, reducing cross-zone latency and preventing a single zone from being overloaded.
Clue confirmation
The clue words "most likely", "always" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the CPU request for the frontend pods and set a higher target CPU utilization for the Horizontal Pod Autoscaler.
Why it's wrong here
This might reduce node CPU but would not fix cross-zone routing issues that cause latency and health check failures.
- ✗
Increase the health check interval and timeout settings to give pods more time to respond before being marked unhealthy.
Why it's wrong here
This would mask the problem but not address the root cause of cross-zone traffic and latency.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates focus on scaling the database (Spanner) or adjusting pod-level configurations, when the real issue is zone-imbalanced traffic distribution from the HTTP Load Balancer, a common misdiagnosis in multi-zone GKE setups.
Detailed technical explanation
How to think about this question
By default, a GKE regional cluster creates a single-zone NEG for each zone, and the HTTP Load Balancer may not distribute traffic evenly across zones unless cross-zone load balancing is enabled. When traffic spikes, pods in one zone may become overloaded while others are underutilized, causing node CPU spikes and 502 errors as the load balancer retries failed requests. Enabling cross-zone load balancing on the backend service (via the `loadBalancingScheme` and `balancingMode` settings) ensures that the load balancer uses a multi-zone NEG and distributes requests proportionally across all healthy pods, regardless of zone.
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
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
Questions learners often ask
What does this PCA question test?
Manage and provision cloud infrastructure — This question tests Manage and provision cloud infrastructure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Change the backend service to use a multi-zone NEG that includes endpoints from all three zones, and ensure the load balancer is configured for cross-zone load balancing. — The high latency and 502 errors are likely caused by the HTTP Load Balancer sending requests to unhealthy backend pods due to zone-imbalanced traffic. A regional GKE cluster with a multi-zone NEG and cross-zone load balancing ensures that the load balancer distributes requests evenly across all pods in all three zones, preventing node CPU spikes in a single zone from causing errors. Option B directly addresses this by enabling proper traffic distribution, which is the most probable root cause given that node CPU spikes correlate with errors but not always.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely", "always". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 11, 2026
This PCA 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 PCA exam.
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