- A
The nodes are under-provisioned; add more nodes to the cluster.
Why wrong: Adding nodes would distribute pods, but memory is the bottleneck, not node count. The existing nodes have memory near 100%, indicating the pod needs more memory or the application has a memory leak.
- B
The application is memory-constrained; increase memory resource limits for the pod.
Memory is near 100% on nodes, causing requests to queue and time out. Increasing memory limits allows more concurrent requests.
- C
The application is CPU-bound; increase CPU resource limits for the pod.
Why wrong: CPU utilization is below 50%, so CPU is not the bottleneck.
- D
The network bandwidth is insufficient; increase the machine type for nodes.
Why wrong: There is no indication of network issues; the symptom is memory pressure.
Quick Answer
The correct answer is to increase memory resource limits for the pod because the symptoms—low CPU utilization but near 100% memory usage on nodes, with API timeouts during peak hours—point directly to a GKE pod OOM kill caused by hitting memory limits. When a pod exceeds its configured memory request, the Linux kernel’s Out-Of-Memory (OOM) killer terminates the process to free resources, which drops in-flight requests and causes latency spikes. On the Google Professional Cloud DevOps Engineer exam, this scenario tests your ability to distinguish memory pressure from CPU bottlenecks; a common trap is assuming you need to scale nodes or adjust CPU limits when the real fix is tuning pod resource requests and limits. Remember the memory tip: “Low CPU, high mem? OOM is the problem—raise the limit, not the node.”
PCDOE Optimizing service performance Practice Question
This PCDOE practice question tests your understanding of optimizing service performance. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
Your team deploys a microservice on Google Kubernetes Engine (GKE) that serves an API with low latency requirements. Users report that the API occasionally times out during peak hours. You check the GKE metrics and see that CPU utilization is below 50% but memory is near 100% on the nodes. What is the most likely cause and what should you do?
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.
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
The application is memory-constrained; increase memory resource limits for the pod.
Option B is correct because the symptoms—low CPU utilization but near 100% memory usage on nodes, with API timeouts during peak hours—indicate that the application is hitting memory limits. When a pod exceeds its memory request, the kernel can OOM-kill it, causing request failures and timeouts. Increasing the memory resource limits for the pod allows it to allocate more heap or cache, preventing OOM kills and stabilizing latency.
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.
- ✗
The nodes are under-provisioned; add more nodes to the cluster.
Why it's wrong here
Adding nodes would distribute pods, but memory is the bottleneck, not node count. The existing nodes have memory near 100%, indicating the pod needs more memory or the application has a memory leak.
- ✓
The application is memory-constrained; increase memory resource limits for the pod.
Why this is correct
Memory is near 100% on nodes, causing requests to queue and time out. Increasing memory limits allows more concurrent requests.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
The application is CPU-bound; increase CPU resource limits for the pod.
Why it's wrong here
CPU utilization is below 50%, so CPU is not the bottleneck.
- ✗
The network bandwidth is insufficient; increase the machine type for nodes.
Why it's wrong here
There is no indication of network issues; the symptom is memory pressure.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that high memory usage on nodes always means you need more nodes, but the correct action is to first check pod-level resource limits and adjust them, as adding nodes only masks the real issue of memory-constrained pods.
Detailed technical explanation
How to think about this question
In GKE, the kubelet uses cgroups to enforce memory limits; when a pod exceeds its memory limit, the kernel’s OOM killer terminates the pod’s processes, leading to HTTP 503 or timeout errors. The `requests` field guarantees memory for scheduling, while `limits` cap usage; setting limits too low causes OOM kills even if the node has free memory. A real-world scenario is a Java application with a large heap that grows during peak traffic—without proper `-Xmx` and pod memory limit alignment, the JVM is killed despite low CPU.
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 healthcare organisation deploys an application with a public-facing web tier and a private database tier. The database subnet has no public IP and only accepts connections from the web tier's security group. Questions like this test whether you can design cloud network isolation using VNets/VPCs, subnets, and security group rules.
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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Optimizing service performance — study guide chapter
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FAQ
Questions learners often ask
What does this PCDOE question test?
Optimizing service performance — This question tests Optimizing service performance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The application is memory-constrained; increase memory resource limits for the pod. — Option B is correct because the symptoms—low CPU utilization but near 100% memory usage on nodes, with API timeouts during peak hours—indicate that the application is hitting memory limits. When a pod exceeds its memory request, the kernel can OOM-kill it, causing request failures and timeouts. Increasing the memory resource limits for the pod allows it to allocate more heap or cache, preventing OOM kills and stabilizing latency.
What should I do if I get this PCDOE 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". 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.
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Last reviewed: Jun 30, 2026
This PCDOE 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 PCDOE exam.
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