The answer is to increase the CPU request for the backend pods to 2 CPUs. This directly resolves the GKE backend latency spikes because the observed CPU throttling indicates that the current 1 CPU request is insufficient for the CPU-bound workload, especially when node utilization hits 70% and the Kubernetes CPU manager enforces limits by throttling the container. On the Google Professional Cloud Architect exam, this scenario tests your understanding of resource requests versus limits, and the common trap is to blame the network or scale replicas—but since the database is not the bottleneck and network bytes are low, the root cause is CPU contention. Remember that increasing the CPU request guarantees a larger CPU share, reducing throttling without over-provisioning the cluster. Memory tip: "Throttle means you need more throttle" — when you see latency correlated with CPU throttling, increase the CPU request, not the replica count.
Google PCA Practice Question: Analyze and optimize technical and business processes
This PCA practice question tests your understanding of analyze and optimize technical and business processes. 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 company runs a multi-tier web application on Google Kubernetes Engine (GKE). The application consists of a frontend service, a backend API service, and a PostgreSQL database deployed using a StatefulSet with persistent volumes. The backend service exposes a gRPC endpoint. Recently, the team noticed that the backend service experiences intermittent high latency and occasional timeouts. The frontend service is stateless and scales well. The backend service is CPU-bound. The database is not the bottleneck. The cluster has three nodes of type n1-standard-4. The backend service is deployed with 10 replicas, each requesting 1 CPU and 2 Gi memory. Node utilization is around 70% CPU. The team suspects the network is the issue. However, after reviewing the GKE monitoring dashboard, they see that the network bytes sent/received per second for the backend pods is well below the node's network bandwidth limit. The latency spikes seem correlated with periods of high CPU throttling on the backend pods. The backend service's gRPC requests are small (under 1 KB), and the responses are also small. The team has already optimized the application code. What should the team do to reduce latency?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the CPU request for the backend pods to 2 CPUs.
The correct answer is C because the latency spikes correlate with CPU throttling, and increasing the CPU request to 2 CPUs ensures that each backend pod receives a guaranteed CPU share, reducing throttling under load. Since the backend is CPU-bound and node utilization is 70%, the current 1 CPU request may be insufficient, causing the Kubernetes CPU manager to throttle the pods when the node's CPU is contended. This directly addresses the root cause without adding unnecessary replicas or memory.
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.
✗
Increase the number of nodes in the cluster to reduce network contention.
Why it's wrong here
Network is not the bottleneck; CPU throttling is.
✗
Increase the number of backend replicas to 20.
Why it's wrong here
More replicas with same CPU request could worsen throttling on the same nodes.
✓
Increase the CPU request for the backend pods to 2 CPUs.
Why this is correct
More CPU will reduce throttling and latency.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the memory request for the backend pods to 4 Gi.
Why it's wrong here
Memory is not the issue.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may focus on network or scaling solutions (A or B) because the symptom is latency, but the monitoring data explicitly points to CPU throttling, not network saturation, making CPU request adjustment the precise fix.
Detailed technical explanation
How to think about this question
CPU throttling occurs when a container's CPU usage exceeds its CPU request, causing the Linux Completely Fair Scheduler (CFS) to limit its time slices via the cpu.cfs_period_us and cpu.cfs_quota_us cgroups. In GKE, the CPU request determines the guaranteed CPU share, and if the node is overcommitted, the kernel throttles pods that exceed their request. Increasing the CPU request to match actual usage (e.g., 2 CPUs) ensures the pod gets a higher CFS quota, reducing throttling and latency for gRPC, which is sensitive to CPU delays due to its small, frequent messages.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this PCA question in full detail.
Analyze and optimize technical and business processes — This question tests Analyze and optimize technical and business processes — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase the CPU request for the backend pods to 2 CPUs. — The correct answer is C because the latency spikes correlate with CPU throttling, and increasing the CPU request to 2 CPUs ensures that each backend pod receives a guaranteed CPU share, reducing throttling under load. Since the backend is CPU-bound and node utilization is 70%, the current 1 CPU request may be insufficient, causing the Kubernetes CPU manager to throttle the pods when the node's CPU is contended. This directly addresses the root cause without adding unnecessary replicas or memory.
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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