20+ practice questions focused on Optimizing service performance — one of the most tested topics on the Google Professional Cloud DevOps Engineer exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Optimizing service performance PracticeYou are troubleshooting a performance issue with a Compute Engine instance that is part of a managed instance group serving a web application. Users report intermittent high latency. You run the command shown in the exhibit. Based on the output, what is the most likely cause of the performance issue?
Explanation: The output shows high CPU utilization (e.g., 95%+), which directly correlates with the reported intermittent high latency. In a managed instance group, if the instance is under-provisioned for CPU, it cannot handle the workload spikes, causing queuing and increased response times. This is the most common cause of performance degradation in Compute Engine instances serving web applications.
An e-commerce platform uses Cloud SQL for its database. The team notices that read queries are slow. They want to improve read performance without significant cost increase. Which action should they take?
Explanation: Adding a read replica is the most cost-effective way to improve read query performance in Cloud SQL. A read replica offloads SELECT queries from the primary instance, reducing contention and latency for read-heavy workloads, without requiring a more expensive primary instance. This approach scales read capacity horizontally while keeping the primary instance's compute and storage unchanged.
A financial services company uses Spanner for their core database. They notice that some transactions are taking longer than expected, especially during cross-region writes. They have set up Spanner with regional configuration. What is the most likely cause?
Explanation: A is correct because cross-region writes in a regional Spanner configuration can lead to increased latency due to hot spotting. A hot spot occurs when many writes are concentrated on a single split (e.g., a monotonically increasing key), causing contention and serialization delays. This is especially pronounced in cross-region scenarios because Spanner's TrueTime and Paxos-based replication require consensus across zones, amplifying the impact of contention.
A team is optimizing a Cloud Run service. Which two actions can reduce request latency? (Select TWO.)
Explanation: Reducing the container image size decreases the time required to pull the image from the registry to the compute instance, which directly reduces cold-start latency. Enabling min-instances keeps a specified number of instances always warm, eliminating cold-start delays for baseline traffic. Both actions address the most common sources of latency in serverless Cloud Run deployments.
Your team has deployed a microservices application on Google Kubernetes Engine (GKE). You notice that one service has high latency during peak hours. The service is CPU-bound and uses a HorizontalPodAutoscaler (HPA) based on CPU utilization. What is the most likely cause of the latency?
Explanation: When the HPA's target CPU utilization is set too high, the autoscaler waits until the average CPU utilization exceeds that threshold before scaling up. During peak hours, the service becomes CPU-bound and latency increases as pods are overwhelmed, but the HPA reacts slowly because it only triggers when the high threshold is breached, causing a delay in adding new pods to handle the load.
+15 more Optimizing service performance questions available
Practice all Optimizing service performance questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Optimizing service performance. This tells you whether you need a concept refresher or just practice.
2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
Optimizing service performance questions on the PCDOE frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.
4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Optimizing service performance is tested as part of the Google Professional Cloud DevOps Engineer blueprint. Practicing with targeted Optimizing service performance questions ensures you can handle any format or difficulty that appears.
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Difficulty is subjective, but Optimizing service performance is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.
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