20+ practice questions focused on Optimising Service Performance — one of the most tested topics on the Google Professional Cloud Database Engineer exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Optimising Service Performance PracticeYour GKE cluster is running a critical web application that experiences predictable traffic spikes during business hours. You want to minimize latency and avoid pod startup delays during scaling. The application uses CPU-intensive image processing. Which scaling strategy should you use?
Explanation: To avoid cold starts while ensuring pods can handle CPU spikes, you need a baseline of pods and dynamic scaling responsive to CPU. HPA with a minimum replicas of 2 ensures baseline capacity; HPA scales on CPU. Cluster autoscaler adds nodes if needed, but does not directly address pod startup delay. VPA adjusts resource requests, which can help but does not prevent cold starts. Using HPA alone with min replicas avoids pod creation latency.
You are running a Cloud Run service that performs background image processing tasks after responding to HTTP requests. Users report that tasks are sometimes not completed. You have set CPU to always-on, but you notice the service's concurrency is set to the default of 80. What is the most likely cause of incomplete tasks?
Explanation: Cloud Run allows up to 80 concurrent requests per instance by default. If the concurrency is too high, the instance's CPU may be overwhelmed, causing background tasks to be preempted or not completed. Setting CPU to always-on ensures CPU is available but does not limit concurrency. Reducing concurrency to a lower value (e.g., 1) ensures each request gets dedicated CPU for background work.
Your Cloud Spanner instance is experiencing high write latency and hot spots on a table that uses an auto-incrementing integer as the primary key. Which change would best mitigate the hot spots?
Explanation: Monotonically increasing keys (like auto-incrementing integers) cause all writes to go to the same tablet (hot spot) in Cloud Spanner. Using a key with uniform distribution, such as a random UUID or a hash prefix, spreads writes across splits. Bit-reverse index is an alternative for sequential keys, but a random key is simpler. Interleaved tables and secondary indexes do not address the root cause.
Your organization uses Cloud SQL for PostgreSQL for a reporting application with read-heavy workloads. Queries are slow and you need to reduce load on the primary instance. You also need to ensure that all read queries from the reporting tool are isolated from the primary. What should you do?
Explanation: Cloud SQL read replicas serve read traffic and offload the primary. For isolation, the reporting tool must connect to the replica's IP. Cloud SQL Auth Proxy is a secure tunnel, but does not provide connection pooling. PgBouncer can be used with proxies for connection pooling, but the question asks for isolation, which is achieved by pointing the reporting tool to the replica. The best answer is to create a read replica and configure the reporting tool to connect to it.
You are deploying a batch job on Compute Engine that processes large datasets and can tolerate interruptions. The job runs for about 6 hours every night. Which option would minimize cost while ensuring the job completes within the 6-hour window?
Explanation: Preemptible VMs are significantly cheaper (up to 80% discount) but can be terminated at any time. For fault-tolerant batch jobs, preemptible VMs are ideal; if preempted, the job can resume on another preemptible VM. Committed use discounts provide cost savings for steady-state usage (1- or 3-year commitment), but are not suitable for a nightly 6-hour job. Custom machine types or standard VMs would be more expensive.
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Practice all Optimising Service Performance questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Optimising 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
Optimising Service Performance questions on the PCDE 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. Optimising Service Performance is tested as part of the Google Professional Cloud Database Engineer blueprint. Practicing with targeted Optimising Service Performance questions ensures you can handle any format or difficulty that appears.
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Difficulty is subjective, but Optimising 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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