20+ practice questions focused on Applying site reliability engineering practices — 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 Applying site reliability engineering practices PracticeRefer to the exhibit. If the error rate spikes to 2% for only 2 minutes, why does the alert not fire?
Explanation: The alert condition requires the error rate to exceed 1% for a duration of 300 seconds (5 minutes). A spike lasting only 2 minutes does not meet the minimum duration requirement, so the alert remains in a 'pending' state and never fires. In Google Cloud Monitoring, the duration parameter defines how long the condition must be continuously true before the alert transitions from pending to firing.
A team uses Google Kubernetes Engine (GKE) with cluster telemetry enabled. During an incident, they notice that a deployment's pods are repeatedly crashing with Exit Code 137. The team wants to investigate the root cause. Which two Google Cloud services should they use together to correlate resource usage and logs?
Explanation: Exit Code 137 indicates a container was killed by SIGKILL, typically due to an out-of-memory (OOM) condition. To correlate resource usage and logs, Cloud Monitoring provides resource usage metrics (e.g., memory, CPU), while Cloud Logging captures container termination logs and system events. Together, they allow correlation of spikes in resource usage with log entries to identify OOM kills. Cloud Trace is not primarily a logging service; it provides distributed tracing for latency analysis, but does not directly correlate logs with resource usage. Therefore, only Cloud Monitoring and Cloud Logging together (option A) satisfy the requirement.
A DevOps engineer receives an alert that the error budget for a critical service has been exhausted. The service runs on Compute Engine behind an HTTP(S) load balancer. The team wants to reduce the impact on users while investigating. What should the engineer do first?
Explanation: Rolling back the most recent deployment is the correct first action because it immediately restores the service to a known stable state, stopping further consumption of the error budget. This aligns with the incident management principle of 'mitigate first, investigate later' — reducing user impact takes priority over root cause analysis. The HTTP(S) load balancer will automatically route traffic to the previous healthy version once the rollback is complete.
A company uses Cloud Run for a stateless API service with concurrency set to 80. During a traffic spike, some requests return HTTP 500 errors and latency spikes. Cloud Monitoring shows container CPU utilization at 100% and memory usage at 70%. What is the most likely cause and the best first step?
Explanation: With CPU at 100% and memory at only 70%, the bottleneck is CPU, not memory. Cloud Run containers handle requests concurrently; setting concurrency to 80 means each container processes up to 80 requests simultaneously. When CPU is saturated, requests queue up, causing latency spikes and eventual HTTP 500 errors as the container becomes unresponsive. Reducing concurrency to 10 lowers the per-container request load, allowing each request to complete before CPU saturation occurs.
A team uses Cloud SQL for PostgreSQL. They receive an alert that the database's CPU utilization is above 95% for the past 30 minutes. Queries are taking longer than usual. They want to investigate without causing further impact. What should they do first?
Explanation: Cloud SQL Query Insights is a managed monitoring tool that automatically captures and analyzes query performance metrics, including CPU consumption, latency, and execution plans. In this scenario, it allows the team to identify the specific queries causing high CPU utilization without making any changes to the instance, thus avoiding further impact. This is the first and safest diagnostic step before any remediation.
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Practice all Applying site reliability engineering practices questions1. Baseline your knowledge
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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
Applying site reliability engineering practices 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. Applying site reliability engineering practices is tested as part of the Google Professional Cloud DevOps Engineer blueprint. Practicing with targeted Applying site reliability engineering practices questions ensures you can handle any format or difficulty that appears.
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