Your team operates a production web service on Compute Engine. You need to alert the on-call engineer when the 99th percentile latency exceeds 2 seconds for 5 minutes. You also want to avoid waking the engineer for brief spikes. Which alerting approach should you use?

Configure a Cloud Logging sink to export logs to BigQuery and manually query for latency spikes.

Set up a Cloud Monitoring alert on the 'Latency' metric with a threshold of 2s, but without a duration condition.

Create an alert on the VM's CPU utilization with a threshold of 80% for 5 minutes.

Create a log-based metric for latency from application logs, then set an alert on that metric with a threshold of 2s and a duration of 5 minutes.

Your organization runs a microservices application on Google Kubernetes Engine (GKE). You need a single dashboard that shows CPU utilization, memory usage, and request latency for all services, and you want to be able to drill down into individual pods. What should you do?

Create a custom dashboard in Cloud Monitoring and add charts for CPU, memory, and latency metrics, grouped by service and pod.

Export metrics to BigQuery and use Data Studio to create a dashboard.

Enable Google Cloud's operations suite and rely on the default GKE dashboard, which already shows all required metrics.

Use Cloud Logging to view logs from all pods and manually correlate them with performance issues.

What is a common strategy to reduce alert noise in Cloud Monitoring?

Using more notification channels

Your production application is experiencing intermittent slowdowns. You suspect a specific function is consuming excessive CPU, but you are not sure which one. You need to identify the bottleneck without adding significant overhead to the application. What should you do?

Run a load test against the application and use Cloud Trace to analyze spans.

Use Cloud Monitoring to view CPU utilization of the VM and correlate with slowdowns.

Add custom logging statements around each function to measure execution time.

Enable Cloud Profiler on the application and analyze the CPU profile to identify the function with high CPU usage.

Google CloudProfessional Cloud Architect

Domain 6Objective 2

6.2 Familiarity with Google Cloud Observability Solutions PROFESSIONAL-CLOUD-ARCHITECT Practice Questions (Page 1)

Part of the Ensuring solution and operations excellence domain, which accounts for ~12.5% of the PROFESSIONAL-CLOUD-ARCHITECT exam. Google Cloud does not publish an official question count, but from its 120-minute exam (~50–80 total, ~6–6 in this domain), expect 1–1 from this objective — we provide 25 practice questions to prepare you well beyond it. (estimate)

25questions here

5free pages

7concepts

~12.5%of the exam

Questions 1–5

1application · medium
Your team operates a production web service on Compute Engine. You need to alert the on-call engineer when the 99th percentile latency exceeds 2 seconds for 5 minutes. You also want to avoid waking the engineer for brief spikes. Which alerting approach should you use?
Select an answer first
2foundation · easy
Which of the following is a valid notification channel type in Cloud Monitoring?
Select an answer first
3application · medium
Your organization runs a microservices application on Google Kubernetes Engine (GKE). You need a single dashboard that shows CPU utilization, memory usage, and request latency for all services, and you want to be able to drill down into individual pods. What should you do?
Select an answer first
4foundation · easy
What is a common strategy to reduce alert noise in Cloud Monitoring?
Select an answer first
5application · medium
Your production application is experiencing intermittent slowdowns. You suspect a specific function is consuming excessive CPU, but you are not sure which one. You need to identify the bottleneck without adding significant overhead to the application. What should you do?
Select an answer first

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