Crucial Exams

GCP Professional Cloud Architect Practice Question

Your organization runs a GKE cluster with 12 microservices written in Java, Go, and Node.js. During seasonal peaks, the cluster autoscaler adds many nodes, increasing costs. Leadership wants data that pinpoints which functions inside each service consume the most CPU time and heap so developers can optimize the code base. The solution must:

  • Collect data continuously in production with sampling overhead below 1 %.
  • Support all three runtimes without modifying the cluster nodes.
  • Allow engineers to compare profiles across different deploys to verify improvements. Which approach best satisfies these requirements?

  • Create logs-based metrics from application logs to calculate average CPU and heap usage for each service, then chart the results in Cloud Monitoring.

  • Turn on automatic instrumentation in Cloud Trace and analyze request latency heat maps to infer which functions consume the most resources.

  • Add the Cloud Profiler agent to each service's build, enable continuous CPU and heap profiling in production, and use the Profiler UI to compare profiles over time.

  • Deploy the Ops Agent as a DaemonSet on every node and rely on Cloud Monitoring dashboards for host-level CPU and memory metrics.

GCP Professional Cloud Architect
Ensuring solution and operations excellence
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