GCP Associate Cloud Engineer Practice Question

Your team operates a Java web service in a GKE cluster. Users report brief latency spikes during traffic peaks, and you suspect a CPU-intensive code path is responsible. Monitoring and Logging are already enabled on the cluster. Which action will let you begin collecting production CPU profiles in Cloud Profiler with the least disruption to the running Pods?

Enable the Cloud Profiler API in the project and rely on the Ops Agent already running on each node to upload CPU samples automatically.
Add the Cloud Profiler Java agent to the application's startup command and grant the Pod's service account the Cloud Profiler Agent IAM role.
Convert the cluster to Autopilot mode and set an --enable-cloud-profiler flag on the control plane so profiles are gathered for all workloads.
Deploy a DaemonSet that periodically SSHes into each node, captures stack traces, and pushes them to Cloud Storage for later analysis.

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Answer Description

Cloud Profiler does not gather data automatically from GKE workloads. The application process itself must load the Cloud Profiler language agent so that it can sample stack traces and send them to the Profiler backend. In GKE, the agent typically is added by including the Profiler Java agent JAR and setting the appropriate startup options or environment variables. In addition, the Kubernetes service account used by the Pods must have the roles/cloudprofiler.agent IAM role so the agent can write profile data. Simply enabling the API or relying on the Ops Agent running on the nodes does not activate profiling for in-process code, and there is no cluster-level flag or external trace-collection script that will populate Cloud Profiler.

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