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GCP Professional Cloud Architect Practice Question

Your organization's customer-facing service runs as a containerized Java deployment on a busy GKE cluster. Memory consumption occasionally grows until Pods are OOM-killed, but the problem never manifests in staging. Leadership asks you to collect production-grade performance data to locate the memory hot spots while keeping user-visible impact to a minimum. Which action best satisfies these requirements?

  • Replicate production load in a separate test cluster and run an on-host Java profiler that records full heap dumps for post-mortem analysis.

  • Add the Cloud Profiler Java agent to the Pods and let it run continuously; its statistical sampling incurs well under 5% runtime overhead, so production traffic remains largely unaffected while detailed allocation flame graphs are collected.

  • Instrument the service with Cloud Trace and export traces to BigQuery; query the trace data to identify methods responsible for increased memory use.

  • Enable remote debugging on the production Pods and attach an IDE debugger during peak traffic to capture live heap information when memory spikes occur.

GCP Professional Cloud Architect
Ensuring solution and operations excellence
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