Crucial Exams

GCP Professional Cloud Architect Practice Question

Your company runs a prediction service on two regional GKE clusters behind an HTTP(S) Load Balancer. After several pods were recently OOM-killed without warning, you must deliver a solution that provides real-time and historical per-container memory dashboards spanning both clusters, triggers an alert when more than 10 percent of pods in any deployment use over 90 percent of their memory limit for at least five minutes, adds no in-pod agents, integrates with Cloud IAM, and can notify PagerDuty. Which approach best meets these goals?

  • Enable Cloud Operations for GKE on all clusters to export workload metrics to Cloud Monitoring, create a metrics scope and dashboard for container/memory/used_bytes, then define an MQL alerting policy that fires when over 10 % of pods exceed 90 % memory for five minutes, using a PagerDuty notification channel.

  • Add Prometheus sidecar containers to every pod to scrape memory metrics and forward them to a self-hosted Prometheus server, use Alertmanager for PagerDuty notifications, and Grafana for dashboards.

  • Turn on node-level Cloud Monitoring only in one cluster and configure an external Pingdom probe to watch memory usage, with PagerDuty alerts triggered by Pingdom.

  • Create a scheduled Cloud Run service that polls the Kubernetes API for pod statistics, stores the data in BigQuery, visualizes it in Looker Studio, and uses budget alerts to notify PagerDuty when thresholds are breached.

GCP Professional Cloud Architect
Analyzing and optimizing technical and business processes
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