GCP Professional Cloud Architect Practice Question
Your company operates a revenue-critical API on GKE in two regions. The SRE team wants to introduce automated chaos experiments that randomly delete pods during business hours. Corporate policy states that the experiment must be aborted as soon as the 500-ms latency SLO is violated, and no customer traffic or data may leave the cluster. Which approach satisfies these requirements with the least operational overhead?
Export request logs to BigQuery through Pub/Sub and run a nightly SQL job that disables the chaos Job if latency spikes are detected.
Set a PodDisruptionBudget with maxUnavailable at 50% and rely on GKE surge upgrades to randomly evict pods; autoscaling will restore capacity if latency increases.
Create a Cloud Monitoring SLO for latency and attach an alerting policy that publishes to Pub/Sub; have a Cloud Function subscribed to the topic delete the chaos-experiment Job via the Kubernetes API, and trigger the Job on a work-hours schedule with Cloud Scheduler.
Deploy chaos sidecars through a blue/green rollout with Cloud Deploy and manually watch dashboards to decide whether to roll back.
Cloud Monitoring lets you define a service-level objective (SLO) for request latency and automatically calculates the remaining error budget. An alerting policy can publish a message to Pub/Sub as soon as the latency SLO is breached; a Cloud Function subscribed to the topic can use Workload Identity to call the Kubernetes API server and delete the Chaos Job, stopping the experiment immediately. The chaos job itself can be triggered on a schedule with Cloud Scheduler, runs entirely inside the cluster, and does not forward customer traffic or data outside. The other options either rely on manual observation, cannot guarantee immediate termination, or expose customer traffic outside the cluster, so they do not meet the stated requirements.
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What is an SLO in Cloud Monitoring?
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What is Cloud Monitoring, and how does it help manage SLOs?
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How does Pub/Sub enable automated responses in this scenario?
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What is a Cloud Function, and how does it interact with Kubernetes API?
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