GCP Professional Cloud Architect Practice Question
Your team operates a global e-commerce platform on Google Kubernetes Engine (GKE). New versions are rolled out with Cloud Deploy using a canary strategy that shifts traffic from 1 % to 100 % over 30 minutes. The SRE lead asks you to ensure that any deployment automatically rolls back if the percentage of HTTP 5xx responses recorded in Cloud Logging rises above 2 % for two consecutive minutes, eliminating the need for human intervention. Which approach best meets this requirement while following the operational excellence principle of automating responses to common operational events?
Use Error Reporting to open a P1 incident when exception counts spike and have the on-call engineer execute a gcloud deploy rollback command.
Schedule a Cloud Scheduler job that invokes a Cloud Run service to scale the canary deployment to zero when 5xx errors exceed 2 %, then manually re-enable the service after investigation.
Configure a Cloud Build trigger that runs every minute, queries Cloud Logging for 5xx rates, and, if above threshold, executes gcloud container clusters rollback for the canary workload.
Create a logs-based metric for 5xx errors, configure a Cloud Monitoring alert to publish to Pub/Sub when the 2 % threshold is exceeded for two minutes, and trigger a Cloud Function that calls the Cloud Deploy API to promote the previous release.
Creating a logs-based metric for 5xx errors lets Cloud Monitoring evaluate service health in near real time. An alerting policy can publish to Pub/Sub when the two-minute, above-2 % threshold is breached. A Cloud Function subscribed to that topic can call the Cloud Deploy REST API to promote the previously stable release, performing a fully automated rollback. This design is event-driven, minimizes manual effort, and is consistent with the Well-Architected recommendation to automate operational procedures.
The other options rely on manual action (Error Reporting escalation, SMS to on-call) or inefficient, continuously running jobs (Cloud Build or Cloud Scheduler polling), which contradict the goal of automated, low-overhead remediation.
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