Question

A retail company deploys its customer-facing web application to Google Kubernetes Engine several times per day. After a recent release caused a checkout outage that went undetected until customer complaints arrived, the release engineering team wants a deployment strategy that automatically exposes new versions to a small subset of live traffic, monitors error rates and latency against defined thresholds, and rolls back automatically if metrics degrade—without requiring a full duplicate production environment. Which approach best meets these requirements?

Accepted Answer

Use a canary deployment managed by Cloud Deploy with automated rollback triggered by Cloud Monitoring SLO-based alerting on error rate and latency.

Answer

Provision a full parallel blue-green environment and cut over 100% of traffic to the green environment after manual smoke testing.

Answer

Adopt a recreate deployment strategy that terminates all old pods before starting new ones to guarantee version consistency.

Answer

Deploy all changes directly to production during a nightly maintenance window and rely on daily database backups for recovery.