Google Professional Cloud DevOps Engineer
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You have a containerized application with a new version that has been tested and is ready for production deployment on Google Kubernetes Engine (GKE). Since full load testing was not possible in the pre-production environment, you need to ensure the application performs well post-deployment while maintaining an automated deployment process. What is the recommended approach?
A
Deploy the application through a continuous delivery pipeline by using canary deployments. Use Cloud Monitoring to look for performance issues, and ramp up traffic as supported by the metrics.
B
Deploy the application through a continuous delivery pipeline by using blue/green deployments. Migrate traffic to the new version of the application and use Cloud Monitoring to look for performance issues.
C
Deploy the application by using kubectl and use Config Connector to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues.
D
Deploy the application by using kubectl and set the spec.updateStrategy.type field to RollingUpdate. Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.