Topic: Google Professional Cloud DevOps Engineer topic 1 question 100

The new version of your containerized application has been tested and is ready to be deployed to production on Google Kubernetes Engine (GKE). You could not fully load-test the new version in your pre-production environment, and you need to ensure that the application does not have performance problems after deployment. Your deployment must be automated. What should you do?

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.

Re: Google Professional Cloud DevOps Engineer topic 1 question 100

I vote for A as in Blue/Green deployment you can rollback quickly after facing the performance issue, but in Canary you can detect performance issue on partial deployment and rollback before the issue get affected.

Re: Google Professional Cloud DevOps Engineer topic 1 question 100

You meant option B?

Re: Google Professional Cloud DevOps Engineer topic 1 question 100

no PrayasM meant that canary fits what got asked more

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Re: Google Professional Cloud DevOps Engineer topic 1 question 100

After consideration, Canary approach is better in this specific scenario as it allows for monitoring the performance of the new version in production while minimizing the risk of widespread issues.

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Re: Google Professional Cloud DevOps Engineer topic 1 question 100

B. Blue/green deployments involve deploying the new version alongside the existing one, routing only a portion of the traffic to the new version initially. Once you verify that the new version is performing well and there are no issues, you can fully migrate traffic to the new version. This allows for a safe rollback if any issues arise.

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Re: Google Professional Cloud DevOps Engineer topic 1 question 100

After consideration, Canary approach is better in this specific scenario as it allows for monitoring the performance of the new version in production while minimizing the risk of widespread issues.

Re: Google Professional Cloud DevOps Engineer topic 1 question 100

The recommended approach to automate the deployment of the new version of a containerized application to production on Google Kubernetes Engine (GKE) while addressing potential performance issues is (Option A).

Utilizing canary deployments within a continuous delivery pipeline allows for a controlled and gradual rollout of the new version. By monitoring performance metrics with Cloud Monitoring, the deployment process can be informed by real-time insights. The traffic can be incrementally increased as supported by the monitored metrics, minimizing the risk of performance problems.

This approach provides a safety net, allowing for quick identification and mitigation of issues before a full deployment, ensuring a smooth transition to the new version with minimal impact on production.