PROFESSIONAL-CLOUD-DEVOPS-ENGINEER Question #62: Real Exam Question with Answer & Explanation

Question

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?

Options

• ADeploy the application through a continuous delivery pipeline by using canary deployments. Use
• BDeploy the application through a continuous delivery pipeline by using blue/green deployments.
• CDeploy the application by using kubectl and use Config Connector to slowly ramp up traffic
• DDeploy the application by using kubectl and set the spec.updateStrategy.type field to

Explanation

To mitigate deployment risks from insufficient load testing for a new GKE application version, use a continuous delivery pipeline with canary deployments.

Common mistakes.

• B. Blue/green deployments switch all traffic to the new version simultaneously, which carries a higher risk of performance degradation if the new version has issues and wasn't fully load-tested.
• C. Using kubectl is a manual or script-based approach, not a full continuous delivery pipeline, and Config Connector is for resource management, not dynamic traffic shifting for new deployments.
• D. Setting spec.updateStrategy.type in Kubernetes controls how pods are updated (e.g., rolling update), but it doesn't provide the granular traffic shifting and monitoring capabilities of a canary deployment for risk mitigation.

Concept tested. Canary deployments for risk mitigation

Reference. https://cloud.google.com/architecture/application-deployment-strategies#canary_deployments

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