Google Professional Cloud DevOps Engineer Question 63
Select 2Google Cloud PlatformYour company uses Google Cloud for hosting critical applications. You are tasked with configuring a deployment process for a new application in Cloud Deploy. The process must ensure that deployments to the production environment can only occur after approval from both the QA team and the Security team. How should you configure this in Cloud Deploy?
- A
Define a pre-deployment approval gate in the production pipeline stage for the QA team and Security team.
- B
Create a separate pipeline for production that requires manual approval from the QA team and Security team.
- C
Use IAM roles to grant QA and Security teams permission to approve releases in the production pipeline stage.
- D
Configure a post-deployment approval gate in the production pipeline stage for the QA and Security teams.
Show answer and explanation
Correct answers: A, C
Explanation
To enforce approvals in Cloud Deploy before deploying to production, you should define pre-deployment approval gates in the production pipeline stage and use IAM roles to ensure the right teams have the permissions to approve. This approach ensures compliance and reduces the risk of unauthorized deployments, aligning with best practices for configuring deployment processes in Google Cloud.
- A. Correct.
This is correct because defining a pre-deployment approval gate in the production pipeline stage allows the QA and Security teams to review and approve the deployment before it proceeds.
- B. Incorrect.
This is incorrect because creating a separate pipeline for production is unnecessary and does not align with Cloud Deploy's recommended practices. Approval gates can be configured within the existing pipeline.
- C. Correct.
This is correct because using IAM roles ensures that only authorized QA and Security team members can approve the deployment to production.
- D. Incorrect.
This is incorrect because post-deployment approval gates are not suitable for preventing deployment; they occur after the deployment has already been executed.