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To prepare for the exam, candidates should have a solid understanding of cloud computing concepts and principles, as well as experience working with Google Cloud Platform services such as Compute Engine, Kubernetes Engine, Cloud Storage, and Cloud Pub/Sub. Additionally, candidates should have experience with DevOps methodologies and tools such as Git, Jenkins, and Ansible.
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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q39-Q44):
NEW QUESTION # 39
You are currently planning how to display Cloud Monitoring metrics for your organization's Google Cloud projects. Your organization has three folders and six projects:
You want to configure Cloud Monitoring dashboards lo only display metrics from the projects within one folder You need to ensure that the dashboards do not display metrics from projects in the other folders You want to follow Google-recommended practices What should you do?
- A. Use the current app-one-prod project as the scoping project
- B. Use the current app-one-dev, app-one-staging and app-one-prod projects as the scoping project for each folder
- C. Create new scoping projects for each folder
- D. Create a single new scoping project
Answer: D
NEW QUESTION # 40
Your company uses a CI/CD pipeline with Cloud Build and Artifact Registry to deploy container images to Google Kubernetes Engine (GKE). Images are tagged with the latest commit hash and promoted to production after successful testing in the development and pre-production environments. A recent production deployment caused the application to fail due to untested integration functionality, requiring a disruptive manual rollback. During the rollback, you noticed many old and unused container images accumulating in Artifact Registry. You need to improve rollout and rollback management and clean up the old container images. What should you do?
- A. Adopt Cloud Deploy for managing deployments, and implement an Artifact Registry cleanup policy.
- B. Adopt Cloud Deploy for managing deployments, and schedule a Cloud Build job for container image cleanup.
- C. Deploy Cloud Service Mesh across the GKE clusters, and manually clean up Artifact Registry images.
- D. Set up a rollback pipeline in Cloud Build, and implement an Artifact Registry cleanup policy.
Answer: A
NEW QUESTION # 41
You use Terraform to manage an application deployed to a Google Cloud environment The application runs on instances deployed by a managed instance group The Terraform code is deployed by using aCI/CD pipeline When you change the machine type on the instance template used by the managed instance group, the pipeline fails at the terraform apply stage with the following error message
You need to update the instance template and minimize disruption to the application and the number of pipeline runs What should you do?
- A. Delete the managed instance group and recreate it after updating the instance template
- B. Add a new instance template update the managed instance group to use the new instance template and delete the old instance template
- C. Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.
- D. Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template
Answer: D
NEW QUESTION # 42
You are deploying a Cloud Build job that deploys Terraform code when a Git branch is updated. While testing, you noticed that the job fails. You see the following error in the build logs:
Initializing the backend. ..
Error: Failed to get existing workspaces : querying Cloud Storage failed: googleapi : Error
403
You need to resolve the issue by following Google-recommended practices. What should you do?
- A. Change the Terraform code to use local state.
- B. Grant the roles/ storage. objectAdmin Identity and Access Management (IAM) role to the Cloud Build service account on the state file bucket.
- C. Grant the roles/ owner Identity and Access Management (IAM) role to the Cloud Build service account on the project.
- D. Create a storage bucket with the name specified in the Terraform configuration.
Answer: B
NEW QUESTION # 43
A third-party application needs to have a service account key to work properly When you try to export the key from your cloud project you receive an error "The organization policy constraint larn.disableServiceAccountKeyCreation is enforcedM You need to make the third-party application work while following Google-recommended security practices What should you do?
- A. Enable the default service account key. and download the key
- B. Add a rule to set the iam.disableServiceAccountKeyCreation policy to off in your project and create a key.
- C. Disable the service account key creation policy at the project's folder, and download the default key
- D. Remove the iam.disableServiceAccountKeyCreation policy at the organization level, and create a key.
Answer: B
Explanation:
The best option for making the third-party application work while following Google-recommended security practices is to add a rule to set the iam.disableServiceAccountKeyCreation policy to off in your project and create a key. The iam.disableServiceAccountKeyCreation policy is an organization policy that controls whether service account keys can be created in a project or organization. By default, this policy is set to on, which means that service account keys cannot be created. However, you can override this policy at a lower level, such as a project, by adding a rule to set it to off. This way, you can create a service account key for your project without affecting other projects or organizations. You should also follow the best practices for managing service account keys, such as rotating them regularly, storing them securely, and deleting them when they are no longer needed.
NEW QUESTION # 44
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