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The Google Professional-Cloud-DevOps-Engineer Exam is designed to evaluate the candidate's ability to design and implement DevOps processes and practices using the Google Cloud Platform. This includes skills such as developing and managing continuous integration and delivery pipelines, configuring monitoring and alerting strategies, implementing automated testing frameworks, and managing infrastructure as code.

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Google Professional-Cloud-DevOps-Engineer Exam is a challenging exam that requires candidates to have a strong understanding of DevOps engineering practices and Google Cloud technologies. To prepare for the exam, candidates should have a solid understanding of the topics covered in the exam, such as continuous delivery, automation, infrastructure as code, and monitoring. They should also have hands-on experience with Google Cloud technologies and related DevOps tools and practices.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q103-Q108):

NEW QUESTION # 103
Your uses Jenkins running on Google Cloud VM instances for CI/CD. You need to extend the functionality to use infrastructure as code automation by using Terraform. You must ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. You want to follow Google-recommended practices- What should you do?

A. Confirm that the Jenkins VM instance has an attached service account with the appropriate Identity and Access Management (IAM) permissions.
B. use the Terraform module so that Secret Manager can retrieve credentials.
C. Create a dedicated service account for the Terraform instance. Download and copy the secret key value to the GOOGLE environment variable on the Jenkins server.
D. Add the auth application-default command as a step in Jenkins before running the Terraform commands.

Answer: A

Explanation:
The correct answer is C)
Confirming that the Jenkins VM instance has an attached service account with the appropriate Identity and Access Management (IAM) permissions is the best way to ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. This follows the Google-recommended practice of using service accounts to authenticate and authorize applications running on Google Cloud1. Service accounts are associated with private keys that can be used to generate access tokens for Google Cloud APIs2. By attaching a service account to the Jenkins VM instance, Terraform can use the Application Default Credentials (ADC) strategy to automatically find and use the service account credentials3.
Answer A is incorrect because the auth application-default command is used to obtain user credentials, not service account credentials. User credentials are not recommended for applications running on Google Cloud, as they are less secure and less scalable than service account credentials1.
Answer B is incorrect because it involves downloading and copying the secret key value of the service account, which is not a secure or reliable way of managing credentials. The secret key value should be kept private and not exposed to any other system or user2. Moreover, setting the GOOGLE environment variable on the Jenkins server is not a valid way of providing credentials to Terraform. Terraform expects the credentials to be either in a file pointed by the GOOGLE_APPLICATION_CREDENTIALS environment variable, or in a provider block with the credentials argument3.
Answer D is incorrect because it involves using the Terraform module for Secret Manager, which is a service that stores and manages sensitive data such as API keys, passwords, and certificates. While Secret Manager can be used to store and retrieve credentials, it is not necessary or sufficient for authorizing the Terraform Jenkins instance. The Terraform Jenkins instance still needs a service account with the appropriate IAM permissions to access Secret Manager and other Google Cloud resources.

NEW QUESTION # 104
You manage several production systems that run on Compute Engine in the same Google Cloud Platform (GCP) project. Each system has its own set of dedicated Compute Engine instances. You want to know how must it costs to run each of the systems. What should you do?

A. Name each virtual machine (VM) after the system it runs. Set up a usage report export to a Cloud Storage bucket. Configure the bucket as a source in BigQuery to query costs based on VM name.
B. In the Google Cloud Platform Console, use the Cost Breakdown section to visualize the costs per system.
C. Assign all instances a label specific to the system they run. Configure BigQuery billing export and query costs per label.
D. Enrich all instances with metadata specific to the system they run. Configure Stackdriver Logging to export to BigQuery, and query costs based on the metadata.

Answer: C

Explanation:
https://cloud.google.com/billing/docs/how-to/export-data-bigquery

NEW QUESTION # 105
Your application artifacts are being built and deployed via a CI/CD pipeline. You want the CI/CD pipeline to securely access application secrets. You also want to more easily rotate secrets in case of a security breach.
What should you do?

A. Prompt developers for secrets at build time. Instruct developers to not store secrets at rest.
B. Store secrets in a separate configuration file on Git. Provide select developers with access to the configuration file.
C. Encrypt the secrets and store them in the source code repository. Store a decryption key in a separate repository and grant your pipeline access to it.
D. Store secrets in Cloud Storage encrypted with a key from Cloud KMS. Provide the CI/CD pipeline with access to Cloud KMS via IAM.

Answer: D

NEW QUESTION # 106
Your company is developing applications that are deployed on Google Kubernetes Engine (GKE). Each team manages a different application. You need to create the development and production environments for each team, while minimizing costs. Different teams should not be able to access other teams' environments. What should you do?

A. Create a Development and a Production GKE cluster in separate projects. In each cluster, create a Kubernetes namespace per team, and then configure Kubernetes Role-based access control (RBAC) so that each team can only access its own namespace.
B. Create a Development and a Production GKE cluster in separate projects. In each cluster, create a Kubernetes namespace per team, and then configure Identity Aware Proxy so that each team can only access its own namespace.
C. Create one GCP Project per team. In each project, create a cluster for Development and one for Production. Grant the teams IAM access to their respective clusters.
D. Create one GCP Project per team. In each project, create a cluster with a Kubernetes namespace for Development and one for Production. Grant the teams IAM access to their respective clusters.

Answer: A

Explanation:
Explanation
https://cloud.google.com/architecture/prep-kubernetes-engine-for-prod#roles_and_groups

NEW QUESTION # 107
You need to build a CI/CD pipeline for a containerized application in Google Cloud Your development team uses a central Git repository for trunk-based development You want to run all your tests in the pipeline for any new versions of the application to improve the quality What should you do?

A. 1. Trigger Cloud Build to build the application container and run unit tests with the container2. If unit tests are successful, deploy the application container to a testing environment, and run integration tests3. If the integration tests are successful the pipeline deploys the application container to the production environment After that, run acceptance tests
B. 1. Install a Git hook to require developers to run unit tests before pushing the code to a central repositoryIf all tests are successful build a container2. Trigger Cloud Build to deploy the application container to a testing environment, and run integrationtests and acceptance tests3. If all tests are successful tag the code as production ready Trigger Cloud Build to build and deploy the application container to the production environment
C. 1. Trigger Cloud Build to run unit tests when the code is pushed If all unit tests are successful, build and push the application container to a central registry.2. Trigger Cloud Build to deploy the container to a testing environment, and run integration tests and acceptance tests3. If all tests are successful the pipeline deploys the application to the production environment and runs smoke tests
D. 1. Install a Git hook to require developers to run unit tests before pushing the code to a central repository2. Trigger Cloud Build to build the application container Deploy the application container to a testing environment, and run integration tests3. If the integration tests are successful deploy the application container to your production environment. and run acceptance tests

Answer: C

NEW QUESTION # 108
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