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The Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam is intended for experienced cloud DevOps professionals who have a deep understanding of cloud computing architectures and services, as well as experience in designing and implementing DevOps practices in a cloud environment. Professional-Cloud-DevOps-Engineer Exam comprises a series of multiple-choice questions and requires the candidate to demonstrate their ability to apply DevOps best practices and techniques to real-world scenarios.

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Google Professional Cloud DevOps Engineer Certification Path

The Google Professional Cloud DevOps Engineer Certification is the highest level of certification mainly focusing on the Solution Architect Professional. There is no prerequisite for this exam but still, it would be best to follow some sequence to prove immense knowledge as a Google Professional Cloud DevOps Engineer.

To earn the Google Professional-Cloud-DevOps-Engineer certification, candidates must pass a rigorous exam that consists of multiple-choice and multiple-select questions. Professional-Cloud-DevOps-Engineer Exam is designed to test the candidate's ability to apply their knowledge to real-world scenarios and use cases. Candidates must demonstrate their ability to design, develop, and deploy applications using GCP tools and services, as well as their ability to troubleshoot and optimize their applications for performance and scalability.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q191-Q196):

NEW QUESTION # 191
Your company runs an e-commerce business. The application responsible for payment processing has structured JSON logging with the following schema:
Capture and access of logs from the payment processing application is mandatory for operations, but the jsonPayload.user_email field contains personally identifiable information (PII). Your security team does not want the entire engineering team to have access to PII. You need to stop exposing PII to the engineering team and restrict access to security team members only. What should you do?

• A. Apply a jsonPayload.user_email restricted field to the _Default bucket. Grant the Log Field Accessor role to the security team members.
• B. Apply a jsonPayload.user_email exclusion filter to the _Default bucket.
• C. Modify the application to toggle inclusion of user_email when the log_user_email environment variable is set to true. Restrict the engineering team members who can change the production environment variable by using the CODEOWNERS file.
• D. Apply the conditional role binding resource.name.extract("locations/global/buckets/(bucket)/") ==
  "_Default" to the _Default bucket.

Answer: A

Explanation:
To restrict access to specific sensitive log fields (e.g. PII), Google Cloud offers Log field-level access control
. You can apply field-level restrictions and then assign the Log Field Accessor role only to trusted personnel.
"You can use field-level access control to restrict access to certain fields in your logs. For example, you can restrict access to jsonPayload.user_email."
- Cloud Logging Field-Level Access
"Grant the roles/logging.fieldAccessor role to principals that require access to these restricted fields."
- Log Field Accessor Role
This lets your operations team continue using logs while ensuring that PII is only visible to the security team
, fulfilling your compliance obligations.

NEW QUESTION # 192
You are designing a continuous delivery (CD) strategy for a new serverless application. The application is packaged as a container image, stored in Artifact Registry, and deployed to Cloud Run. Your design requires a staging environment, a fully-managed Google Cloud service, mandatory manual approval for production deployments, and a phased rollout to production. Your solution should minimize administrative overhead.
What should you do?

• A. Use a Cloud Build trigger to initiate a GitOps workflow. Configure the trigger to update a manifest in a Git repository, which a controller on a GKE Autopilot cluster then synchronizes to manage a phased traffic rollout to the new revision.
• B. Define two separate Cloud Deploy pipelines. Configure the first pipeline to deploy to staging, and configure the second pipeline to trigger and execute a phased, canary rollout to the production Cloud Run service.
• C. Use Cloud Deploy to define a single delivery pipeline that promotes a release between a staging target and a production target. Configure the production target to require approval and to automatically execute a phased rollout that incrementally shifts traffic.
• D. Use Cloud Build to create a multi-stage pipeline. Configure the trigger to require approval before starting the build. Use the deploy command with the --traffic flag to incrementally shift traffic to the new revision in production.

Answer: C

Explanation:
Comprehensive and Detailed 150 to 200 words of Explanation From Google Cloud DevOps guides documents:
Google Cloud Deploy is the platform's premier, fully-managed continuous delivery service specifically designed to simplify the progression of software through a series of environments (targets). For a Cloud Run application, Cloud Deploy provides a native, low-overhead way to define a single delivery pipeline that encapsulates both the staging and production targets. This approach directly satisfies the requirement for a fully-managed service while minimizing administrative toil compared to custom-scripted Cloud Build workflows (Option C) or complex GitOps controllers on GKE (Option B).
Key features of Cloud Deploy relevant here are its built-in support for mandatory manual approvals and automated canary/phased rollouts. By defining these in the delivery-pipeline YAML, you can ensure that a release is only promoted to production after a designated user approves it in the console or via CLI. Once approved, Cloud Deploy manages the traffic shifting to the new Cloud Run revision incrementally according to your specified percentages. This eliminates the need for managing multiple pipelines (Option D) and leverages native platform capabilities to ensure a reliable, repeatable, and secure deployment process that adheres to Google Cloud's modern DevOps and SRE deployment standards.

NEW QUESTION # 193
Your application images are built using Cloud Build and pushed to Google Container Registry (GCR). You want to be able to specify a particular version of your application for deployment based on the release version tagged in source control. What should you do when you push the image?

• A. Supply the source control tag as a parameter within the image name.
• B. Use GCR digest versioning to match the image to the tag in source control.
• C. Use Cloud Build to include the release version tag in the application image.
• D. Reference the image digest in the source control tag.

Answer: A

Explanation:
https://cloud.google.com/container-registry/docs/pushing-and-pulling

NEW QUESTION # 194
You are developing reusable infrastructure as code modules. Each module contains integration tests that launch the module in a test project. You are using GitHub for source control. You need to Continuously test your feature branch and ensure that all code is tested before changes are accepted. You need to implement a solution to automate the integration tests. What should you do?

• A. Use Cloud Build to run tests in a specific folder. Trigger Cloud Build for every GitHub pull request.
• B. Use Cloud Build to run the tests. Trigger all tests to run after a pull request is merged.
• C. Use a Jenkins server for Cl/CD pipelines. Periodically run all tests in the feature branch.
• D. Ask the pull request reviewers to run the integration tests before approving the code.

Answer: A

Explanation:
Cloud Build is a service that executes your builds on Google Cloud Platform infrastructure. Cloud Build can import source code from Google Cloud Storage, Cloud Source Repositories, GitHub, or Bitbucket, execute a build to your specifications, and produce artifacts such as Docker containers or Java archives1. Cloud Build can also run integration tests as part of your build steps2.
You can use Cloud Build to run tests in a specific folder by specifying the path to the folder in the dir field of your build step3. For example, if you have a folder named tests that contains your integration tests, you can use the following build step to run them:
steps:
- name: 'gcr.io/cloud-builders/go'
args: ['test', '-v']
dir: 'tests'
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You can use Cloud Build to trigger builds for every GitHub pull request by using the Cloud Build GitHub app. The app allows you to automatically build on Git pushes and pull requests and view your build results on GitHub and Google Cloud console4. You can configure the app to run builds on specific branches, tags, or paths5. For example, if you want to run builds on pull requests that target the master branch, you can use the following trigger configuration:
includedFiles:
- '**'
name: 'pull-request-trigger'
github:
name: 'my-repo'
owner: 'my-org'
pullRequest:
branch: '

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