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To become a Certified Professional Cloud DevOps Engineer, the candidate must have a deep understanding of agile and DevOps methodologies, as well as proficiency in GCP services such as Kubernetes, Google Cloud Build, Google Cloud Functions, Google Cloud Monitoring, and more. Professional-Cloud-DevOps-Engineer Exam also tests the candidate's ability to design and implement continuous integration/continuous delivery (CI/CD) pipelines, automate infrastructure deployments, and monitor and optimize application performance using GCP tools.

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Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer) Exam is designed for professionals who have expertise in DevOps practices and technologies in the Google Cloud Platform. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification validates the knowledge and skills required to design, develop, and implement DevOps processes and practices on Google Cloud Platform. Professional-Cloud-DevOps-Engineer exam covers a wide range of topics including continuous integration and delivery, infrastructure as code, monitoring and logging, and site reliability engineering. It is ideal for DevOps engineers, site reliability engineers, automation engineers, and cloud architects who work with Google Cloud Platform.

Google Professional-Cloud-DevOps-Engineer Exam is designed to test the candidate's knowledge and skills related to DevOps engineering practices and Google Cloud technologies. Professional-Cloud-DevOps-Engineer exam comprises of two sections – the first section includes multiple-choice questions, while the second section includes practical scenarios that test the candidate's ability to apply their knowledge and skills to real-world situations.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q37-Q42):

NEW QUESTION # 37
You are running a real-time gaming application on Compute Engine that has a production and testing environment. Each environment has their own Virtual Private Cloud (VPC) network. The application frontend and backend servers are located on different subnets in the environment's VPC. You suspect there is a malicious process communicating intermittently in your production frontend servers. You want to ensure that network traffic is captured for analysis. What should you do?

A. Enable VPC Flow Logs on the production VPC network frontend and backend subnets only with a sample volume scale of 0.5.
B. Enable VPC Flow Logs on the production VPC network frontend and backend subnets only with a sample volume scale of 1.0.
C. Enable VPC Flow Logs on the testing and production VPC network frontend and backend subnets with a volume scale of 1.0. Apply changes in testing before production.
D. Enable VPC Flow Logs on the testing and production VPC network frontend and backend subnets with a volume scale of 0.5. Apply changes in testing before production.

Answer: C

NEW QUESTION # 38
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. Reference the image digest in the source control tag.
D. Use Cloud Build to include the release version tag in the application image.

Answer: D

NEW QUESTION # 39
Your organization is using Helm to package containerized applications Your applications reference both public and private charts Your security team flagged that using a public Helm repository as a dependency is a risk You want to manage all charts uniformly, with native access control and VPC Service Controls What should you do?

A. Store public and private charts by using GitHub Enterprise with Google Workspace as the identity provider
B. Configure a Helm chart repository server to run in Google Kubernetes Engine (GKE) with Cloud Storage bucket as the storage backend
C. Store public and private charts in OCI format by using Artifact Registry
D. Store public and private charts by using Git repository Configure Cloud Build to synchronize contents of the repository into a Cloud Storage bucket Connect Helm to the bucket by using https: // [bucket] .srorage.googleapis.com/ [holnchart] as the Helm repository

Answer: C

Explanation:
The best option for managing all charts uniformly, with native access control and VPC Service Controls is to store public and private charts in OCI format by using Artifact Registry. Artifact Registry is a service that allows you to store and manage container images and other artifacts in Google Cloud. Artifact Registry supports OCI format, which is an open standard for storing container images and other artifacts such as Helm charts. You can use Artifact Registry to store public and private charts in OCI format and manage them uniformly. You can also use Artifact Registry's native access control features, such as IAM policies and VPC Service Controls, to secure your charts and control who can access them.

NEW QUESTION # 40
You are leading a DevOps project for your organization. The DevOps team is responsible for managing the service infrastructure and being on-call for incidents. The Software Development team is responsible for writing, submitting, and reviewing code. Neither team has any published SLOs. You want to design a new joint-ownership model for a service between the DevOps team and the Software Development team. Which responsibilities should be assigned to each team in the new joint-ownership model?

A. Option C
B. Option D
C. Option A
D. Option B

Answer: B

NEW QUESTION # 41
Your organization has a containerized web application that runs on-premises As part of the migration plan to Google Cloud you need to select a deployment strategy and platform that meets the following acceptance criteria
1 The platform must be able to direct traffic from Android devices to an Android-specific microservice
2 The platform must allow for arbitrary percentage-based traffic splitting
3 The deployment strategy must allow for continuous testing of multiple versions of any microservice What should you do?

A. Deploy the canary release of the application to Compute Engine Use Anthos Service Mesh with Compute Engine to direct 10% of user traffic to the canary release by configuring the virtual service.
B. Deploy the canary release of the application to Cloud Run Use traffic splitting to direct 10% of user traffic to the canary release based on the revision tag
C. Deploy the canary release to Google Kubernetes Engine with Anthos Sen/ice Mesh Use traffic splitting to direct 10% of user traffic to the new version based on the user-agent header configured in the virtual service
D. Deploy the canary release of the application to App Engine Use traffic splitting to direct a subset of user traffic to the new version based on the IP address

Answer: C

NEW QUESTION # 42
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