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Google Professional-Cloud-DevOps-Engineer is a certification exam that is designed to test an individual's ability to effectively integrate and manage cloud technologies with DevOps practices. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is intended for cloud professionals who have a strong background in software development, infrastructure management, and operations.

Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:

Topic	Details
Topic 1	Optimizing the service performance: It delves into the identification of service performance issues, implementation of debugging tools in Google Cloud, and optimization of resource utilization and costs.
Topic 2	Applying site reliability engineering practices to a service: It deals with velocity, and reliability of the service, service lifecycle, healthy communication, and collaboration for operations. The topic also discusses mitigation of incident impact on users and conducting a postmortem.
Topic 3	Bootstrapping a Google Cloud organization for DevOps: It discusses the overall resource hierarchy for an organization, infrastructure as code, CI CD architecture stack in Google Cloud, hybrid, and multi-cloud environments. Moreover, the topic focuses on multiple environments including staging and production.
Topic 4	Implementing service monitoring strategies: This topic covers structured and unstructured logs from Compute Engine, GKE, and serverless platforms using Cloud Logging. Its sub-topics include coverage of metrics with Cloud Monitoring, dashboards and alerts in Cloud Monitoring, Cloud Logging platform, and logging and monitoring access controls.
Topic 5	Building and implementing CI CD pipelines for a service: Management and designing of CI CD pipelines, implementation of CI CD pipelines, management of CI CD configuration, and secrets are discussed in this paper. Moreover, it focuses on storage methods and key rotation services, and finally securing the CI CD deployment pipeline.

Google Professional-Cloud-DevOps-Engineer Certification is ideal for professionals who work in DevOps roles and are proficient in using GCP to build and deploy applications. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is also suitable for professionals who want to enhance their skills and advance their careers in the DevOps field. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is recognized globally and is highly valued by employers, making it an excellent investment for IT professionals who want to stay ahead of the competition.

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q203-Q208):

NEW QUESTION # 203
You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub. You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?

A. Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.
B. Disable the CI pipeline and revert to manually building and pushing the artifacts.
C. Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.
D. Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.

Answer: B

NEW QUESTION # 204
Your company experiences bugs, outages, and slowness in its production systems. Developers use the production environment for new feature development and bug fixes. Configuration and experiments are done in the production environment, causing outages for users. Testers use the production environment for load testing, which often slows the production systems. You need to redesign the environment to reduce the number of bugs and outages in production and to enable testers to load test new features. What should you do?

A. Create a development environment for writing code and a test environment for configurations, experiments, and load testing.
B. Create a development environment with smaller server capacity and give access only to developers and testers.
C. Secure the production environment to ensure that developers can't change it and set up one controlled update per year.
D. Create an automated testing script in production to detect failures as soon as they occur.

Answer: A

NEW QUESTION # 205
You want to share a Cloud Monitoring custom dashboard with a partner team What should you do?

A. Download the JSON definition of the dashboard, and send the JSON file to the partner team
B. Export the metrics to BigQuery Use Looker Studio to create a dashboard, and share the dashboard with the partner team
C. Copy the Monitoring Query Language (MQL) query from the dashboard; and send the MQL query to the partner team
D. Provide the partner team with the dashboard URL to enable the partner team to create a copy of the dashboard

Answer: D

Explanation:
The best option for sharing a Cloud Monitoring custom dashboard with a partner team is to provide the partner team with the dashboard URL to enable the partner team to create a copy of the dashboard. A Cloud Monitoring custom dashboard is a dashboard that allows you to create and customize charts and widgets to display metrics, logs, and traces from your Google Cloud resources and applications. You can share a custom dashboard with a partner team by providing them with the dashboard URL, which is a link that allows them to view the dashboard in their browser. The partner team can then create a copy of the dashboard in their own project by using the Copy Dashboard option. This way, they can access and modify the dashboard without affecting the original one.

NEW QUESTION # 206
Your Cloud Run application writes unstructured logs as text strings to Cloud Logging. You want to convert the unstructured logs to JSON-based structured logs. What should you do?

A. A Install a Fluent Bit sidecar container, and use a JSON parser.
B. Install the log agent in the Cloud Run container image, and use the log agent to forward logs to Cloud Logging.
C. Configure the log agent to convert log text payload to JSON payload.
D. Modify the application to use Cloud Logging software development kit (SDK), and send log entries with a jsonPay10ad field.

Answer: D

NEW QUESTION # 207
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. U2026/2/4se the Terraform module so that Secret Manager can retrieve credentials.
C. Add the auth application-default command as a step in Jenkins before running the Terraform commands.
D. 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.

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 # 208
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