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Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer) Certification Exam is a valuable certification for cloud DevOps engineers who want to validate their skills and knowledge in designing, developing, and implementing cloud solutions using GCP services and tools. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam is challenging and requires candidates to have a good understanding of cloud computing, software development, and DevOps practices. Passing the certification exam can enhance the candidate's career prospects and demonstrate their expertise in cloud DevOps engineering.

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q42-Q47):

NEW QUESTION # 42
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 B
C. Option A
D. Option D

Answer: D

Explanation:
Explanation
The correct answer is D. Option D.
According to the DevOps best practices, a joint-ownership model for a service between the DevOps team and the Software Development team should follow these principles12:
The DevOps team and the Software Development team should share the responsibility and collaboration for managing the service infrastructure, performing code reviews, and adopting and sharing SLOs for the service.
The DevOps team and the Software Development team should have end-to-end ownership of the service, from design to development to deployment to operation to maintenance.
The DevOps team and the Software Development team should use common tools and processes to facilitate communication, coordination, and feedback.
The DevOps team and the Software Development team should align their goals and incentives with the business outcomes and customer satisfaction.
Option D is the only option that reflects these principles. Option D assigns both teams the responsibilities of managing the service infrastructure, performing code reviews, and adopting and sharing SLOs for the service.
Option D also implies that both teams have end-to-end ownership of the service, as they are involved in every stage of the service lifecycle. Option D also encourages both teams to use common tools and processes, such as GitLab3, to collaborate and communicate effectively. Option D also aligns both teams with the business outcomes and customer satisfaction, as they use SLOs to measure and improve the service quality.
The other options are incorrect because they do not follow the DevOps best practices. Option A is incorrect because it assigns only the DevOps team the responsibility of managing the service infrastructure, which creates a silo between the two teams and reduces their collaboration. Option A also does not assign any responsibility for adopting and sharing SLOs for the service, which means that both teams lack a common metric for measuring and improving the service quality. Option B is incorrect because it assigns only the Software Development team the responsibility of performing code reviews, which creates a gap between the two teams and reduces their feedback. Option B also does not assign any responsibility for adopting and sharing SLOs for the service, which means that both teams lack a common metric for measuring and improving the service quality. Option C is incorrect because it assigns both teams the same responsibilities as option A and option B, which combines their drawbacks.

NEW QUESTION # 43
You have a set of applications running on a Google Kubernetes Engine (GKE) cluster, and you are using Stackdriver Kubernetes Engine Monitoring. You are bringing a new containerized application required by your company into production. This application is written by a third party and cannot be modified or reconfigured. The application writes its log information to /var/log/app_messages.log, and you want to send these log entries to Stackdriver Logging. What should you do?

A. Write a script to tail the log file within the pod and write entries to standard output. Run the script as a sidecar container with the application's pod. Configure a shared volume between the containers to allow the script to have read access to /var/log in the application container.
B. Install Kubernetes on Google Compute Engine (GCE> and redeploy your applications. Then customize the built-in Stackdriver Logging configuration to tail the log file in the application's pods and write to Stackdriver Logging.
C. Use the default Stackdriver Kubernetes Engine Monitoring agent configuration.
D. Deploy a Fluentd daemonset to GKE. Then create a customized input and output configuration to tail the log file in the application's pods and write to Slackdriver Logging.

Answer: D

Explanation:
Explanation
https://cloud.google.com/architecture/customizing-stackdriver-logs-fluentd Besides the list of default logs that the Logging agent streams by default, you can customize the Logging agent to send additional logs to Logging or to adjust agent settings by adding input configurations. The configuration definitions in these sections apply to the fluent-plugin-google-cloud output plugin only and specify how logs are transformed and ingested into Cloud Logging.
https://cloud.google.com/logging/docs/agent/logging/configuration#configure

NEW QUESTION # 44
You currently store the virtual machine (VM) utilization logs in Stackdriver. You need to provide an easy-to- share interactive VM utilization dashboard that is updated in real time and contains information aggregated on a quarterly basis. You want to use Google Cloud Platform solutions. What should you do?

A. 1. Export VM utilization logs from Stackdriver to BigQuery.
2. Create a dashboard in Data Studio.
3. Share the dashboard with your stakeholders.
B. 1. Export VM utilization logs from Stackdriver to a Cloud Storage bucket.
2. Enable the Cloud Storage API to pull the logs programmatically.
3. Build a custom data visualization application.
4. Display the pulled logs in a custom dashboard.
C. 1. Export VM utilization logs from Stackdriver to Cloud Pub/Sub.
2. From Cloud Pub/Sub, send the logs to a Security Information and Event Management (SIEM) system.
3. Build the dashboards in the SIEM system and share with your stakeholders.
D. 1. Export VM utilization logs from Stackdriver to BigQuery.
2. From BigQuery, export the logs to a CSV file.
3. Import the CSV file into Google Sheets.
4. Build a dashboard in Google Sheets and share it with your stakeholders.

Answer: A

NEW QUESTION # 45
You support a web application that is hosted on Compute Engine. The application provides a booking service for thousands of users. Shortly after the release of a new feature, your monitoring dashboard shows that all users are experiencing latency at login. You want to mitigate the impact of the incident on the users of your service. What should you do first?

A. Deploy a new release to see whether it fixes the problem.
B. Review the Stackdriver monitoring.
C. Roll back the recent release.
D. Upsize the virtual machines running the login services.

Answer: D

Explanation:
Explanation
Rollback to previous stable version. Then you need to find what is causing the issue.

NEW QUESTION # 46
You are using Terraform to manage infrastructure as code within a Cl/CD pipeline You notice that multiple copies of the entire infrastructure stack exist in your Google Cloud project, and a new copy is created each time a change to the existing infrastructure is made You need to optimize your cloud spend by ensuring that only a single instance of your infrastructure stack exists at a time. You want to follow Google-recommended practices What should you do?

A. Confirm that the pipeline is storing and retrieving the terraform. if state file from Cloud Storage with the Terraform gcs backend
B. Create a new pipeline to delete old infrastructure stacks when they are no longer needed
C. Update the pipeline to remove any existing infrastructure before you apply the latest configuration
D. Verify that the pipeline is storing and retrieving the terrafom.tfstat* file from a source control

Answer: A

Explanation:
Explanation
The best option for optimizing your cloud spend by ensuring that only a single instance of your infrastructure stack exists at a time is to confirm that the pipeline is storing and retrieving the terraform.tfstate file from Cloud Storage with the Terraform gcs backend. The terraform.tfstate file is a file that Terraform uses to store the current state of your infrastructure. The Terraform gcs backend is a backend type that allows you to store the terraform.tfstate file in a Cloud Storage bucket. By using the Terraform gcs backend, you can ensure that your pipeline has access to the latest state of your infrastructure and avoid creating multiple copies of the entire infrastructure stack.

NEW QUESTION # 47
......

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Valuable Google Professional-Cloud-DevOps-Engineer Feedback - Exam Professional-Cloud-DevOps-Engineer Demo

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q42-Q47):

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