PROFESSIONAL-CLOUD-DEVOPS-ENGINEER TRUSTED EXAM RESOURCE - PROFESSIONAL-CLOUD-DEVOPS-ENGINEER LEAD2PASS REVIEW

Professional-Cloud-DevOps-Engineer Trusted Exam Resource - Professional-Cloud-DevOps-Engineer Lead2pass Review

Professional-Cloud-DevOps-Engineer Trusted Exam Resource - Professional-Cloud-DevOps-Engineer Lead2pass Review

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Google Professional-Cloud-DevOps-Engineer exam is a certification test designed to assess the knowledge and skills of individuals in the field of Cloud DevOps engineering. Professional-Cloud-DevOps-Engineer exam is one of the most sought-after certifications for IT professionals who want to prove their proficiency in designing, building, and managing applications on the Google Cloud Platform.

Google Professional-Cloud-DevOps-Engineer certification is a valuable asset for professionals who want to advance their careers in the cloud computing industry. It demonstrates their expertise in designing and managing cloud-based solutions using Google Cloud technologies. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification also provides a competitive advantage in the job market, as it validates the candidate's skills and knowledge in a rapidly growing field. Overall, the Professional-Cloud-DevOps-Engineer Certification is an excellent choice for professionals who want to enhance their career prospects and stay up-to-date with the latest trends in cloud-based DevOps engineering.

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q15-Q20):

NEW QUESTION # 15
You manage an application that is writing logs to Stackdriver Logging. You need to give some team members the ability to export logs. What should you do?

  • A. Configure Access Context Manager to allow only these members to export logs.
  • B. Grant the team members the IAM role of logging.configWriter on Cloud IAM.
  • C. Create an Organizational Policy in Cloud IAM to allow only these members to create log exports.
  • D. Create and grant a custom IAM role with the permissions logging.sinks.list and logging.sink.get.

Answer: B

Explanation:
Explanation
https://cloud.google.com/logging/docs/access-control
The logging.configWriter role grants permissions to create, update, and delete log exports. This is the correct role to give team members who need to export logs2.


NEW QUESTION # 16
You support an e-commerce application that runs on a large Google Kubernetes Engine (GKE) cluster deployed on-premises and on Google Cloud Platform. The application consists of microservices that run in containers. You want to identify containers that are using the most CPU and memory. What should you do?

  • A. Use the Stackdriver Monitoring API to create custom metrics, and then organize your containers using groups.
  • B. Use Stackdriver Logging to export application logs to BigOuery. aggregate logs per container, and then analyze CPU and memory consumption.
  • C. Use Prometheus to collect and aggregate logs per container, and then analyze the results in Grafana.
  • D. Use Stackdriver Kubernetes Engine Monitoring.

Answer: C


NEW QUESTION # 17
You are ready to deploy a new feature of a web-based application to production. You want to use Google Kubernetes Engine (GKE) to perform a phased rollout to half of the web server pods.
What should you do?

  • A. Use a partitioned rolling update.
  • B. Use Node taints with NoExecute.
  • C. Use a replica set in the deployment specification.
  • D. Use a stateful set with parallel pod management policy.

Answer: A

Explanation:
https://medium.com/velotio-perspectives/exploring-upgrade-strategies-for-stateful-sets-in-kubernetes-c02b8286f251


NEW QUESTION # 18
You use Terraform to manage an application deployed to a Google Cloud environment The application runs on instances deployed by a managed instance group The Terraform code is deployed by using aCI/CD pipeline When you change the machine type on the instance template used by the managed instance group, the pipeline fails at the terraform apply stage with the following error message

You need to update the instance template and minimize disruption to the application and the number of pipeline runs What should you do?

  • A. Add a new instance template update the managed instance group to use the new instance template and delete the old instance template
  • B. Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template
  • C. Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.
  • D. Delete the managed instance group and recreate it after updating the instance template

Answer: B

Explanation:
The best option for updating the instance template and minimizing disruption to the application and the number of pipeline runs is to set the create_before_destroy meta-argument to true in the lifecycle block on the instance template. The create_before_destroy meta-argument is a Terraform feature that specifies that a new resource should be created before destroying an existing one during an update. This way, you can avoid downtime and errors when updating a resource that is in use by another resource, such as an instance template that is used by a managed instance group. By setting the create_before_destroy meta-argument to true in the lifecycle block on the instance template, you can ensure that Terraform creates a new instance template with the updated machine type, updates the managed instance group to use the new instance template, and then deletes the old instance template.


NEW QUESTION # 19
You support a trading application written in Python and hosted on App Engine flexible environment. You want to customize the error information being sent to Stackdriver Error Reporting. What should you do?

  • A. Install the Stackdriver Error Reporting library for Python, and then run your code on App Engine flexible environment.
  • B. Use the Stackdriver Error Reporting API to write errors from your application to ReportedErrorEvent, and then generate log entries with properly formatted error messages in Stackdriver Logging.
  • C. Install the Stackdriver Error Reporting library for Python, and then run your code on a Compute Engine VM.
  • D. Install the Stackdriver Error Reporting library for Python, and then run your code on Google Kubernetes Engine.

Answer: B


NEW QUESTION # 20
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