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Google Professional-Cloud-DevOps-Engineer Exam Questions Are Out: Download And Prepare [2025]
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Google Professional-Cloud-DevOps-Engineer Certification Exam is designed to test a candidate's knowledge and skills in cloud-based DevOps engineering. Professional-Cloud-DevOps-Engineer exam is intended for professionals who are responsible for designing, creating, and managing DevOps processes and tools in a cloud-based environment. This Google Cloud Certified Professional Cloud DevOps Engineer certification is the ideal way for professionals to demonstrate their expertise in the field and to enhance their career prospects.
Upon passing the exam, candidates will receive the Google Cloud Certified - Professional Cloud DevOps Engineer certification, which demonstrates their expertise in cloud-based DevOps engineering. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification can help individuals advance their careers in the IT industry and open up new opportunities for growth and development.
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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q178-Q183):
NEW QUESTION # 178
You are configuring your CI/CD pipeline natively on Google Cloud. You want builds in a pre-production Google Kubernetes Engine (GKE) environment to be automatically load-tested before being promoted to the production GKE environment. You need to ensure that only builds that have passed this test are deployed to production. You want to follow Google-recommended practices. How should you configure this pipeline with Binary Authorization?
Answer: D
NEW QUESTION # 179
Your company has a Google Cloud resource hierarchy with folders for production test and development Your cyber security team needs to review your company's Google Cloud security posture to accelerate security issue identification and resolution You need to centralize the logs generated by Google Cloud services from all projects only inside your production folder to allow for alerting and near-real time analysis. What should you do?
Answer: D
Explanation:
Explanation
The best option for centralizing the logs generated by Google Cloud services from all projects only inside your production folder is to create an aggregated log sink associated with the production folder that uses a Cloud Logging bucket as the destination. An aggregated log sink is a log sink that collects logs from multiple sources, such as projects, folders, or organizations. A Cloud Logging bucket is a storage location for logs that can be used as a destination for log sinks. By creating an aggregated log sink with a Cloud Logging bucket, you can collect and store all the logs from the production folder in one place and allow for alerting and near-real time analysis using Cloud Monitoring and Cloud Operations.
NEW QUESTION # 180
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?
Answer: C
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 # 181
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?
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 # 182
You have migrated an e-commerce application to Google Cloud Platform (GCP). You want to prepare the application for the upcoming busy season. What should you do first to prepare for the busy season?
Answer: D
NEW QUESTION # 183
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