PROFESSIONAL-CLOUD-DEVOPS-ENGINEER LATEST TEST QUESTION & LATEST PROFESSIONAL-CLOUD-DEVOPS-ENGINEER EXAM VCE

Professional-Cloud-DevOps-Engineer Latest Test Question & Latest Professional-Cloud-DevOps-Engineer Exam Vce

Professional-Cloud-DevOps-Engineer Latest Test Question & Latest Professional-Cloud-DevOps-Engineer Exam Vce

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Preparation Process

The best way to prepare for the Google Professional Cloud DevOps Engineer certification exam is to explore the training tools offered on its official website. The candidates can start their preparation process by reviewing the topics in the study guide. This will give them an idea of what they need to cover studying for the test and plan their learning time properly.

The official platform recommends that the potential individuals complete the Professional DevOps Engineer learning path, which includes in-person classes, online training, and hands-on labs for a better understating of the exam content. The courses within this path cover each aspect of the certification test in depth improving the candidates’ chances of passing the exam at the first attempt. Apart from the learning path, the applicants can take advantage of additional resources such as Google Cloud documentation and Google Cloud solutions. There is also the option of signing up for a dedicated webinar to learn valuable prep tips from the Google experts. At the end of your preparation, use the official sample questions to familiarize yourself with the format of exam questions and check the level of readiness.

Google Professional-Cloud-DevOps-Engineer Certification is highly valued in the industry as it validates the skills and knowledge of professionals who are working in the field of cloud DevOps engineering. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification program is designed to help professionals enhance their career prospects and demonstrate their expertise in cloud computing and DevOps principles.

>> Professional-Cloud-DevOps-Engineer Latest Test Question <<

Quiz 2025 Marvelous Google Professional-Cloud-DevOps-Engineer Latest Test Question

Candidates who participate in the Google practice exam should first choose our latest braindumps pdf. It will help you pass test with 100% guaranteed. Besides, our Professional-Cloud-DevOps-Engineer exam prep can help you fit the atmosphere of actual test in advance, which enable you to improve your ability with minimum time spent on Professional-Cloud-DevOps-Engineer Dumps PDF and maximum knowledge gained.

Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer) Certification Exam is a professional-level exam designed to validate the skills and knowledge of individuals in the field of cloud DevOps engineering. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam is intended for individuals who have experience in cloud computing, software development, and DevOps practices. Professional-Cloud-DevOps-Engineer Exam assesses the candidate's ability to design, develop, and implement cloud solutions using Google Cloud Platform (GCP) services and tools.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q38-Q43):

NEW QUESTION # 38
You are creating Cloud Logging sinks to export log entries from Cloud Logging to BigQuery for future analysis Your organization has a Google Cloud folder named Dev that contains development projects and a folder named Prod that contains production projects Log entries for development projects must be exported to dev_dataset. and log entries for production projects must be exported to prod_dataset You need to minimize the number of log sinks created and you want to ensure that the log sinks apply to future projects What should you do?

  • A. Create a single aggregated log sink at the organization level.
  • B. Create a log sink in each project
  • C. Create two aggregated log sinks at the organization level, and filter by project ID
  • D. Create an aggregated Iog sink in the Dev and Prod folders

Answer: D

Explanation:
Explanation
The best option for minimizing the number of log sinks created and ensuring that the log sinks apply to future projects is to create an aggregated log sink in the Dev and Prod folders. An aggregated log sink is a log sink that collects logs from multiple sources, such as projects, folders, or organizations. By creating an aggregated log sink in each folder, you can export log entries for development projects to dev_dataset and log entries for production projects to prod_dataset. You can also use filters to specify which logs you want to export.
Additionally, by creating an aggregated log sink at the folder level, you can ensure that the log sink applies to future projects that are created under that folder.


NEW QUESTION # 39
You support a Node.js application running on Google Kubernetes Engine (GKE) in production. The application makes several HTTP requests to dependent applications. You want to anticipate which dependent applications might cause performance issues. What should you do?

  • A. Use Stackdriver Debugger to review the execution of logic within each application to instrument all applications.
  • B. Instrument all applications with Stackdriver Profiler.
  • C. Instrument all applications with Stackdriver Trace and review inter-service HTTP requests.
  • D. Modify the Node.js application to log HTTP request and response times to dependent applications. Use Stackdriver Logging to find dependent applications that are performing poorly.

Answer: C


NEW QUESTION # 40
You are analyzing Java applications in production. All applications have Cloud Profiler and Cloud Trace installed and configured by default. You want to determine which applications need performance tuning.
What should you do?
Choose 2 answers

  • A. 17 Examine the wall-clock time and the CPU time of the application. If the difference is substantial, increase the local disk storage allocation.
  • B. Examine the wall-clock time and the CPU time of the application. If the difference is substantial, increase the memory resource allocation.
  • C. Examine the wall-clock time and the CPU time Of the application. If the difference is substantial, increase the CPU resource allocation.
  • D. O Examine the latency time, the wall-clock time, and the CPU time of the application. If the latency time is slowly burning down the error budget, and the difference between wall-clock time and CPU time is minimal, mark the application for optimization.
  • E. Examine the heap usage Of the application. If the usage is low, mark the application for optimization.

Answer: C,D

Explanation:
The correct answers are A and D.
Examine the wall-clock time and the CPU time of the application. If the difference is substantial, increase the CPU resource allocation. This is a good way to determine if the application is CPU-bound, meaning that it spends more time waiting for the CPU than performing actual computation.Increasing the CPU resource allocation can improve the performance of CPU-bound applications1.
Examine the latency time, the wall-clock time, and the CPU time of the application. If the latency time is slowly burning down the error budget, and the difference between wall-clock time and CPU time is minimal, mark the application for optimization. This is a good way to determine if the application is I/O-bound, meaning that it spends more time waiting for input/output operations than performing actual computation.
Increasing the CPU resource allocation will not help I/O-bound applications, and they may need optimization to reduce the number or duration of I/O operations2.
Answer B is incorrect because increasing the memory resource allocation will not help if the application is CPU-bound or I/O-bound. Memory allocation affects how much data the application can store and access in memory, but it does not affect how fast the application can process that data.
Answer C is incorrect because increasing the local disk storage allocation will not help if the application is CPU-bound or I/O-bound. Disk storage affects how much data the application can store and access on disk, but it does not affect how fast the application can process that data.
Answer E is incorrect because examining the heap usage of the application will not help to determine if the application needs performance tuning. Heap usage affects how much memory the application allocates for dynamic objects, but it does not affect how fast the application can process those objects. Moreover, low heap usage does not necessarily mean that the application is inefficient or unoptimized.


NEW QUESTION # 41
Your company follows Site Reliability Engineering practices. You are the person in charge of Communications for a large, ongoing incident affecting your customer-facing applications. There is still no estimated time for a resolution of the outage. You are receiving emails from internal stakeholders who want updates on the outage, as well as emails from customers who want to know what is happening. You want to efficiently provide updates to everyone affected by the outage. What should you do?

  • A. Delegate the responding to internal stakeholder emails to another member of the Incident Response Team.
    Focus on providing responses directly to customers.
  • B. Focus on responding to internal stakeholders at least every 30 minutes. Commit to "next update" times.
  • C. Provide periodic updates to all stakeholders in a timely manner. Commit to a "next update" time in all communications.
  • D. Provide all internal stakeholder emails to the Incident Commander, and allow them to manage internal communications. Focus on providing responses directly to customers.

Answer: A


NEW QUESTION # 42
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. Delete the managed instance group and recreate it after updating 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. Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template

Answer: D

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 # 43
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