Pre-Summer Sale 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: save70

Google Professional-Cloud-DevOps-Engineer Exam With Confidence Using Practice Dumps

Exam Code:
Professional-Cloud-DevOps-Engineer
Exam Name:
Google Cloud Certified - Professional Cloud DevOps Engineer Exam
Certification:
Vendor:
Questions:
201
Last Updated:
Apr 11, 2026
Exam Status:
Stable
Google Professional-Cloud-DevOps-Engineer

Professional-Cloud-DevOps-Engineer: Cloud DevOps Engineer Exam 2025 Study Guide Pdf and Test Engine

Are you worried about passing the Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer Exam) exam? Download the most recent Google Professional-Cloud-DevOps-Engineer braindumps with answers that are 100% real. After downloading the Google Professional-Cloud-DevOps-Engineer exam dumps training , you can receive 99 days of free updates, making this website one of the best options to save additional money. In order to help you prepare for the Google Professional-Cloud-DevOps-Engineer exam questions and verified answers by IT certified experts, CertsTopics has put together a complete collection of dumps questions and answers. To help you prepare and pass the Google Professional-Cloud-DevOps-Engineer exam on your first attempt, we have compiled actual exam questions and their answers. 

Our (Google Cloud Certified - Professional Cloud DevOps Engineer Exam) Study Materials are designed to meet the needs of thousands of candidates globally. A free sample of the CompTIA Professional-Cloud-DevOps-Engineer test is available at CertsTopics. Before purchasing it, you can also see the Google Professional-Cloud-DevOps-Engineer practice exam demo.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Questions and Answers

Question 1

You are working with a government agency that requires you to archive application logs for seven years. You need to configure Stackdriver to export and store the logs while minimizing costs of storage. What should you do?

Options:

A.

Create a Cloud Storage bucket and develop your application to send logs directly to the bucket.

B.

Develop an App Engine application that pulls the logs from Stackdriver and saves them in BigQuery.

C.

Create an export in Stackdriver and configure Cloud Pub/Sub to store logs in permanent storage for seven years.

D.

Create a sink in Stackdriver, name it, create a bucket on Cloud Storage for storing archived logs, and then select the bucket as the log export destination.

Buy Now
Question 2

You are performing a semiannual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP). using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?

Options:

A.

Verity the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verity your expected resource needs.

B.

Because you are deployed on GKE and are using a cluster autoscaler. your GKE cluster will scale automatically, regardless of growth rate.

C.

Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.

D.

Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough capacity.

Question 3

You have an application that runs in Google Kubernetes Engine (GKE). The application consists of several microservices that are deployed to GKE by using Deployments and Services One of the microservices is experiencing an issue where a Pod returns 403 errors after the Pod has been running for more than five hours Your development team is working on a solution but the issue will not be resolved for a month You need to ensure continued operations until the microservice is fixed You want to follow Google-recommended practices and use the fewest number of steps What should you do?

Options:

A.

Create a cron job to terminate any Pods that have been running for more than five hours

B.

Add a HTTP liveness probe to the microservice s deployment

C.

Monitor the Pods and terminate any Pods that have been running for more than five hours

D.

Configure an alert to notify you whenever a Pod returns 403 errors