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Google Professional-Cloud-DevOps-Engineer exam is designed to assess an individual's knowledge and skills in the field of cloud-based DevOps engineering. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is intended for professionals who are interested in developing and deploying software applications in the cloud environment. Professional-Cloud-DevOps-Engineer exam is part of the Google Cloud Certified program, which is designed to validate the knowledge and expertise of professionals in various areas of cloud computing.

Google Professional-Cloud-DevOps-Engineer Certification Exam is a highly sought-after certification that is designed for IT professionals who want to demonstrate their skills in managing and deploying applications on Google Cloud Platform (GCP). Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification validates the skills and knowledge of individuals in various areas of cloud computing, including DevOps practices, infrastructure automation, continuous delivery, and monitoring and logging.

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Professional-Cloud-DevOps-Engineer Valid Exam Topics & Latest Professional-Cloud-DevOps-Engineer Exam Pass4sure

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Test Structure

The candidates who want to take this Google exam will have two hours to answer all questions. Even though the vendor doesn’t give details on the total number of questions that the examinees will receive, they should be prepared to solve multiple-choice and multiple-answer inquiries. Besides, the test is delivered in the English language only. As for the registration fee, the test-takers will need to pay $200 to take it. Additional taxes may apply depending on the candidate’s profile and chosen delivery method. By and large, the applicants have two options to take the official exam. They can choose to take it online from any remote location that they prefer. If they choose this option, the candidates should read carefully what the testing requirements are. In case applicants prefer to be present in a classroom when they take the actual testing, then they can search for a test center that is closest to their location. Also, Google doesn’t have any prerequisites for the candidates to be eligible for the evaluation. Still, it recommends that the candidates for the Professional Cloud DevOps Engineer exam should have at least 3 years of experience in the industry including a minimum of one year of experience in managing and developing solutions on GCP.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q20-Q25):

NEW QUESTION # 20
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring. What should you do?

A. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
B. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
C. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.
D. Publish various metrics from the application directly to the Slackdriver Monitoring API, and then observe these custom metrics in Stackdriver.

Answer: D

Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics#custom_metrics
https://github.com/GoogleCloudPlatform/k8s-stackdriver/blob/master/custom-metrics-stackdriver-adapter/README.md Your application can report a custom metric to Cloud Monitoring. You can configure Kubernetes to respond to these metrics and scale your workload automatically. For example, you can scale your application based on metrics such as queries per second, writes per second, network performance, latency when communicating with a different application, or other metrics that make sense for your workload. https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics

NEW QUESTION # 21
You support a high-traffic web application and want to ensure that the home page loads in a timely manner. As a first step, you decide to implement a Service Level Indicator (SLI) to represent home page request latency with an acceptable page load time set to 100 ms. What is the Google-recommended way of calculating this SLI?

A. Count the number of home page requests that load in under 100 ms. and then divide by the total number of all web application requests.
B. Bucketize the request latencies into ranges, and then compute the median and 90th percentiles.
C. Count the number of home page requests that load in under 100 ms, and then divide by the total number of home page requests.
D. Buckelize Ihe request latencies into ranges, and then compute the percentile at 100 ms.

Answer: C

Explanation:
https://sre.google/workbook/implementing-slos/
In the SRE principles book, it's recommended treating the SLI as the ratio of two numbers: the number of good events divided by the total number of events. For example: Number of successful HTTP requests / total HTTP requests (success rate)

NEW QUESTION # 22
Your team of Infrastructure DevOps Engineers is growing, and you are starting to use Terraform to manage infrastructure. You need a way to implement code versioning and to share code with other team members. What should you do?

A. Store the Terraform code in a shared Google Drive folder so it syncs automatically to every team member's computer. Organize files with a naming convention that identifies each new version.
B. Store the Terraform code in a Cloud Storage bucket using object versioning. Give access to the bucket to every team member so they can download the files.
C. Store the Terraform code in a network shared folder with child folders for each version release. Ensure that everyone works on different files.
D. Store the Terraform code in a version-control system. Establish procedures for pushing new versions and merging with the master.

Answer: D

Explanation:
https://www.terraform.io/docs/cloud/guides/recommended-practices/part3.3.html

NEW QUESTION # 23
You are the on-call Site Reliability Engineer for a microservice that is deployed to a Google Kubernetes Engine (GKE) Autopilot cluster. Your company runs an online store that publishes order messages to Pub/Sub and a microservice receives these messages and updates stock information in the warehousing system. A sales event caused an increase in orders, and the stock information is not being updated quickly enough. This is causing a large number of orders to be accepted for products that are out of stock You check the metrics for the microservice and compare them to typical levels.

You need to ensure that the warehouse system accurately reflects product inventory at the time orders are placed and minimize the impact on customers What should you do?

A. Increase the Pod CPU and memory limits
B. Increase the number of Pod replicas
C. Add a virtual queue to the online store that allows typical traffic levels
D. Decrease the acknowledgment deadline on the subscription

Answer: B

Explanation:
Explanation
The best option for ensuring that the warehouse system accurately reflects product inventory at the time orders are placed and minimizing the impact on customers is to increase the number of Pod replicas. Increasing the number of Pod replicas will increase the scalability and availability of your microservice, which will allow it to handle more Pub/Sub messages and update stock information faster. This way, you can reduce the backlog of undelivered messages and oldest unacknowledged message age, which are causing delays in updating product inventory. You can use Horizontal Pod Autoscaler or Cloud Monitoring metrics-based autoscaling to automatically adjust the number of Pod replicas based on load or custom metrics.

NEW QUESTION # 24
You are configuring connectivity across Google Kubernetes Engine (GKE) clusters in different VPCs You notice that the nodes in Cluster A are unable to access the nodes in Cluster B You suspect that the workload access issue is due to the network configuration You need to troubleshoot the issue but do not have execute access to workloads and nodes You want to identify the layer at which the network connectivity is broken What should you do?

A. Use a debug container to run the traceroute command from Cluster A to Cluster B and from Cluster B to Cluster A Identify the common failure point
B. Enable VPC Flow Logs in both VPCs and monitor packet drops
C. Use Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster
D. Install a toolbox container on the node in Cluster A Confirm that the routes to Cluster B are configured appropriately

Answer: A

Explanation:
The best option for troubleshooting the issue without having execute access to workloads and nodes is to use Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster B. Network Connectivity Center is a service that allows you to create, manage, and monitor network connectivity across Google Cloud, hybrid, and multi-cloud environments. You can use Network Connectivity Center to perform a Connectivity Test, which is a feature that allows you to test the reachability and latency between two endpoints, such as GKE clusters, VM instances, or IP addresses. By using Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster B, you can identify the layer at which the network connectivity is broken, such as the firewall, routing, or load balancing.

NEW QUESTION # 25
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Test Google Professional-Cloud-DevOps-Engineer Questions - Professional-Cloud-DevOps-Engineer Valid Exam Topics

Professional-Cloud-DevOps-Engineer Valid Exam Topics & Latest Professional-Cloud-DevOps-Engineer Exam Pass4sure

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q20-Q25):

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