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Google Professional-Cloud-DevOps-Engineer is a certification exam that is designed to validate the skills and knowledge of professionals in cloud-based DevOps engineering. Professional-Cloud-DevOps-Engineer exam is designed for individuals who have experience in managing and deploying applications on Google Cloud Platform (GCP). Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam focuses on assessing the candidate's ability to design, develop, and manage a robust cloud-based DevOps environment using GCP services and tools.

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Earning the Google Professional-Cloud-DevOps-Engineer Certification demonstrates a high level of expertise in implementing DevOps practices on Google Cloud Platform. It is a valuable credential for professionals seeking to advance their careers in cloud computing and DevOps. Additionally, it is a testament to the individual’s commitment to continuous learning and professional development.

Domains Tested in Final Evaluation

The candidates who succeed in passing the Google Professional Cloud DevOps Engineer validation will add an international designation under their belt that helps them consolidate their position in the company and receive generous offers from their employers. So, if applicants want to differentiate themselves from other colleagues, they should demonstrate the following skills:

Implementing and building CI/CD service pipelines;
Identifying issues related to service performance and implementing solutions to optimize it;
Checking and implementing strategies related to service monitoring;
Coordinating teams to identify and manage incidents related to service development.
Identifying the most effective principles related to site reliability engineering and applying them to a definite service;

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q34-Q39):

NEW QUESTION # 34
You have a set of applications running on a Google Kubernetes Engine (GKE) cluster, and you are using Stackdriver Kubernetes Engine Monitoring. You are bringing a new containerized application required by your company into production. This application is written by a third party and cannot be modified or reconfigured. The application writes its log information to /var/log/app_messages.log, and you want to send these log entries to Stackdriver Logging. What should you do?

A. Deploy a Fluentd daemonset to GKE. Then create a customized input and output configuration to tail the log file in the application's pods and write to Slackdriver Logging.
B. Use the default Stackdriver Kubernetes Engine Monitoring agent configuration.
C. Install Kubernetes on Google Compute Engine (GCE> and redeploy your applications. Then customize the built-in Stackdriver Logging configuration to tail the log file in the application's pods and write to Stackdriver Logging.
D. Write a script to tail the log file within the pod and write entries to standard output. Run the script as a sidecar container with the application's pod. Configure a shared volume between the containers to allow the script to have read access to /var/log in the application container.

Answer: D

NEW QUESTION # 35
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_datasetYou 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 an aggregated Iog sink in the Dev and Prod folders
B. Create two aggregated log sinks at the organization level, and filter by project ID
C. Create a log sink in each project
D. Create a single aggregated log sink at the organization level.

Answer: D

NEW QUESTION # 36
You need to deploy a new service to production. The service needs to automatically scale using a Managed Instance Group (MIG) and should be deployed over multiple regions. The service needs a large number of resources for each instance and you need to plan for capacity. What should you do?

A. Validate that the resource requirements are within the available quota limits of each region.
B. Deploy the service in one region and use a global load balancer to route traffic to this region.
C. Monitor results of Stackdriver Trace to determine the required amount of resources.
D. Use the n1-highcpu-96 machine type in the configuration of the MIG.

Answer: A

Explanation:
https://cloud.google.com/compute/quotas#understanding_quotas
https://cloud.google.com/compute/quotas

NEW QUESTION # 37
You are designing a new Google Cloud organization for a client. Your client is concerned with the risks associated with long-lived credentials created in Google Cloud. You need to design a solution to completely eliminate the risks associated with the use of JSON service account keys while minimizing operational overhead. What should you do?

A. Apply the constraints/iam. disableServiceAccountKeyUp10ad constraint to the organization.
B. Grant the roles/ iam.serviceAccountKeyAdmin IAM role to organization administrators only.
C. Apply the constraints/iam.disableserviceAccountKeycreation constraint to the organization.
D. Use custom versions of predefined roles to exclude all iam.serviceAccountKeys. * service account role permissions.

Answer: C

NEW QUESTION # 38
You currently store the virtual machine (VM) utilization logs in Stackdriver. You need to provide an easy-to- share interactive VM utilization dashboard that is updated in real time and contains information aggregated on a quarterly basis. You want to use Google Cloud Platform solutions. What should you do?

A. 1. Export VM utilization logs from Stackdriver to BigQuery.
2. From BigQuery, export the logs to a CSV file.
3. Import the CSV file into Google Sheets.
4. Build a dashboard in Google Sheets and share it with your stakeholders.
B. 1. Export VM utilization logs from Stackdriver to a Cloud Storage bucket.
2. Enable the Cloud Storage API to pull the logs programmatically.
3. Build a custom data visualization application.
4. Display the pulled logs in a custom dashboard.
C. 1. Export VM utilization logs from Stackdriver to Cloud Pub/Sub.
2. From Cloud Pub/Sub, send the logs to a Security Information and Event Management (SIEM) system.
3. Build the dashboards in the SIEM system and share with your stakeholders.
D. 1. Export VM utilization logs from Stackdriver to BigQuery.
2. Create a dashboard in Data Studio.
3. Share the dashboard with your stakeholders.

Answer: D

NEW QUESTION # 39
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