2025 100% PASS-RATE LATEST PROFESSIONAL-CLOUD-DEVOPS-ENGINEER MOCK TEST HELP YOU PASS PROFESSIONAL-CLOUD-DEVOPS-ENGINEER EASILY

2025 100% Pass-Rate Latest Professional-Cloud-DevOps-Engineer Mock Test Help You Pass Professional-Cloud-DevOps-Engineer Easily

2025 100% Pass-Rate Latest Professional-Cloud-DevOps-Engineer Mock Test Help You Pass Professional-Cloud-DevOps-Engineer Easily

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Earning the Google Professional-Cloud-DevOps-Engineer certification demonstrates to employers and clients that a professional has the skills and knowledge to design, implement, and manage DevOps practices and processes on the Google Cloud Platform. It can lead to career advancement opportunities and higher salaries. Additionally, it can help organizations that use Google Cloud Platform to identify and hire qualified professionals to manage their DevOps practices.

Google Professional-Cloud-DevOps-Engineer Certification is a highly esteemed certification program for professionals seeking to validate their expertise in cloud-based DevOps engineering. It is designed to test the knowledge and skills required to deploy, manage, and monitor secure, scalable, and highly available cloud-based infrastructure and applications.

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q91-Q96):

NEW QUESTION # 91
You are deploying an application that needs to access sensitive information. You need to ensure that this information is encrypted and the risk of exposure is minimal if a breach occurs. What should you do?

  • A. Inject the secret at the time of instance creation via an encrypted configuration management system.
  • B. Integrate the application with a Single sign-on (SSO) system and do not expose secrets to the application
  • C. Leverage a continuous build pipeline that produces multiple versions of the secret for each instance of the application.
  • D. Store the encryption keys in Cloud Key Management Service (KMS) and rotate the keys frequently

Answer: D

Explanation:
https://cloud.google.com/security-key-management


NEW QUESTION # 92
Your organization has a containerized web application that runs on-premises As part of the migration plan to Google Cloud you need to select a deployment strategy and platform that meets the following acceptance criteria
1 The platform must be able to direct traffic from Android devices to an Android-specific microservice
2 The platform must allow for arbitrary percentage-based traffic splitting
3 The deployment strategy must allow for continuous testing of multiple versions of any microservice What should you do?

  • A. Deploy the canary release of the application to App Engine Use traffic splitting to direct a subset of user traffic to the new version based on the IP address
  • B. Deploy the canary release to Google Kubernetes Engine with Anthos Sen/ice Mesh Use traffic splitting to direct 10% of user traffic to the new version based on the user-agent header configured in the virtual service
  • C. Deploy the canary release of the application to Cloud Run Use traffic splitting to direct 10% of user traffic to the canary release based on the revision tag
  • D. Deploy the canary release of the application to Compute Engine Use Anthos Service Mesh with Compute Engine to direct 10% of user traffic to the canary release by configuring the virtual service.

Answer: B

Explanation:
The best option for deploying a containerized web application to Google Cloud with the given acceptance criteria is to use Google Kubernetes Engine (GKE) with Anthos Service Mesh. GKE is a managed service for running Kubernetes clusters on Google Cloud, and Anthos Service Mesh is a service mesh that provides observability, traffic management, and security features for microservices. With Anthos Service Mesh, you can use traffic splitting to direct traffic from Android devices to an Android-specific microservice by configuring the user-agent header in the virtual service. You can also use traffic splitting to direct arbitrary percentage-based traffic to different versions of any microservice for continuous testing. For example, you can use a canary release strategy to direct 10% of user traffic to a new version of a microservice and monitor its performance and reliability.


NEW QUESTION # 93
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (Pll) is leaking into certain log entry fields. All Pll entries begin with the text userinfo. You want to capture these log entries in a secure location for later review and prevent them from leaking to Stackdriver Logging. What should you do?

  • A. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, and then copy the entries to a Cloud Storage bucket.
  • B. Create a basic log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
  • C. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, create an advanced log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
  • D. Create an advanced log filter matching userinfo, configure a log export in the Stackdriver console with Cloud Storage as a sink, and then configure a tog exclusion with userinfo as a filter.

Answer: B


NEW QUESTION # 94
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 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.
  • B. 1. Export VM utilization logs from Stackdriver to BigQuery.
    2. Create a dashboard in Data Studio.
    3. Share the dashboard with your stakeholders.
  • C. 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.
  • D. 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.

Answer: B


NEW QUESTION # 95
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. Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template
  • B. Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.
  • C. Add a new instance template update the managed instance group to use the new instance template and delete the old instance template
  • D. Delete the managed instance group and recreate it after updating the instance template

Answer: A

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 # 96
......

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