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How to book Google Professional Cloud DevOps Engineer Exams

The registration for the Google Professional Cloud DevOps Engineer exam follows the steps given below.

Step 1: Visit the Google Cloud Webassessor Website
Step 2: Sign-in or sign up to your Google Cloud Webassessor account
Step 3: Search for the exam name Google Professional Cloud DevOps Engineer
Step 4: Take the date of the exam, choose the exam center, and make further payment using payment methods like credit/debit, etc.

After registering for the exam, prepare from the Professional Cloud DevOps Engineer exam dumps and make sure to take Professional Cloud DevOps Engineer practice exam so you know the exam format in advance. This will give you an advantage over other candidates.

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q78-Q83):

NEW QUESTION # 78
You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub. You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?

A. Disable the CI pipeline and revert to manually building and pushing the artifacts.
B. Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.
C. Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.
D. Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.

Answer: A

NEW QUESTION # 79
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 a CI/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. Delete the managed instance group and recreate it after updating the instance template
C. Add a new instance template update the managed instance group to use the new instance template and delete the old instance template
D. Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.

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 # 80
You are creating a CI/CD pipeline to perform Terraform deployments of Google Cloud resources Your CI/CD tooling is running in Google Kubernetes Engine (GKE) and uses an ephemeral Pod for each pipeline run You must ensure that the pipelines that run in the Pods have the appropriate Identity and Access Management (1AM) permissions to perform the Terraform deployments You want to follow Google-recommended practices for identity management What should you do?
Choose 2 answers

A. Create a new JSON service account key for the Google service account store the key as a Kubernetes secret, inject the key into the Pods, and set the boogle_application_credentials environment variable
B. Create a new JSON service account key for the Google service account store the key in the secret management store for the CI/CD tool and configure Terraform to use this key for authentication
C. Create a new Google service account, and assign the appropriate 1AM permissions
D. Assign the appropriate 1AM permissions to the Google service account associated with the Compute Engine VM instances that run the Pods
E. Create a new Kubernetes service account, and assign the service account to the Pods Use Workload Identity to authenticate as the Google service account

Answer: C,E

Explanation:
The best options for ensuring that the pipelines that run in the Pods have the appropriate IAM permissions to perform the Terraform deployments are to create a new Kubernetes service account and assign the service account to the Pods, and to use Workload Identity to authenticate as the Google service account. A Kubernetes service account is an identity that represents an application or a process running in a Pod. A Google service account is an identity that represents a Google Cloud resource or service. Workload Identity is a feature that allows you to bind Kubernetes service accounts to Google service accounts. By using Workload Identity, you can avoid creating and managing JSON service account keys, which are less secure and require more maintenance. You can also assign the appropriate IAM permissions to the Google service account that corresponds to the Kubernetes service account.

NEW QUESTION # 81
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. Add a virtual queue to the online store that allows typical traffic levels
B. Increase the number of Pod replicas
C. Increase the Pod CPU and memory limits
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 # 82
You are reviewing your deployment pipeline in Google Cloud Deploy You must reduce toil in the pipeline and you want to minimize the amount of time it takes to complete an end-to-end deployment What should you do?
Choose 2 answers

A. Add more engineers to finish the manual steps.
B. Create a trigger to notify the required team to complete the next step when manual intervention is required
C. Use a script to automate the creation of the deployment pipeline in Google Cloud Deploy
D. Automate promotion approvals from the development environment to the test environment
E. Divide the automation steps into smaller tasks

Answer: B,D

Explanation:
Explanation
The best options for reducing toil in the pipeline and minimizing the amount of time it takes to complete an end-to-end deployment are to create a trigger to notify the required team to complete the next step when manual intervention is required and to automate promotion approvals from the development environment to the test environment. A trigger is a resource that initiates a deployment when an event occurs, such as a code change, a schedule, or a manual request. You can create a trigger to notify the required team to complete the next step when manual intervention is required by using Cloud Build or Cloud Functions. This way, you can reduce the waiting time and human errors in the pipeline. A promotion approval is a process that allows you to approve or reject a deployment from one environment to another, such as from development to test. You can automate promotion approvals from the development environment to the test environment by using Google Cloud Deploy or Cloud Build. This way, you can speed up the deployment process and avoid manual steps.

NEW QUESTION # 83
......

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