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  1. Home
  2. Google Certification
  3. Professional-Cloud-DevOps-Engineer Exam
  4. Google.Professional-Cloud-DevOps-Engineer.v2025-01-09.q159 Dumps
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Question 86

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?

Correct Answer: D
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.
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Question 87

You support the backend of a mobile phone game that runs on a Google Kubernetes Engine (GKE) cluster. The application is serving HTTP requests from users. You need to implement a solution that will reduce the network cost. What should you do?

Correct Answer: D
Costs associated with a load balancer are charged to the project containing the load balancer components. Because of these benefits, container-native load balancing is the recommended solution for load balancing through Ingress. When NEGs are used with GKE Ingress, the Ingress controller facilitates the creation of all aspects of the L7 load balancer. This includes creating the virtual IP address, forwarding rules, health checks, firewall rules, and more. https://cloud.google.com/architecture/best-practices-for-running-cost-effective-kubernetes-applications-on-gke
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Question 88

You support a Node.js application running on Google Kubernetes Engine (GKE) in production. The application makes several HTTP requests to dependent applications. You want to anticipate which dependent applications might cause performance issues. What should you do?

Correct Answer: B
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Question 89

The new version of your containerized application has been tested and is ready to be deployed to production on Google Kubernetes Engine (GKE) You could not fully load-test the new version in your pre-production environment and you need to ensure that the application does not have performance problems after deployment Your deployment must be automated What should you do?

Correct Answer: A
Explanation
The best option for deploying a new version of your containerized application to production on GKE and ensuring that the application does not have performance problems after deployment is to deploy the application through a continuous delivery pipeline by using canary deployments, use Cloud Monitoring to look for performance issues, and ramp up traffic as supported by the metrics. A canary deployment is a deployment strategy that involves releasing a new version of an application to a subset of users or servers and monitoring its performance and reliability. This way, you can test the new version in the production environment with real traffic and load, and gradually increase the traffic as the metrics indicate. You can use Cloud Monitoring to collect and analyze metrics from your application and GKE cluster, such as latency, error rate, CPU utilization, and memory usage. You can also use Cloud Monitoring to set up alerts and dashboards to track the performance of your application.
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Question 90

Your organization is using Helm to package containerized applications Your applications reference both public and private charts Your security team flagged that using a public Helm repository as a dependency is a risk You want to manage all charts uniformly, with native access control and VPC Service Controls What should you do?

Correct Answer: A
The best option for managing all charts uniformly, with native access control and VPC Service Controls is to store public and private charts in OCI format by using Artifact Registry. Artifact Registry is a service that allows you to store and manage container images and other artifacts in Google Cloud. Artifact Registry supports OCI format, which is an open standard for storing container images and other artifacts such as Helm charts. You can use Artifact Registry to store public and private charts in OCI format and manage them uniformly. You can also use Artifact Registry's native access control features, such as IAM policies and VPC Service Controls, to secure your charts and control who can access them.
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