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Your organization uses a change advisory board (CAB) to approve all changes to an existing service. You want to revise this process to eliminate any negative impact on the software delivery performance. What should you do? (Choose two.)

A. Replace the CAB with a senior manager to ensure continuous oversight from development to deployment.

B. Let developers merge their own changes, but ensure that the team's deployment platform can roll back changes if any issues are discovered.

C. Move to a peer-review based process for individual changes that is enforced at code check-in time and supported by automated tests.

D. Batch changes into larger but less frequent software releases.

E. Ensure that the team's development platform enables developers to get fast feedback on the impact of their changes.

You work for a global organization and run a service with an availability target of 99% with limited engineering resources.

For the current calendar month, you noticed that the service has 99.5% availability. You must ensure that your service meets the defined availability goals and can react to business changes, including the upcoming launch of new features.

You also need to reduce technical debt while minimizing operational costs. You want to follow Google-recommended practices. What should you do?

A. Add N+1 redundancy to your service by adding additional compute resources to the service.

B. Identify, measure, and eliminate toil by automating repetitive tasks.

C. Define an error budget for your service level availability and minimize the remaining error budget.

D. Allocate available engineers to the feature backlog while you ensure that the service remains within the availability target.

Your team is building a service that performs compute-heavy processing on batches of data. The data is processed faster based on the speed and number of CPUs on the machine. These batches of data vary in size and may arrive at any time from multiple third-party sources. You need to ensure that third parties are able to upload their data securely. You want to minimize costs, while ensuring that the data is processed as quickly as possible. What should you do?

A. Provide a secure file transfer protocol (SFTP) server on a Compute Engine instance so that third parties can upload batches of data, and provide appropriate credentials to the server. Create a Cloud Function with a google.storage.object.finalize Cloud Storage trigger. Write code so that the function can scale up a Compute Engine autoscaling managed instance group Use an image pre-loaded with the data processing software that terminates the instances when processing completes.

B. Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (IAM) access to the bucket. Use a standard Google Kubernetes Engine (GKE) cluster and maintain two services: one that processes the batches of data, and one that monitors Cloud Storage for new batches of data. Stop the processing service when there are no batches of data to process.

C. Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (IAM) access to the bucket. Create a Cloud Function with a google.storage.object.finalize Cloud Storage trigger. Write code so that the function can scale up a Compute Engine autoscaling managed instance group. Use an image pre-loaded with the data processing software that terminates the instances when processing completes.

D. Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (IAM) access to the bucket. Use Cloud Monitoring to detect new batches of data in the bucket and trigger a Cloud Function that processes the data. Set a Cloud Function to use the largest CPU possible to minimize the runtime of the processing.

You are investigating issues in your production application that runs on Google Kubernetes Engine (GKE). You determined that the source of the issue is a recently updated container image, although the exact change in code was not identified. The deployment is currently pointing to the latest tag. You need to update your cluster to run a version of the container that functions as intended. What should you do?

A. Create a new tag called stable that points to the previously working container, and change the deployment to point to the new tag.

B. Alter the deployment to point to the sha256 digest of the previously working container.

C. Build a new container from a previous Git tag, and do a rolling update on the deployment to the new container.

D. Apply the latest tag to the previous container image, and do a rolling update on the deployment.

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. Delete the managed instance group, and recreate it after updating the instance template.

B. Add a new instance template, update the managed instance group to use the new instance template, and delete the old instance template.

C. Remove the managed instance group from the Terraform state file, update the instance template, and reimport the managed instance group.

D. Set the create_before_destroy meta-argument to true in the lifecycle block on the instance template.