Your application requires service accounts to be authenticated to GCP products via credentials stored on its host Compute Engine virtual machine instances. You want to distribute these credentials to the host instances as securely as possible. What should you do?

• A.Use HTTP signed URLs to securely provide access to the required resources.
• B.Use the instance's service account Application Default Credentials to authenticate to the required resources.
• C.Generate a P12 file from the GCP Console after the instance is deployed, and copy the credentials to the host instance before starting the application.
• D.Commit the credential JSON file into your application's source repository, and have your CI/CD process package it with the software that is deployed to the instance.

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You need to load-test a set of REST API endpoints that are deployed to Cloud Run. The API responds to HTTP POST requests. Your load tests must meet the following requirements:
- Load is initiated from multiple parallel threads.
- User traffic to the API originates from multiple source IP addresses.
- Load can be scaled up using additional test instances.
You want to follow Google-recommended best practices. How should you configure the load testing?

• A.Deploy a distributed load testing framework on a private Google Kubernetes Engine cluster.
  Deploy additional Pods as needed to initiate more traffic and support the number of concurrent users.
• B.Download the container image of a distributed load testing framework on Cloud Shell.Sequentially start several instances of the container on Cloud Shell to increase the load on the API.
• C.Create an image that has cURL installed, and configure cURL to run a test plan. Deploy the image in a managed instance group, and run one instance of the image for each VM.
• D.Create an image that has cURL installed, and configure cURL to run a test plan. Deploy the image in an unmanaged instance group, and run one instance of the image for each VM.

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You are about to deploy an application hosted on a Compute Engine instance with Windows OS and Cloud SQL. You plan to use the Cloud SQL Auth Proxy for connectivity to the Cloud SQL instance. You plan to follow Google-recommended practices and the principle of least privilege.
You have already created a custom service account. What should you do next?

• A.Create and assign a custom role with the cloudsql.instances.connect permission to the custom service account. Adjust the Cloud SQL Auth Proxy start command to specify your instance connection name.
• B.Grant the custom service account the roles/cloudsql.client role. Adjust the Cloud SQL Auth Proxy start command to use the --unix-socket CLI option.
• C.Grant the custom service account the roles/cloudsql.editor role.
• D.Grant the custom service account the roles/cloudsql.viewer role. Adjust the Cloud SQL Auth Proxy start command to specify your instance connection name.

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Your teammate has asked you to review the code below, which is adding a credit to an account balance in Cloud Datastore. Which improvement should you suggest your teammate make?

• A.Don't return the account entity from the function.
• B.Use a strongly consistent transactional database.
• C.Get the entity with an ancestor query.
• D.Get and put the entity in a transaction.

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You are defining your system tests for an application running in Cloud Run in a Google Cloud project. You need to create a testing environment that is isolated from the production environment. You want to fully automate the creation of the testing environment with the least amount of effort and execute automated tests. What should you do?

• A.Using Cloud Build, execute Terraform scripts to create a new Google Cloud project and a Cloud Run instance of your application in the Google Cloud project.
• B.Using Cloud Build, execute a Terraform script to deploy a new Cloud Run revision in the existing Google Cloud project. Use traffic splitting to send traffic to your test environment.
• C.Using Cloud Build, execute gcloud commands to create a new Google Cloud project and a Cloud Run instance of your application in the Google Cloud project.
• D.Using Cloud Build, execute gcloud commands to deploy a new Cloud Run revision in the existing Google Cloud project. Use traffic splitting to send traffic to your test environment.

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