For this question, refer to the Dress4Win case study.
Dress4Win would like to become familiar with deploying applications to the cloud by successfully deploying some applications quickly, as is. They have asked for your recommendation. What should you advise?

• A.Identify self-contained applications with external dependencies as a first move to the cloud.
• B.Identify enterprise applications with internal dependencies and recommend these as a first move to the cloud.
• C.Suggest moving their in-house databases to the cloud and continue serving requests to on-premise applications.
• D.Recommend moving their message queuing servers to the cloud and continue handling requests to on-premise applications.

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Your team will start developing a new application using microservices architecture on Kubernetes Engine. As part of the development lifecycle, any code change that has been pushed to the remote develop branch on your GitHub repository should be built and tested automatically. When the build and test are successful, the relevant microservice will be deployed automatically in the development environment. You want to ensure that all code deployed in the development environment follows this process. What should you do?

• A.Have each developer install a pre-commit hook on their workstation that tests the code and builds the container when committing on the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.
• B.Create a Cloud Build trigger based on the development branch that tests the code, builds the container, and stores it in Container Registry. Create a deployment pipeline that watches for new images and deploys the new image on the development cluster. Ensure only the deployment tool has access to deploy new versions.
• C.Create a Cloud Build trigger based on the development branch to build a new container image and store it in Container Registry. Rely on Vulnerability Scanning to ensure the code tests succeed. As the final step of the Cloud Build process, deploy the new container image on the development cluster. Ensure only Cloud Build has access to deploy new versions.
• D.Install a post-commit hook on the remote git repository that tests the code and builds the container when code is pushed to the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.

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A production database virtual machine on Google Compute Engine has an ext4-formatted persistent disk for data files The database is about to run out of storage space How can you remediate the problem with the least amount of downtime?

• A.In the Cloud Platform Console, increase the size of the persistent disk and use the resize2fs command in Linux.
• B.Shut down the virtual machine, use the Cloud Platform Console to increase the persistent disk size, then restart the virtual machine.
• C.In the Cloud Platform Console, increase the size of the persistent disk and verify the new space is ready to use with the fdisk command in Linux.
• D.In the Cloud Platform Console, create a new persistent disk attached to the virtual machine, format and mount it, and configure the database service to move the files to the new disk.
• E.In the Cloud Platform Console, create a snapshot of the persistent disk, restore the snapshot to a new larger disk, unmount the old disk, mount the new disk, and restart the database service.

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You are managing an application deployed on Cloud Run for Anthos, and you need to define a strategy for deploying new versions of the application. You want to evaluate the new code with a subset of production traffic to decide whether to proceed with the rollout. What should you do?

• A.Deploy a new service to Cloud Run with the new version. Add a Cloud Load Balancing instance in front of both services.
• B.Deploy a new revision to Cloud Run with the new version. Configure traffic percentage between revisions.
• C.In the Google Cloud Console, configure Traffic Director with a new Service that points to the new version of the application on Cloud Run. Configure Traffic Director to send a small percentage of traffic to the new version of the application.
• D.In the Google Cloud Console page for Cloud Run, set up continuous deployment using Cloud Build for the development branch. As part of the Cloud Build trigger, configure the substitution variable TRAFFIC_PERCENTAGE with the percentage of traffic you want directed to a new version.

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For this question, refer to the Helicopter Racing League (HRL) case study. Your team is in charge of creating a payment card data vault for card numbers used to bill tens of thousands of viewers, merchandise consumers, and season ticket holders. You need to implement a custom card tokenization service that meets the following requirements:
* It must provide low latency at minimal cost.
* It must be able to identify duplicate credit cards and must not store plaintext card numbers.
* It should support annual key rotation.
Which storage approach should you adopt for your tokenization service?

• A.Store the card data in Secret Manager after running a query to identify duplicates.
• B.Encrypt the card data with a deterministic algorithm stored in Firestore using Datastore mode.
• C.Encrypt the card data with a deterministic algorithm and shard it across multiple Memorystore instances.
• D.Use column-level encryption to store the data in Cloud SQL.

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