An application development team has come to you for advice.They are planning to write and deploy an HTTP (S) API using Go 1.12. The API will have a very unpredictable workload and must remain reliable during peaks in traffic. They want to minimize operational overhead for this application. What approach should you recommend?

• A. Develop the application for App Engine Flexible environment using a custom runtime
• B. Develop the application for App Engine standard environment
• C. Use a Managed Instance Group when deploying to Compute Engine
• D. Develop an application with containers, and deploy to Google Kubernetes Engine (GKE)

For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?

• A. Replace the existing data warehouse with BigQuery. Use table partitioning.
• B. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.
• C. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.
• D. Replace the existing data warehouse with BigQuery. Use federated data sources.

You are a cloud architect for a financial services organization that is migrating its environment to Google Cloud. A new developer on your team needs to quickly inspect the metadata of a Compute Engine instance to troubleshoot a configuration issue, but they do not have the Google Cloud SDK installed on their local workstation. You need to provide a quick and effective solution that allows them to run gcloud commands directly from their browser. What should you do?

• A. Advise the developer to use the Cloud Shell Terminal.
• B. Instruct the developer to install Cloud Code in their local integrated development environment (IDE).
• C. Tell the developer to provision a Cloud Workstation and use its terminal to run the commands.
• D. Guide the developer to download and install the Google Cloud SDK on their workstation.

Your company has an application that is running on multiple instances of Compute Engine. It generates 1 TB per day of logs. For compliance reasons, the logs need to be kept for at least two years. The logs need to be available for active query for 30 days. After that, they just need to be retained for audit purposes. You want to implement a storage solution that is compliant, minimizes costs, and follows Google-recommended practices.
What should you do?

• A. 1. Install the Cloud Ops agent on all instances.
  2. Create a sink to export logs into a regional Cloud Storage bucket.
  3. Create an Object Lifecycle rule to move files into a Coldline Cloud Storage bucket after one month.
  4. Configure a retention policy at the bucket level to create a lock.
• B. 1. Install the Cloud Ops agent on all instances.
  2. Create a sink to export logs into a partitioned BigQuery table.
  3. Set a time_partitioning_expiration of 30 days.
• C. 1. Create a daily cron job, running on all instances, that uploads logs into a partitioned BigQuery table. 2. Set a time_partitioning_expiration of 30 days.
• D. 1. Write a daily cron job, running on all instances, that uploads logs into a Cloud Storage bucket.
  2. Create a sink to export logs into a regional Cloud Storage bucket.
  3. Create an Object Lifecycle rule to move files into a Coldline Cloud Storage bucket after one month.

You are building a continuous deployment pipeline for a project stored in a Git source repository and want to ensure that code changes can be verified deploying to production. What should you do?

• A. Use Jenkins to monitor tags in the repository. Deploy staging tags to a staging environment for testing.After testing, tag the repository for production and deploy that to the production environment.
• B. Use Jenkins to build the staging branches and the master branch. Build and deploy changes to production for 10% of users before doing a complete rollout.
• C. Use Spinnaker to deploy builds to production using the red/black deployment strategy so that changes can easily be rolled back.
• D. Use Spinnaker to deploy builds to production and run tests on production deployments.