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Ultimate access to all questions.
You are in the process of migrating third-party applications from optimized on-premises virtual machines to Google Cloud Platform (GCP). You are uncertain about which CPU and memory configurations would be optimal in the cloud environment. The third-party applications exhibit a consistent usage pattern over several weeks. Your goal is to optimize resource usage while minimizing costs. What steps should you take to achieve this?
A
Create an instance template with the smallest available machine type, and use an image of the third-party application taken from a current on-premises virtual machine. Create a managed instance group that uses average CPU utilization to autoscale the number of instances in the group. Modify the average CPU utilization threshold to optimize the number of instances running.
B
Create an App Engine flexible environment, and deploy the third-party application using a Dockerfile and a custom runtime. Set CPU and memory options similar to your application's current on-premises virtual machine in the app.yaml file.
C
Create multiple Compute Engine instances with varying CPU and memory options. Install the Cloud Monitoring agent, and deploy the third-party application on each of them. Run a load test with high traffic levels on the application, and use the results to determine the optimal settings.
D
Create a Compute Engine instance with CPU and memory options similar to your application's current on-premises virtual machine. Install the Cloud Monitoring agent, and deploy the third-party application. Run a load test with normal traffic levels on the application, and follow the Rightsizing Recommendations in the Cloud Console.