Choose Professional-Cloud-Architect most accurate study material

You are creating an App Engine application that uses Cloud Datastore as its persistence layer. You need to retrieve several root entities for which you have the identifiers. You want to minimize the overhead in operations performed by Cloud Datastore. What should you do?

• A. Create the Key object for each Entity and run a batch get operation
• B. Use the identifiers to create a query filter and run multiple query operations, one operation for each entity
• C. Create the Key object for each Entity and run multiple get operations, one operation for each entity
• D. Use the identifiers to create a query filter and run a batch query operation

As part of implementing their disaster recovery plan, your company is trying to replicate their production MySQL database from their private data center to their GCP project using a Google Cloud VPN connection.
They are experiencing latency issues and a small amount of packet loss that is disrupting the replication. What should they do?

• A. Restore their database daily using Google Cloud SQL.
• B. Add additional VPN connections and load balance them.
• C. Configure a Google Cloud Dedicated Interconnect.
• D. Configure their replication to use UDP.
• E. Send the replicated transaction to Google Cloud Pub/Sub.

For this question, refer to the TerramEarth case study.
You start to build a new application that uses a few Cloud Functions for the backend. One use case requires a Cloud Function func_display to invoke another Cloud Function func_query. You want func_query only to accept invocations from func_display. You also want to follow Google ' s recommended best practices. What should you do?

• A. Create those two functions in the same project and VPC. Make func_query only accept internal traffic.Create an ingress firewall for func_query to only allow traffic from func_display. Also, make sure both functions use the same service account.
• B. Make func _query ' Require authentication ' and only accept internal traffic. Create those two functions in the same VPC. Create an ingress firewall rule for func_query to only allow traffic from func_display.
• C. Make func_query ' Require authentication. ' Create a unique service account and associate it to func_display. Grant the service account invoker role for func_query. Create an id token in func_display and include the token to the request when invoking func_query.
• D. Create a token and pass it in as an environment variable to func_display. When invoking func_query, include the token in the request Pass the same token to func _query and reject the invocation if the tokens are different.

You are migrating third-party applications from optimized on-premises virtual machines to Google Cloud.
You are unsure about the optimal CPU and memory requirements. The applications have a con sistent usage pattern across multiple weeks. You want to optimize resource usage for the lowest cost . What should you do?

• A. 1. Create multiple Compute Engine instances with varying CPU and memory options.
  2. Install the Ops Agent, and deploy the third-party application on each of them.
  3. Run a load test with high traffic levels on the application, and use the results to determine the optimal settings.
• B. 1. Create an App Engine flexible environment, and deploy the third-party application using a Dockerfile and a custom runtime.
  2. Set CPU and memory options similar to your application ' s current on-premises virtual machine in the app.yaml file.
• C. 1. 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.
  2. Create a managed instance group that uses average CPU utilization to autoscale the number of instances in the group.
  3. Modify the average CPU utilization threshold to optimize the number of instances running.
• D. 1. Create a Compute Engine instance with CPU and memory options similar to your application's current on-premises virtual machine.
  2. Install the Ops agent, and deploy the third-party application.
  3. Run a load test with normal traffic levels on the application, and follow the Rightsizing Recommendations in the Google Cloud console.

For this question refer to the TerramEarth case study
Operational parameters such as oil pressure are adjustable on each of TerramEarth ' s vehicles to increase their efficiency, depending on their environmental conditions. Your primary goal is to increase the operating efficiency of all 20 million cellular and unconnected vehicles in the field How can you accomplish this goal?

• A. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically.
• B. Capture all operating data, train machine learning models that identify ideal operations, and host in Google Cloud Machine Learning (ML) Platform to make operational adjustments automatically.
• C. Have your engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically.
• D. Capture all operating data, train machine learning models that identify ideal operations, and run locally to make operational adjustments automatically.