You are working at an institution that processes medical data. You are migrating several workloads onto Google Cloud. Company policies require all workloads to run on physically separated hardware, and workloads from different clients must also be separated You created a sole-tenant node group and added a node for each client. You need to deploy the workloads on these dedicated hosts. What should you do?

• A.Add the node group name as a network tag when creating Compute Engine instances in order to host each workload on the correct node group.
• B.Add the node name as a network tag when creating Compute Engine instances in order to host each workload on the correct node.
• C.Use node affinity labels based on the node group name when creating Compute Engine instances in order to host each workload on the correct node group
• D.Use node affinity labels based on the node name when creating Compute Engine instances in order to host each workload on the correct node.

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Your company captures all web traffic data in Google Analytics 360 and stores it in BigQuery. Each country has its own dataset. Each dataset has multiple tables. You want analysts from each country to be able to see and query only the data for their respective countries.
How should you configure the access rights?

• A.Create a group per country. Add analysts to their respective country-groups. Create a single group
  'all_analysts', and add all country-groups as members. Grant the 'all-analysts' group the IAM role of BigQuery dataViewer. Share the appropriate dataset with view access with each respective analyst country- group.
• B.Create a group per country. Add analysts to their respective country-groups. Create a single group
  'all_analysts', and add all country-groups as members. Grant the 'all-analysts' group the IAM role of BigQuery dataViewer. Share the appropriate table with view access with each respective analyst country- group.
• C.Create a group per country. Add analysts to their respective country-groups. Create a single group
  'all_analysts', and add all country-groups as members. Grant the 'all-analysts' group the IAM role of BigQuery jobUser. Share the appropriate tables with view access with each respective analyst country- group.
• D.Create a group per country. Add analysts to their respective country-groups. Create a single group
  'all_analysts', and add all country-groups as members. Grant the 'all-analysts' group the IAM role of BigQuery jobUser. Share the appropriate dataset with view access with each respective analyst country- group.

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During a high traffic portion of the day, one of your relational databases crashes, but the replica is never promoted to a master. You want to avoid this in the future.
What should you do?

• A.Use a different database
• B.Choose larger instances for your database
• C.Create snapshots of your database more regularly
• D.Implement routinely scheduled failovers of your databases

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For this question, refer to the TerramEarth case study.
TerramEarth has equipped unconnected trucks with servers and sensors to collet telemetry data. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs. What should they do?

• A.Have the vehicle' computer compress the data in hourly snapshots, and store it in a Google Cloud storage (GCS) Nearline bucket.
• B.Push the telemetry data in Real-time to a streaming dataflow job that compresses the data, and store it in Google BigQuery.
• C.Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable.
• D.Have the vehicle's computer compress the data in hourly snapshots, a Store it in a GCS Coldline bucket.

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You deploy your custom java application to google app engine.
It fails to deploy and gives you the following stack trace:

• A.Digitally sign all of your JAR files and redeploy your application.
• B.Upload missing JAR files and redeploy your application
• C.Recompile the CLoakedServlet class using and MD5 hash instead of SHA1

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