You recently launched a new product to the US market. You currently have two Bigtable clusters in one US region to serve all the traffic. Your marketing team is planning an immediate expansion to APAC. You need to roll out the regional expansion while implementing high availability according to Google-recommended practices. What should you do?

• A.Maintain a target of 35% CPU utilization by locating:
  cluster-a in zone us-central1-a
  cluster-b in zone us-central2-a
  cluster-c in zone asia-northeast1-b
  cluster-d in zone asia-east1-b
• B.Maintain a target of 23% CPU utilization by locating:
  cluster-a in zone us-central1-a
  cluster-b in zone europe-west1-d
  cluster-c in zone asia-east1-b
• C.Maintain a target of 35% CPU utilization by locating:
  cluster-a in zone us-central1-a
  cluster-b in zone australia-southeast1-a
  cluster-c in zone europe-west1-d
  cluster-d in zone asia-east1-b
• D.Maintain a target of 23% CPU utilization by locating:
  cluster-a in zone us-central1-a
  cluster-b in zone us-central1-b
  cluster-c in zone us-east1-a

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You are building an application that allows users to customize their website and mobile experiences. The application will capture user information and preferences. User profiles have a dynamic schema, and users can add or delete information from their profile. You need to ensure that user changes automatically trigger updates to your downstream BigQuery data warehouse. What should you do?

• A.Use Firestore in Datastore mode, and store user profile data as a document. Update the user profile with preferences specific to that user and use the user identifier to query.
• B.Store your data in Bigtable, and use the user identifier as the key. Use one column family to store user profile data, and use another column family to store user preferences.
• C.Use Firestore in Native mode, and store user profile data as a document. Update the user profile with preferences specific to that user and use the user identifier to query.
• D.Use Cloud SQL, and create different tables for user profile data and user preferences from your recommendations model. Use SQL to join the user profile data and preferences

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Your organization is running a low-latency reporting application on Microsoft SQL Server. In addition to the database engine, you are using SQL Server Analysis Services (SSAS), SQL Server Reporting Services (SSRS), and SQL Server Integration Services (SSIS) in your on-premises environment. You want to migrate your Microsoft SQL Server database instances to Google Cloud. You need to ensure minimal disruption to the existing architecture during migration. What should you do?

• A.Migrate to Cloud SQL for SQL Server.
• B.Migrate to Cloud SQL for PostgreSQL.
• C.Migrate to Compute Engine.
• D.Migrate to Google Kubernetes Engine (GKE).

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You are managing a Cloud SQL for PostgreSQL instance in Google Cloud. You have a primary instance in region 1 and a read replica in region 2. After a failure of region 1, you need to make the Cloud SQL instance available again. You want to minimize data loss and follow Google-recommended practices. What should you do?

• A.Restore the Cloud SQL instance from the automatic backups in region 3.
• B.Restore the Cloud SQL instance from the automatic backups in another zone in region 1.
• C.Check "Lag Bytes" in the monitoring dashboard for the primary instance in the read replica instance. Check the replication status using pg_catalog.pg_last_wal_receive_lsn(). Then, fail over to region 2 by promoting the read replica instance.
• D.Check your instance operational log for the automatic failover status. Look for time, type, and status of the operations. If the failover operation is successful, no action is necessary. Otherwise, manually perform gcloud sql instances failover .

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Your customer has a global chat application that uses a multi-regional Cloud Spanner instance. The application has recently experienced degraded performance after a new version of the application was launched. Your customer asked you for assistance. During initial troubleshooting, you observed high read latency. What should you do?

• A.Use query parameters to speed up frequently executed queries.
• B.Change the Cloud Spanner configuration from multi-region to single region.
• C.Use SQL statements to analyze SPANNER_SYS.READ_STATS* tables.
• D.Use SQL statements to analyze SPANNER_SYS.QUERY_STATS* tables.

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