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Google Professional-Cloud-Database-Engineer Exam Syllabus Topics:

Topic 1
  • Reverse replication from Google Cloud to source
  • Evaluate appropriate database solutions on Google Cloud
Topic 2
  • Provision high availability database solutions in Google Cloud
  • Design scalable and highly available cloud database solutions
Topic 3
  • Apply concepts to implement highly scalable and available databases in Google Cloud
  • Given a scenario, define maintenance windows and notifications based on application availability requirements
Topic 4
  • Design for recovery time objective (RTO) and recovery point objective (RPO)
  • Assess slow running queries and database locking and identify missing indexes
Topic 5
  • Analyze relevant variables to perform database capacity and usage planning
  • Design scalable, highly available, and secure databases
Topic 6
  • Automate database instance provisioning
  • Determine how applications will connect to the database
Topic 7
  • Plan and perform database migration, including fallback plans and schema conversion
  • Test high availability and disaster recovery strategies periodically
Topic 8
  • Deploy scalable and highly available databases in Google Cloud
  • Determine database connectivity and access management considerations
Topic 9
  • Evaluate performance and cost tradeoffs of different database configurations
  • Plan database upgrades for Google Cloud-managed databases

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q12-Q17):


Your application uses Cloud SQL for MySQL. Your users run reports on data that relies on near-real time; however, the additional analytics caused excessive load on the primary database. You created a read replica for the analytics workloads, but now your users are complaining about the lag in data changes and that their reports are still slow. You need to improve the report performance and shorten the lag in data replication without making changes to the current reports. Which two approaches should you implement? (Choose two.)

  • A. Create additional read replicas, and partition your analytics users to use different read replicas.
  • B. Disable replication on the primary instance, and set the flag for parallel replication on the primary instance. Re-enable replication and optimize performance by setting flags on the read replica.
  • C. Create secondary indexes on the replica.
  • D. Move your analytics workloads to BigQuery, and set up a streaming pipeline to move data and update BigQuery.
  • E. Disable replication on the read replica, and set the flag for parallel replication on the read replica. Re-enable replication and optimize performance by setting flags on the primary instance.

Answer: A,D


You need to migrate existing databases from Microsoft SQL Server 2016 Standard Edition on a single Windows Server 2019 Datacenter Edition to a single Cloud SQL for SQL Server instance. During the discovery phase of your project, you notice that your on-premises server peaks at around 25,000 read IOPS. You need to ensure that your Cloud SQL instance is sized appropriately to maximize read performance. What should you do?

  • A. Create a SQL Server 2019 Enterprise on High Memory machine type with 16 vCPUs, 104 GB of RAM, and 500 GB of SSD.
  • B. Create a SQL Server 2019 Standard on High Memory machine type with 16 vCPUs, 104 GB of RAM, and 4 TB of SSD.
  • C. Create a SQL Server 2019 Standard on Standard machine type with 4 vCPUs, 15 GB of RAM, and 800 GB of solid-state drive (SSD).
  • D. Create a SQL Server 2019 Standard on High Memory machine type with at least 16 vCPUs, 104 GB of RAM, and 200 GB of SSD.

Answer: D


Your team uses thousands of connected IoT devices to collect device maintenance data for your oil and gas customers in real time. You want to design inspection routines, device repair, and replacement schedules based on insights gathered from the data produced by these devices. You need a managed solution that is highly scalable, supports a multi-cloud strategy, and offers low latency for these IoT devices. What should you do?

  • A. Use Firestore with Looker.
  • B. Use Bigtable with Looker.
  • C. Use MongoD8 Atlas with Charts.
  • D. Use Cloud Spanner with Data Studio.

Answer: C


Your organization has a production Cloud SQL for MySQL instance. Your instance is configured with 16 vCPUs and 104 GB of RAM that is running between 90% and 100% CPU utilization for most of the day. You need to scale up the database and add vCPUs with minimal interruption and effort. What should you do?

  • A. Issue a gcloud sql instances patch command to increase the number of vCPUs.
  • B. Back up the database, create an instance with additional vCPUs, and restore the database.
  • C. Issue a gcloud compute instances update command to increase the number of vCPUs.
  • D. Update a MySQL database flag to increase the number of vCPUs.

Answer: A


You host an application in Google Cloud. The application is located in a single region and uses Cloud SQL for transactional dat a. Most of your users are located in the same time zone and expect the application to be available 7 days a week, from 6 AM to 10 PM. You want to ensure regular maintenance updates to your Cloud SQL instance without creating downtime for your users. What should you do?

  • A. Create your database with one primary node and one read replica in the region.
  • B. Configure your Cloud SQL instance with high availability enabled.
  • C. Enable maintenance notifications for users, and reschedule maintenance activities to a specific time after notifications have been sent.
  • D. Configure a maintenance window during a period when no users will be on the system. Control the order of update by setting non-production instances to earlier and production instances to later.

Answer: D



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