Google Professional Cloud Database Engineer Question 9
Single answerGoogle Cloud PlatformYour company is planning to migrate a legacy on-premises database system to Google Cloud. The current system handles a workload of 20,000 queries per second (QPS) during peak hours, with each query averaging 2 KB in size. The future workload is expected to grow by 50% within the next two years. Additionally, the database must maintain a 99.99% availability SLA and support automatic scaling to handle traffic spikes. Based on this information, which Google Cloud database solution and configuration would best meet these requirements?
- A
Cloud SQL with a high-availability configuration and vertical scaling.
- B
Cloud Spanner with multi-region deployment and automatic scaling.
- C
BigQuery with reservation-based scaling for predictable costs.
- D
Firestore in Datastore mode with regional configuration.
Show answer and explanation
Correct answer: B
Explanation
Cloud Spanner is the best choice for the given scenario because it is specifically designed to handle high-throughput transactional workloads with global distribution. It offers a 99.99% availability SLA, horizontal scaling, and multi-region deployment, which align perfectly with the current and future requirements of the workload described in the scenario.
- A. Incorrect.
Cloud SQL supports high availability and can handle many use cases, but it has limitations with horizontal scaling and might not efficiently handle the anticipated 50% future growth in traffic and large QPS requirements.
- B. Correct.
Cloud Spanner is designed for high-throughput, globally distributed workloads. It offers multi-region deployments, 99.99% availability SLA, and automatic horizontal scaling, making it ideal for this scenario.
- C. Incorrect.
BigQuery is a data warehouse solution optimized for analytical workloads rather than transactional workloads. It is not suitable for high QPS, low-latency transactional use cases.
- D. Incorrect.
Firestore in Datastore mode is optimized for application backends with NoSQL workloads. While it offers scalability, it is not designed for high QPS transactional workloads with strict consistency and availability requirements.