
Explanation:
The question asks for an SQL database architecture that minimizes costs and user disruption during a gradual rollout, with the ability to scale up or down based on demand, such as nights and holidays. Option A suggests using Oracle Real Application Cluster (RAC) databases on Bare Metal Solution for Oracle, which is a high-cost solution and not the best fit for minimizing costs or for a cloud-native approach. Option B proposes using sharded Cloud SQL instances, which allows for isolating stores to individual instances, minimizing disruption during rollout, and enabling cost-effective scaling. However, managing multiple instances can become complex. Option C suggests using a Bigtable cluster with autoscaling, but Bigtable is a NoSQL database, not SQL, which doesn't meet the requirement for an SQL database. Option D recommends using Cloud Spanner with a custom autoscaling solution. Cloud Spanner is a fully managed, scalable, relational database service that supports SQL queries, and adding a custom autoscaling solution can help manage costs and performance during varying loads, making it the most suitable option among the choices provided.
Ultimate access to all questions.
How would you design an SQL database architecture for a centralized inventory management system tracking 200 stores (each with 500 GB of data) that supports a gradual regional rollout, minimizes costs and user disruption, and allows scaling up or down during nights and holidays?
A
Use Oracle Real Application Cluster (RAC) databases on Bare Metal Solution for Oracle.
B
Use sharded Cloud SQL instances with one or more stores per database instance.
C
Use a Biglable cluster with autoscaling.
D
Use Cloud Spanner with a custom autoscaling solution.
No comments yet.