Your company manages an application that captures stock data in an internal database. You need to create an API that provides real-time stock data to users. You want to return stock data to users as quickly as possible, and you want your solution to be highly scalable. What should you do?
By using Memorystore for Redis as a caching layer for the most frequently accessed stock data, you can significantly reduce latency and improve scalability. In this design, your API queries Redis first for real-time data, and if the data isn’t available there, it falls back to the internal database. This approach minimizes the response time for common requests while maintaining access to complete data when necessary.