Introduction to the Problem
In modern web applications, there are different types of data that the client consumes from the server: dynamic data (like product listings or shopping carts), user-specific data, and static lookup data. Lookup data might include lists such as countries, regions, currencies, ZIP codes, or dropdown configurations that rarely change but must be available on every client session. Usually, to store and retrieve such data, a distributed cache is used, for example, Redis (from my practice). However, in large systems with dozens of endpoints and high-throughput requirements, even a distributed cache can become a performance bottleneck.
That is exactly the situation I faced on one of my past projects, and in this article, I will share with you the approach we used to build a more efficient caching strategy using HTTP cache headers and versioning.