A caching pattern is a software design pattern that improves the performance of an application by storing frequently accessed data in a temporary location. This temporary location, called a cache, is typically faster to access than the original data source, such as a database or a server.
Knowing what the expect and how to mitigate the issues with caching is the first step towards a successful caching implementation.
Adding a cache is usually a good way to reduce load on your database, but it does come at the cost of increased complexity. This video looks at the most commong caching pattern, and the problems that can occur.
00:00:00 Intro
00:00:35 Cache Aside
00:01:01 Implementation
00:06:52 Cache Invalidation
00:07:28 Eviction Policy
00:09:15 Key Expiration
00:10:37 Write-Through Caching
00:12:49 Outro
GitHub Project:
https://github.com/dreamsofcode-io/spellbook
