Foundations of Scalable Systems

Chapter 6. Distributed Caching

Caches exist in many places in an application. The CPUs that run your applications have fast, multilevel hardware caches to reduce relatively slow main memory accesses. Database engines can make use of main memory to cache the contents of the data store so that in many cases queries do not have to touch relatively slow disks.

Distributed caching is an essential ingredient of a scalable system. Caching makes the results of expensive queries and computations available for reuse by subsequent requests at low cost. By not having to reconstruct the cached results for every request, the capacity of the system is increased, and it can scale to handle greater workloads.

I’ll cover two flavors of caching in this chapter. Application caching requires business logic that incorporates the caching and access of precomputed results using distributed caches. Web caching exploits mechanisms built into the HTTP protocol to enable caching of results within the infrastructure provided by the internet. When used effectively, both will protect your services and databases from heavy read traffic loads.

Application Caching

Application caching is designed to improve request responsiveness by storing the results of queries and computations in memory so they can be subsequently served by later requests. For example, think of an online newspaper site where readers can leave comments. Once posted, articles change infrequently, if ever. New comments tend to get posted soon ...