Inspect Redis artistry!

This article will probe into the magic of Redis for cache management, to reduce client workload and speed up your application.

Over a period of time, I kept wondering how a large scale application would respond impulsively when the number of users increase rapidly, which means large audience interaction, large database requests, large response time, and obviously large costs. 🙄 🤔 It was really strange for me to understand the whole situation because of my very less experience in the IT industry to know how could we actually save the god damn database requests? As far as I knew saving data could be done via database only.

When I was cogitating about the solution, there came a sudden notion about Caching technique!🙇

What is Caching?

Caching is the process of storing some data in Cache. It is a temporary storage component area where the data is stored so that in future. Data can be served faster.

The distributed cache is a widely-adopted design pattern for building robust and scalable applications. By serving data from the cache, and instead of fetching it from slower devices or re-computing it, the application’s overall performance is improved.

The cache also relieves some of the load on external data sources as well as improves the availability of the application…