Always running the same queries over and over... and waiting seconds after seconds, minutes after minutes.
It's not about being lazy, a dev first of all is a person with immense patience.
Patience doesn't last forever, at some point, it expires, you don't have it anymore. Exactly like data in a cache.
But the cache can be configured to retain data as long as you want. But, what about your patience? Still wanna be slow? Stressed about slowness?
Start caching your queries.
Start caching your web API call.
Start caching anything you need, just for the sake of getting it back at the speed of light.
That's the purpose of a cache. Retrieve your data instantly.
But retrieving data from the cache is just one side of the coin, what happens when you flip it?
Well, you need a mechanism to load, to feed your cache, and that's what you will discover in this presentation.
Best practices, patterns, and anti-patterns to load your cache, using Redis Stack as distributed cache and Spring Data as your Swiss army knife.
You will also learn how to distribute your cached data and get them updated automatically.
I started with computers in the early 80s when I was a kid. I began with a Commodore Vic-20, passing through a Sinclair, a Commodore 64, and an Atari ST 1040.
I spent days and nights giving breath mints to Otis.
It was a rollercoaster, jumping from project to project, from company to company until I landed in 2012 in Red Hat. An amazing experience that lasted more than 7 years.
Next, I had the privilege to learn all about observability and monitoring with Datadog. Such a great solution!!!
But in 2021 I received a call from Redis, a technology made in Italy.
Redis is the place where apps and data merge together and they enjoy it.