Caching patterns for lazy devs for lazy loading by Luigi Fugaro

Note: as the video registration was lost due to a technical issue, the recovered low quality audio has been remixed with the slides kindly provided by the speaker. 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.