▲ | maxbond 11 hours ago | |||||||
I like to call cases like this "premature distribution." Or maybe you could call it "premature capacity." If you have an application running in the cloud with several thousand requests per day, you could probably really benefit from adding a service like Redis. But when you have 0-10 users and 0-1000 requests per day, it can make more sense to write something more monolithic and with limited scalability. Eg, doing everything in Postgres. Caching is especially amenable to adding in later. If you get too far into the weeds managing services and creating scalability you might bogged down and never get your application in front of potential users in the first place. Eg, your UX sucks and key features aren't implemented, but you're tweaking TTLs and getting a Redis cluster to work inside Docker Compose. Is that a good use of your time? If your goal is to get a functional app in front of potential users, probably not. | ||||||||
▲ | not_kurt_godel 11 hours ago | parent | next [-] | |||||||
You probably don't need Redis until you have thousands of requests per minute, nevermind per day. | ||||||||
| ||||||||
▲ | MobiusHorizons 9 hours ago | parent | prev [-] | |||||||
To be clear my question isn’t claiming redis isn’t premature optimization, but rather asking why the op thinks that it is. Being new doesn’t automatically mean that there is no need for latency sensitivity. Making that assumption could be just as premature. Ripping something out that is already working also takes time and the trade offs need to be weighed. | ||||||||
|