Caddy is not going to fix anything, on the contrary, it consumes more ram. Generally the instances have been slowing down when swap gets hit by the db, so lowering ram usage and optimizing that should be the first priority.
Context size is huge, as well as the ability to context switch effectively. It can mean the difference between solving something in a day or weeks.
I like problem decomposition a lot as a discrete step. There's a huge tendency to go, I have problem A, let's just solve with it B. Many times the nuance of why A occurred, whether it's a symptom of something, and what are the different subproblems that comprise A are skipped.
This often causes solutions which don't actually solve the problem, or just mask it. That extra effort up front, leads to the proper solution, and as you said, very tactical fixes instead of huge unnecessary solutions.
Definitely agree there! Communication is super underrated, especially with how difficult it can be to align people and teams across organizations.
Jargon is great for consolidating complexity into just a few words, reducing the things you have to think about. It can be equally valuable though to poke into implicit assumptions that are commonly made.
It's definitely a balance, and being inclusive in conversations is super important as you mentioned. It allows newer folks to get up to speed much faster in comparison, and allows more engagement across the people within the discussions.
What API are you using? Where is the data stored? Would be easier to answer with more data on how this is setup.
Doesn’t support HA or horizontal scaling yet from what I read. Unsure if kbin does. Probably would have to add support for horizontal scaling to have that auto scaling do anything.
Sorry if I was curt! No reason to be sorry for throwing out a decent idea