Even as a new grad in full stack engineering, I found that I could've used a lot of these tips to manage my project team in college. We had been testing our models/algorithms on one user and hadn't anticipated how to scale up at all. I'll definitely be keeping these in mind in my future projects.
It’s frustrating how almost all scaling advice is focused on stuff like how to manage a fleet of 100s of servers or implement consensus algorithms. Enterprise startups in many cases really should be treating servers like pets, not cattle.
I totally agree with the author’s point about driving decisions with empirical evidence. It’s really useful to have in mind reasonable benchmarks and expectations for performance and systems to determine whether those are met.