The world could run on older hardware if software optimization was a priority

So I've worked for Google (and Facebook) and it really drives the point home of just how cheap hardware is and how not worth it optimizing code is most of the time.

More than a decade ago Google had to start managing their resource usage in data centers. Every project has a budget. CPU cores, hard disk space, flash storage, hard disk spindles, memory, etc. And these are generally convertible to each other so you can see the relative cost.

Fun fact: even though at the time flash storage was ~20x the cost of hard disk storage, it was often cheaper net because of the spindle bottleneck.

Anyway, all of these things can be turned into software engineer hours, often called "mili-SWEs" meaning a thousandth of the effort of 1 SWE for 1 year. So projects could save on hardware and hire more people or hire fewer people but get more hardware within their current budgets.

I don't remember the exact number of CPU cores amounted to a single SWE but IIRC it was in the thousands. So if you spend 1 SWE year working on optimization acrosss your project and you're not saving 5000 CPU cores, it's a net loss.

Some projects were incredibly large and used much more than that so optimization made sense. But so often it didn't, particularly when whatever code you wrote would probably get replaced at some point anyway.

The other side of this is that there is (IMHO) a general usability problem with the Web in that it simply shouldn't take the resources it does. If you know people who had to or still do data entry for their jobs, you'll know that the mouse is pretty inefficient. The old terminals from 30-40+ years ago that were text-based had some incredibly efficent interfaces at a tiny fraction of the resource usage.

I had expected that at some point the Web would be "solved" in the sense that there'd be a generally expected technology stack and we'd move on to other problems but it simply hasn't happened. There's still a "framework of the week" and we're still doing dumb things like reimplementing scroll bars in user code that don't work right with the mouse wheel.

I don't know how to solve that problem or even if it will ever be "solved".

Except you’re self selecting for a company that has high engineering costs, big fat margins to accommodate expenses like additional hardware, and lots of projects for engineers to work on.

The evaluation needs to happen in the margins, even if it saves pennies/year on the dollar, it’s best to have those engineers doing that than have them idling.

The problem is that almost no one is doing it, because the way we make these decisions has nothing to do with the economical calculus behind, most people just do “what Google does”, which explains a lot of the disfunction.

I think the parent's point is that if Google with millions of servers can't make performance optimization worthwhile, then it is very unlikely that a smaller company can. If salaries dominate over compute costs, then minimizing the latter at the expense of the former is counterproductive.

> The evaluation needs to happen in the margins, even if it saves pennies/year on the dollar, it’s best to have those engineers doing that than have them idling.

That's debatable. Performance optimization almost always lead to complexity increase. Doubled performance can easily cause quadrupled complexity. Then one has to consider whether the maintenance burden is worth the extra performance.