Go Optimization Guide

Yup, it's a fairly low-level language intended as a replacement to C/C++ but for modern day systems (networked, concurrent, etc). You don't have manual memory management per se but you still need to decide on heap vs stack and consider the hardware.

"you still need to decide on heap vs stack"

No, you can't decide on heap vs stack. Go's compiler decides that. You can get feedback about the decision if you pass the right debug flags, and then based on that you may be able to tickle the optimizer into changing its mind based on code changes you make, but it'll always be an optimization decision subject to change without notice in any future versions of Go, just like any other language where you program to the optimizer.

If you need that level of control, Go is generally not the right language. However, I would encourage developers to be sure they need that level of control before taking it, and that's not special pleading for Go but special pleading for the entire class of "languages that are pretty fast but don't offer quite that level of control". There's still a lot of programmers running around with very 200x ideas of performance, even programmers who weren't programmers at the time, who must have picked it up by osmosis.

(My favorite example to show 200x perf ideas is paginated APIs where the "pages" are generally chosen from the set {25, 50, 100} for "performance reasons". In 2025, those are terribly, terribly small numbers. Presenting that many results to humans makes sense, but my default size for paginating API calls nowadays is closer to 1000, and that's the bottom end, for relatively expensive things. If I have no reason to think it's expensive, tack another order of magnitude on to my minimum.)

Just an anecdote from work to back this up. I wrote a system that was taking requests, making another request to a service (that basically wrapped elasticsearch) and then processed the results and returned to the results to the caller.

By default the elastic-search results were paginated and defaulted to some small number in the order of 25..100. I increased this steadily upwards beyond 100,000 to the point where every request always returned the entire result in the first page. And it _transformed_ the performance of the service. From one that was unbearably slow for human users to one that _felt_ instantaneous. I had real perf numbers at the time, but now all I have are the impressions.

But the lesson on the impact of the overhead of those paginated calls was important. Obviously everything is specific and YMMV, but this something worth having in the back of your mind.