Which optimization strategy do you prefer in Go compilers?

19 Tem 08:28

I usually start by focusing on runtime analysis to find bottlenecks, bro. Since Go's own compiler and GC are already pretty smart, it makes more sense to me to understand where I'm losing time rather than jumping into manual optimizations. First, I grab CPU and memory profiles with `pprof`, then I extract the hotspots and start optimizing from there. For example, if a specific function is consistently taking up 40% of the CPU in HTTP handlers or database queries, I zero in on that right away. But of course, I don’t stop at compiler-level optimizations. I remove debug symbols and enable linking optimizations using `-ldflags="-s -w"`, for instance. With Go 1.18+, I also support runtime optimizations with flags like `-tags=netgo` and `-race`. So, after runtime analysis, I use compiler optimizations in a supporting role—not as the primary strategy. Otherwise, the code complexity increases unnecessarily, and debugging becomes a pain.