> It's 8 K B per thread, so you can scale a thousand times further than you thought. One dark secret of the async movement is that if your goal is C10K (10,000 concurrent clients) then actually bog standard threading will handle that fine these days.

Default virtual memory allocation for threads on Linux distributions tends to be 8 megabytes. Actual memory used is the peak stack depth used, rounded up a bit. It'd be pretty unusual to only use as little as 8 kilobytes per thread; just the standard per-thread libc context information for concurrency is a few kilobytes, plus at least one page of stack, plus the kernel's information about the thread (which isn't counted against the process)...

Yes, you can spawn thousands of threads on relatively modest hardware; I was spawning thousands of threads a decade ago.

Spawning 5000 bare-minimal python threads that do nil seems to use about 300 megs of ram on my system; real threads that do anything substantial will use a whole lot more, even if their use of the stack depth is intermittent.

Not to mention allocators that cache part of freed heap per-thread, etc.