I think this argument presumes that everything is the sort of problem that maps well to redis and kafka. Scientific computing doesn't. And while things like numpy might lower contention on the GIL a bit, it's not a cure-all.

Finely-grained locks are useful. Even when you end up scaling between machines, it can be useful to have many threads in one memory space to maximize what you get out of one machine.

We're moving up to hundreds of cores; Python often being stuck only being able to use a couple while tightly coupling state has been unfortunate.