Comment by theptip
This is 1m nodes, you typically run tens or hundreds of pods per node, each with one or more containers. So more like 100m+ functions if I follow the Erlang analogy correctly?
This is 1m nodes, you typically run tens or hundreds of pods per node, each with one or more containers. So more like 100m+ functions if I follow the Erlang analogy correctly?
Kubernetes is way heavier than Erlang’s lightweight processes, so for millions of tasks at scale, a middle-ground solution could blend Erlang’s concurrency efficiency with k8s’ orchestration power, dodging containers’ overhead while keeping flexibility for diverse workloads. That's if you don't actually need the strict isolation of pods/containers and you're just trying to run something at massive scale. I don't get why so many people want to run everything as heavy container processes or pods vs coming up with a better solution. The point is we don't have to fit every problem into the shoe called kubernetes if it doesn't seem to fit, and we should look at other ways to spin up millions of processes
This is not analogous. It’s just someone beating the Erlang drum. You can’t PyTorch in Erlang.