[donnygreenberg]

Good question. We actually use Ray to handle a bunch of the scheduling within the compute, but largely see our role as outside the compute. Meaning, Ray provides a powerful DSL for distributed compute, while we are aggressively DSL-free so users can ship Ray code, PyTorch Distributed, Accelerate, Horovod, etc. to their hardware through Runhouse. We're more focused on connecting disparate compute and storage and making them multiplayer (but largely see the cluster as an opaque unit of compute) while they're more focused on enabling distribution inside the cluster, if that makes sense.