Ray on a Mac
Distributed compute for AI (training/serving/tuning) · AI Clusters
Ray scales Python/AI workloads across a cluster; Ray Train, Tune, Serve and RLlib, with autoscaling and GPU scheduling. pip install 'ray[default]', then ray start --head (dashboard on :8265, GCS on :6379) and join workers with ray start --address=…. Monitor via the dashboard or ray status / the Jobs & State REST API (:8265). Pairs with vLLM (Ray Serve) and KubeRay on Kubernetes.
Run Ray with FrontierStack
Install or connect Ray; then check its status, ports and certificate from FrontierStack. The same screen links to firewall checks, Malware Audit and backups where they apply.
Run it from your Mac.
FrontierStack installs, monitors and secures services on this Mac and on linked servers.
Download FrontierStackApple notarized · Safe & secure · macOS 13 Ventura+