Ray Distributed Framework

Ray is a unified open-source framework for building and scaling distributed applications and AI workloads in Python. It provides simple APIs for parallelizing Python functions and classes (tasks and actors) and a toolkit of specialized libraries (Ray Data, Train, Tune, Serve, RLlib) for machine learning. Ray offers a universal compute layer for orchestrating clusters, scheduling processes, fault tolerance, and autoscaling. The project maintains a very frequent release cadence, with minor and patch releases occurring every few weeks.