Ray manages, executes, and optimizes compute needs across AI workloads. It unifies infrastructure by leveraging any compute instance and accelerator on AWS via a single, flexible framework—enabling any AI workload from data processing to model training to model serving and beyond.
Started as a research project in 2016, Ray today is used by leading AI organizations like Uber, Spotify, Netflix, Pinterest, OpenAI, and many more. Across the ecosystem, it is powering 1 million clusters each month for AI and GenAI workloads (and growing).
At Ray Summit 2024, Anyscale released powerful new features to make Anyscale’s RayTurbo available to customers on-premise with Machine Pools, in the cloud, and on Kubernetes with the Anyscale Operator for Kubernetes.
They also introduced powerful new governance tooling and an Advanced Instance Manager to speed up cluster launch and to optimize the infrastructure used for AI workloads.
Seamlessly upgrade existing Kubernetes customers using Kuberay to Anyscale for improved performance, efficiency, reliability, and scalability
Power new AI workloads on existing Kubernetes cluster with Anyscale’s RayTurbo
Dominic Catalano, Product Manager Anyscale
Yifei Feng, Engineering Manager Anyscale
Access Anyscale today to see how companies using Anyscale and Ray benefit from rapid time-to-market and faster iterations across the entire AI lifecycle.