Distributed computing made simple

Easily develop and deploy distributed Python and machine learning applications, at any scale.

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Upcoming Webinar | Sept 9

Learn how to serve machine learning models at scale with Ray Serve in this live webinar.

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Webinar | On Demand

Join our introductory webinar on using Ray for scaling machine learning workloads.

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Ray Core Tutorial | On Demand

New to Ray? Jump-start your learning with this free hands-on tutorial on Ray Core.

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Origins and mission

Modern workloads, especially in machine learning and artificial intelligence, require immense amounts of compute — which is only possible through distributed execution.

However, building and running distributed apps is hard, and remains inaccessible to most developers. Ray was created at the UC Berkeley RISELab to address this challenge and make distributed computing simple, flexible, and accessible to all engineers.

Vibrant community. Inspiring stories.

Thousands of engineers, developers, and researchers are building the next generation of distributed Python and machine learning systems on Ray to solve all kinds of hard problems — from scaling ecosystem restoration to making boats fly.

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Anyscale platform

Ray simplifies distributed computing. Anyscale simplifies building, running and managing Ray applications. By eliminating infrastructure and cluster management from the equation, Anyscale lets you focus on your application, and reduce time to market.

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Productivity

Focus on your applications, and leave the infrastructure management and compute orchestration to us

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Reliability

Operated by the creators of Ray, rest easy knowing your Ray clusters are in the best hands.

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Scalability

From testing at scale on a multi-terabyte data to deploying to production, access infinite compute with zero code changes

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Performance

Our managed Ray platform provides fast access to clusters, letting you tap into scale quickly and efficiently

Ready to get started?

Sign up for our early access program to try out the infinite laptop experience on Anyscale.

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