Anyscale

Every developer and every team should be able to succeed with AI without worrying about building and managing infrastructure. To make that possible, we aim to remove distributed systems expertise from the critical path of realizing the business potential of AI. Machine learning and AI are urgent competitive necessities, but companies struggle with scale, production, and expertise. With Ray and Anyscale, developers of all skill levels can easily build applications that run at any scale, from a laptop to a data center. We're thrilled to see how far the Ray project has come. Now, developers at industry leaders like Uber, OpenAI, Shopify, and Amazon are building their next-generation machine learning platforms using Ray. And we're going to keep building — because the future of computing is distributed.Are you passionate about Ray, scalable AI and distributed computing? Join us at Ray Summit! Find out more! Products Solutions Ecosystem Success Stories Learn Company Try It Now Build, deploy, and manage scalable AI and Python applications Use Ray on Anyscale, the unified compute platform from the creators of Ray Watch Demo The Anyscale Platform, a fully managed Ray platform The Anyscale Platform offers key advantages over Ray open source. It provides a seamless user experience for developers and AI teams to speed development, and deploy AI/ML workloads at scale. Companies using Anyscale benefit from rapid time-to-market and faster iterations across the entire AI lifecycle. Orchestration Experiment management Hyperparameter Tuning Training Data / features Serving / Applications Explainability / Observability Any cloud Download the Anyscale Platform Overview Download the Ray Overview Accelerate Development & Scaling of ML and Python Workloads Anyscale Workspaces. Workspaces provides an integrated IDE experience that allows teams to edit and run code, install dependencies, monitor jobs and resources across a scalable cluster just like you would on your laptop. Use the tools you know and already love. Anyscale provides integration and instant setup for popular tools such as VSCode and Jupyter notebook, with Github, Weights & Biases, and more. Collaborate. Share or clone experiments with a click of a button. Different users can access a workspace with all the same configuration and environments and be productive instantaneously Learn More Production-Grade, Fully Managed Service Fully managed service. Anyscale operates clusters of machines on demand so AI teams don't have to operate the cluster. ML practitioners get access to an interactive, scalable compute environment. It accelerates application development irrespective of the scale of the workloads. Bring your own cloud. Anyscale is built from the ground up with customer data security in mind. It runs in an organization's infrastructure and cloud account, while still providing an exceptional managed experience. Optimize compute costs. Anyscale's autoscaling and auto-suspend features, and spot instance support allow teams to reduce the compute costs of running workloads while leveraging their existing agreements public cloud environments. Security and Compliance Security and Access Control. Anyscale gives users secure secrets management within the Anyscale environment. All logs and user-related data are securely managed in a customer's private environment. Auditing and logging provide transparency into user access and actions. Secure network controls ensure communications take place over private cloud-provider networks. Governance and compliance. Anyscale provides user access controls for projects, workspaces and clusters as well as cost tracking mechanism. Anyscale has SOC 2 Type 1 attestation. Seamlessly Move Between Development and Production A unified environment for development and production. Anyscale focuses the experience on a unified environment - run, debug, and test your code at scale on the same cluster configuration with the same software dependencies for both development and production. Flexible and extensive dependency management. Anyscale provides different options to manage your dependencies across your cluster. You can use existing base images, bring your own Docker, or use Ray's runtime environments for faster iteration. Jobs and services API and SDK. Anyscale provides an easy interface to operationalize your workloads and integrate with your existing deployment tools. Anyscale Jobs support cron jobs, ephemeral cluster creation and retry capabilities, while Anyscale Services provides replica management, no downtime upgrades and high availability. Learn More Monitoring and Observability Managed logs, monitoring, and observability. Anyscale provides a production-grade monitoring and observability stack with a managed Grafana and Ray dashboard. Additionally, Anyscale provides production monitoring and notifications for added trust that pipelines are running well. Learn More “The scale, simplicity, and support from Anyscale has enabled us to significantly speed up our time-to-market on new products and experiences for our players.' Emiliano Castro Principle Data Scientist Automate. Monitor. Manage. Robust APIs and SDKs Automate jobs and cluster management or integrate into your CI/CD pipelines with simple, intuitive APIs and SDKs. Observability Centrally monitor the health of your jobs and resources with out of the box Grafana dashboards. Or send logs and metrics to your existing observability stack. Cost tracking Keep tabs on the costs tied to jobs, clusters, and users in a single intuitive UI. 'We chose Ray as the unified compute backend for our machine learning and deep learning platform because it has allowed us to significantly improve performance and fault tolerance, while also reducing the complexity of our technology stack. Ray has brought significant value to our business.' Xu Ning Senior Manager, Uber AI Platform Why Ray Users Choose Anyscale Faster Development Speed developer productivity with Anyscale's fully integrated development environment that includes a ML Workspace, Ray client, Ray libraries, and integrations with popular ML tools and frameworks. Easy, Elastic Scaling Leverage Anyscale's operational monitoring and cost management capabilities for comprehensive observability into model execution. Anyscale + AWS Learn how companies leverage Anyscale and AWS to scale their machine learning and Python applications. Simplify Scaling ML & Python Workloads Watch this on-demand webinar to learn how to simply scale any AI or Python workload using Ray, the fastest growing unified compute framework for scaling machine learning workloads. Learn how users are using Ray to build, manage and deploy scalable ML workloads. Watch Now Already using open source Ray? The Anyscale Platform offers several key advantages over Ray open source and provides a seamless user experience for developers and AI teams to speed development, improve developer productivity and productionize AI/ ML workloads at scale including large data sets. The result is faster time-to-market and faster iterations across the entire AI lifecycle. Get started on your existing workloads to Anyscale with no code changes. Experience the magic of infinite scale at your fingertips. Why Anyscale vs Ray © Anyscale, Inc 2022 Follow Anyscale Follow Ray Products Anyscale Compute Platform Ray Open Source Events Webinars Meetups Summits Company About Us News Careers Community Learn Blog Demos & Webinars Anyscale Academy Anyscale Docs Scalable AI and Python Data Ingestion Reinforcement Learning Ray AIR Model Serving Hyperparameter Tuning Use Cases Demand Forecasting/Pricing Industrial Automation Scalable ML Platforms NLP Recommendation System Are you passionate about Ray, scalable AI and distributed computing? Join us at Ray Summit - Early Bird rates end on 6/30. Find out more! Products Solutions Ecosystem Success Stories Learn Company Try It Now Scale AI and Python Applications Effortlessly Ray is an open source unified compute framework for scaling ML and Python workloads. With Ray, training, tuning and serving many models or massive models is reduced to minutes. Learn more about Ray, and the Anyscale Platform, an enterprise-ready managed Ray platform. Request a Trial Live Event Passionate about Ray, scalable AI, LLM and distributed computing? Then join us at Ray Summit – Early Bird rates thru 6/30. Spotlight Announcing Aviary from Anyscale. Quickly select and deploy LLMs for your AI applications. Learn Building an LLM open source search engine in 100 lines using LangChain and Ray Breathtaking Scale and Speed Instacart trains thousands of demand forecasting models 12x faster. How Netflix Scales ML Workloads and Speeds AI Innovation on Ray Open Source Engineer Netflix Nestlé trains 30,000 forecasting and churn models in under 6 minutes. How Meta Scales Distributed Training of AI Workloads on Ray Staff Applied AI Engineer Meta Dow Chemical accelerates their production scheduling optimization by 10x using Ray. How KocDigital Scales AI and Simplifies AI Development and Ops on Ray Director of Data and Analytics KocDigital Uber speeds model tuning by 2x-6x for HPO workloads. How Amazon Scales Improves Cost and Performance by 90% on Ray Principal Engineer Amazon Organizations Using Ray Why everyone is turning to Ray Companies are using Ray to scale ML and Python workloads including everything from data ingest, to preprocessing, hyperparameter tuning, training, and model serving at scale. Easy Scaling Scale from a laptop to thousands of servers Develop and scale in production, with zero code changes A Unified Framework Supports all workloads - data loading, training, tuning, reinforcement learning, model serving Develop, test, and productionize - in one framework Open Platform Integrate with the ML ecosystem, any ML library, data platform & workflow orchestrators Run on any cloud, Kubernetes or on a laptop Accelerated Development Speed development, testing, iterations and instantly scale in production Move faster from development to scaling in production with no re-coding The enterprise-ready, fully managed Anyscale Platform Companies are using Ray to scale ML and Python workloads including everything from data ingest, to preprocessing, hyperparameter tuning, training, and model serving at scale. Orchestration Experiment management Hyperparameter Tuning Training Data / features Serving / Applications Explainability / Observability Any cloud Learn More Why Anyscale vs. Ray One Unified Scalable Framework Effortlessly scale all workloads from data loading to training to hyperparamer tuning, to reinforcement learning and model serving. Learn more about all capabilities and the Ray AI Runtime (AIR). Organizations globally are using Ray and Anyscale for diverse solutions from recommendation systems, to supply-chain logistics optimization to pricing optimization, virtual environment simulations, and more. Data Loading Scalable Training/ Deep Learning Hyperparameter Tuning Reinforcement Learning Model Serving Ray AIR What Users are Saying About Ray and Anyscale See All At OpenAI, we are tackling some of the world's most complex and demanding computational problems. Ray powers our solutions to the thorniest of these problems and allows us to iterate at scale much faster than we could before. As an example, we use Ray to train our largest models, including ChatGPT. Greg Brockman Co-founder, Chairman, and President, OpenAI Story Ray and Anyscale empower even the leanest teams to bring AI to production and realize the business potential of AI in record time. Laure Fouilloux Head of Data Intelligence, Ricardo Story We chose Ray as the unified compute backend for our machine learning and deep learning platform because it has allowed us to significantly improve performance and fault tolerance, while also reducing the complexity of our technology stack. Ray has brought significant value to our business. Xu Ning Senior Manager, Uber AI Platform Story Being able to operate quickly at this massive scale has enabled us to deliver novel solutions towards Dendra Systems' mission of scaling ecosystem restoration of our biodiverse natural world. Shuning Bian Chief Architect, Dendra Systems Story Ray and Anyscale have enabled us to quickly develop, test and deploy a new in-game offer recommendation engine based on reinforcement learning, and subsequently serve those offers 3X faster in production. This resulted in revenue lift and a better gaming experience. Emiliano Castro Principal Data Scientist Story Anyscale is a fully managed scalable Ray compute platform that provides the easiest way to develop, deploy and manage Ray applications. Get Started © Anyscale, Inc 2022 Follow Anyscale Follow Ray Products Anyscale Compute Platform Ray Open Source Events Webinars Meetups Summits Company About Us News Careers Community Learn Blog Demos & Webinars Anyscale Academy Anyscale Docs Scalable AI and Python Data Ingestion Reinforcement Learning Ray AIR Model Serving Hyperparameter Tuning Use Cases Demand Forecasting/Pricing Industrial Automation Scalable ML Platforms NLP Recommendation System