Anyscale Managed Ray Platform

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Anyscale, by the creators of Ray, is an end-to-end platform to build, deploy, and scale AI and Gen AI applications. Trusted by industry giants like OpenAI, Uber, and Netflix, Ray defines the standard for AI infrastructure. Anyscale builds on the foundation of Ray, enhancing it with developer tooling, an optimized runtime, and managed services that bolster performance, reliability, efficiency, and scale while speeding up development and productivity.

Anyscale integrates effortlessly with major ML libraries and tools, offering an AI Compute platform that dynamically orchestrates cloud resources for unmatched scale, reliability, and performance at sustainable costs, empowering enterprises to lead in the ever-accelerating AI revolution.

High-Performance Machine: -Anyscale offers a fast, cost-effective, efficient, reliable, and scalable solution for running AI workloads.

Leading Performance and Cost -Run production AI workloads on spot instances and lower costs by as much as 50% -<1 minute node startup times and <10s model download -Fully customizable LLM inferencing with support for latency / throughput optimization with built-in LoRA Swapping and model multiplexing -Deliver up to 100% resource utilization from optimized resource management with fractional resources, instance compaction, and priority scheduling and queueing -Reliability and Availability -Built in high availability and fault tolerance -Access compute and GPUs from across availability zones -Zero downtime upgrades, observability, and alerting -Scale -Run 1,000s of concurrent AI workloads -Deploy clusters with >10,000 nodes -Perform data processing at exabyte scale

All-in-One Compute Platform: -Anyscale powers the entire lifecycle for any traditional AI/ML application (data prep, training, inference, fine-tuning, deployment and serving) as well as Gen AI applications (embeddings, inference, fine-tuning, RAG, Stable Diffusion).

Powerful libraries: -Ray Data, Ray Train, Ray Tune, Ray Serve, and RLLib -Prebuilt App Accelerators for Gen AI and traditional AI use cases speed up development for any workload from a single platform -Integrations with the ML Ecosystem to build a best of breed AI Compute Platform including: --Data sources: Snowflake, Databricks, MongoDB, S3, GCP, and more --ML Ops: W&B, MLFlow, Sagemaker, Vertex --DevOps: Prefect, Airflow, Github, Datadog, and more UI: --Streamlit and Gradio -Developer Tooling

Anyscale Workspaces: Anyscale abstracts away the complexity of distributed systems through powerful, cutting-edge pythonic APIs and a fully managed experience to help developers get to production with total ease.

Workspaces provides an integrated IDE experience to develop on a scalable cluster just like you would on your laptop.

Use the tools you know and already love. Anyscale provides integrations 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.

A unified environment for development and production. 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 the Ray runtime environments for faster iteration.

Enterprise Ready: Anyscale is designed to meet the data, security and compute patterns of your company. Start quickly with our fully-managed, fully-hosted platform. Scale on our cloud or your own.

Security and Access Control: -Centrally manage users, projects, and clouds with the Anyscale control plane. -Audit logging -SOC 2 Type II compliance -Cost tracking: Keep tabs on the costs tied to jobs, clusters, and users in a single intuitive UI. -Deployment options: bring your own cloud with private networking, use Anyscale provided compute and GPUs, or even hybrid deployments with on-premise compute -Observability: Centrally monitor the health of your AI workloads and resources.

Anyscale provides a production-grade monitoring and observability stack. Integrations enable teams to send logs and metrics to existing observability stacks. Compute Management: Auto-suspend features built-in to reduce idle time and unexpected costs, complete control over compute resources and scaling behavior Automate jobs and cluster management or integrate into your CI/CD pipelines with simple, intuitive APIs and SDKs.