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Jiao Dong

Shreyas Krishnaswamy

Simon Mo

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Edward Oakes

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Multi-model composition with Ray Serve deployment graphs

Chandler Gibbons

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Deploying XGBoost models with Ray Serve

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Serving PyTorch models with FastAPI and Ray Serve

Leonnardo Rabello

Lucas Machado

The live traffic pattern is variable and predictable. Serve’s replica autoscaling drives the cost down further during idle time.

Cheaper and 3X Faster Parallel Model Inference with Ray Serve

Michael Galarnyk

In this post, we explore the 4 common patterns of ML in production and how to implement these patterns using Ray Serve.


Where Ray Serve Fits In

Serving ML Models in Production: Common Patterns

The Ray Summit 2025 CfP is now open for submissions. The premier AI conference will be held November 3-5 in San Francisco, and the due date for CfPs is June 30th, 2025.  

Ray Summit 2025 CFP Open

Ray Summit 2025: Call for Proposals Closes on June 30th, 2025

Google + Anyscale

Google Cloud Integrates Anyscale's RayTurbo with GKE

Simplifying AI Development at Scale: Google Cloud Integrates Anyscale's RayTurbo with GKE

At Ray Summit 2024, we brought together AI experts and practitioners to dive into the future of distributed AI and scalable machine learning.

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Ray Summit 2024: Breaking Through the AI Complexity Wall

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Anyscale is the leading AI application platform. With Anyscale, developers can build, run and scale AI applications instantly.

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