Multi-Model Composition with Ray Serve Deployment Graphs
Offered By: Anyscale via YouTube
Course Description
Overview
Explore multi-model composition using Ray Serve deployment graphs in this 30-minute talk from Anyscale. Discover how to leverage Ray's programmable and general-purpose distributed computing capabilities to author, orchestrate, scale, and deploy complex serving graphs as a DAG under a unified set of APIs. Learn to program multiple models dynamically on your laptop as if writing a local Python script, deploy to production at scale, and perform individual upgrades. Gain insights into streamlining microservice-like functionality for efficient model deployment and management.
Syllabus
Multi-model composition with Ray Serve deployment graphs
Taught by
Anyscale
Related Courses
Patterns of ML Models in ProductionPyCon US via YouTube Deploying Many Models Efficiently with Ray Serve
Anyscale via YouTube Modernizing DoorDash Model Serving Platform with Ray Serve
Anyscale via YouTube Ray for Large-Scale Time-Series Energy Forecasting to Plan a More Resilient Power Grid
Anyscale via YouTube Enabling Cost-Efficient LLM Serving with Ray Serve
Anyscale via YouTube