Ray Logo

June 22-24 | Virtual & Free

Ray Summit 2021

Scalable machine learning,
Scalable Python, for everyone


Ray Serve: Patterns of ML Models in Production

June 22, 12:25 PM - 12:55 PM

You trained a ML model, now what? The model needs to be deployed for online serving and offline processing. This talk walks through the journey of deploying your ML models in production. I will cover common deployment patterns backed by concrete use cases which are drawn from 100+ user interviews for Ray and Ray Serve. Lastly, I will cover how we built Ray Serve, a scalable model serving framework, from these learnings.


Simon Mo

Simon Mo

Software Engineer, Anyscale