A software engineer and technical lead in the areas of machine learning and big data. Open source enthusiast, passionate about music production, photography and sourdough.
November 17, 2020 04:00 PM PT
MLflow serving is a great way to deploy any model as a rest API endpoint and start experimenting. But what about taking it to the next level? What if we want to deploy our application to production just like any other server in a containerized environment? What about adding custom middlewares, monitoring, logging and tweaking performance for high scale?
In this talk I will cover what we did in Yotpo in order to make MLflow serving production-grade!
Speaker: Ron Barabash