It’s Alive! Taming the MLOps Franken-Stack: Write, Run, and Serve with Michelangelo

Deep in enterprise infrastructure, platform engineers often play the mad scientist, stitching together disparate MLOps tools into a terrifying “Franken-stack”, a fragile ecosystem held together by custom code and vendor lock-in. Let’s move past these infrastructure headaches and look at how Uber open-sourced Michelangelo to bring architectural order to the chaos. This session reveals how the platform anchors a consistent developer experience across the entire ML lifecycle using its three core open-source pillars: Uniflow for pipeline orchestration, the native Job Controller for automated cluster execution, and the Model Serving layer for low-latency inference. Through a live demo, we’ll provide a blueprint to seamlessly swap out your underlying infrastructure components, like shifting compute or orchestrators, without breaking your Python workflow code. Finally, attendees will get an inside look at our local sandbox architecture, allowing developers to safely spin up, experiment with, and master this composable, cloud-native stack on their own hardware.