This session shows how to manage both ML and app workflows using Google Cloud tools like Vertex AI, Cloud Build, Artifact Registry, and GKE. You'll see how to automate model training, testing, and deployment alongside application code in a single, unified DevOps pipeline. We'll walk through practical challenges like handling dependencies, model versioning, and rollbacks—plus how to monitor it all. Real examples, no fluff—just what works when running ML and DevOps together in production.