Explore how to leverage Kubernetes as an orchestration layer for MLOps workflows powered by MLflow in this 25-minute conference talk from the Linux Foundation's Open Source Summit. Learn to combine the flexibility of cloud-native control with the modular capabilities of MLflow to build scalable, reproducible, and secure machine learning pipelines. Discover practical strategies for building a modern MLOps environment that balances autonomy with governance, covering everything from container management to experiment tracking and model deployment. Gain insights from real-world examples and field-tested best practices for implementing cloud-native MLOps processes that effectively integrate Kubernetes orchestration with MLflow's machine learning lifecycle management capabilities.