Kubeflow MLOps tutorial: from notebook development to production inference
In this video, our engineering team takes you through a full end-to-end Kubeflow implementation, step by step – from data exploration to production inference. Follow the journey of a house price prediction use case and see how modern MLOps components work together: Kubeflow architectures and starter repositories Notebook-based development workflows Data exploration and model development MLflow for experiment tracking Katib for hyperparameter optimization Kubeflow Pipelines for automated preprocessing and training KServe for scalable model inference.