Kubeflow 1.9: New Tools for Model Management and Training Optimization

Jul 22, 2024 • Kubeflow 1. 9 Release Team, Stefano Fioravanzo • 11 min read release Kubeflow 1. 9 significantly simplifies the development, tuning and management of secure machine learning models and LLMs. Highlights include: These updates aim to simplify workflows, improve integration dependencies, and provide Kubernetes-native operational efficiencies for enterprise scale, security, and isolation. A model registry provides a central catalog for ML model developers to index and manage models, versions, and ML artifacts metadata. It fills a gap between model experimentation and production activities. It provides a central interface for all stakeholders in the ML lifecycle to collaborate on ML models. Model registry has been asked by the community for a long time and we are delighted to introduce it to the Kubeflow ecosystem. This initial release includes REST APIs and a Python SDK to track model artifacts and model metadata with a standardized format that can be reused across Kubeflow components, such as to deploy Inference Servers. You can get started by following the Model Registry tutorial on the Kubeflow website , or see a short demo video of the Model Registry in action. We are just getting started. This is an Alpha version and we look forward to feedback.