About Kubeflow
An open-source Kubernetes-native platform that provides composable tools for ML workloads including notebooks, pipelines, training operators, hyperparameter tuning, and model serving.
Key Features
- Kubeflow Pipelines — author and deploy portable, scalable ML workflows on Kubernetes.
- Notebooks & training — run web-based notebooks and Kubernetes-native training operators.
- AutoML & tuning — Katib for hyperparameter tuning and early stopping.
- Model serving & registry — KServe and model registry components for production serving.
Use Cases & Best For
Platform and infrastructure teams building Kubernetes-native ML platforms.
Organizations that need modular, scalable ML tooling integrated with Kubernetes.
About MLOps & Monitoring
Model operations and lifecycle management