Kubeflow
MLOps & Infrastructure
Overview
Kubeflow is an open-source Kubernetes-native ML platform that provides pipelines for orchestrating ML workflows, distributed training, model serving, and notebook environments. It supports TensorFlow, PyTorch, and other frameworks, and is designed for teams running ML workloads on Kubernetes. Kubeflow offers components for hyperparameter tuning, metadata tracking, and multi-framework distributed training.
- Pricing model
- Free
- Deployment
- Self-hosted / on-premises
- Regions served
- Global
- Categories
- Free, MLOps & Infrastructure, Software & technology, Workflow orchestration, Self-hosted / on-premises, MLOps & model tooling, Predictive / classical ML
- Last updated
- 2 October 2026
- Published
- 2 October 2026
Use cases
Deployment options
Data sources & provenance
Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.
- Data quality
- Data quality: Editorially Reviewed
- Primary source
- kubeflow.org
- Sources cited
- 2
- Last reviewed
- 28 September 2026
- Last updated
- 2 October 2026
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