Kubeflow
Machine learning platform for Kubernetes that bundles pipelines, model training, hyperparameter tuning, and serving into one toolkit.
- Actively maintained
- Foundation-backed
- Well documented
- Permissive license
Overview
Kubeflow packages together the pieces a data science team needs to run ML workflows on Kubernetes - pipeline orchestration, distributed training jobs, hyperparameter tuning, model serving, and notebook environments - so a platform team doesn't have to assemble and integrate each piece separately. It's built specifically to bring ML workloads into the same Kubernetes infrastructure a team already operates.
Kubeflow is a fit for platform teams standardizing ML infrastructure on Kubernetes, a broader end-to-end MLOps platform than more focused tools like MLflow (also in this catalog), which handles experiment tracking and model management specifically.
Why it's in this catalog
Catalog rating: ★★★★☆ (4/5)
The standard Kubernetes-native ML pipeline platform, strong representative pick for MLOps.
- Mature
- Foundation-governed
- Categories
- AI & Machine Learning
- Languages
- Python, Go
- License
- Apache-2.0
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