Kubeflow
Open-source Kubernetes-native ML platform for deploying scalable machine learning workflows
Kubeflow
Open-source Kubernetes-native ML platform for deploying scalable machine learning workflows
Kubeflow is an open-source machine learning platform built on Kubernetes for deploying, monitoring, and managing ML workflows at scale. It provides components for experiment tracking, pipeline orchestration, model serving, hyperparameter tuning, and distributed training. Kubeflow pipelines enable data scientists to build reproducible, containerized ML workflows that run consistently from development to production. ML platform teams at technology companies and enterprises use Kubeflow to standardize and operationalize machine learning infrastructure on Kubernetes clusters. The platform runs on any cloud provider or on-premises Kubernetes deployment, making it a vendor-neutral choice for organizations wanting control over their ML infrastructure.
Key Features
- ✓Kubernetes-native
- ✓Pipeline orchestration
- ✓Distributed training
- ✓Model serving
- ✓Experiment tracking
Quick Info
- Category
- MLOps
- Pricing
- Free
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