run-house/kubetorch
Distribute and run AI workloads on Kubernetes magically in Python, like PyTorch for ML infra.
This tool helps machine learning engineers and data scientists efficiently build and deploy AI applications on Kubernetes. You write your ML code in Python locally, and it runs remotely on your cluster, providing faster iteration and real-time feedback. It's for anyone managing ML infrastructure who wants to streamline their development workflow and reduce compute costs.
1,172 stars. Actively maintained with 2 commits in the last 30 days. Available on PyPI.
Use this if you are a machine learning engineer or data scientist who needs to run complex ML models and distributed training efficiently on Kubernetes.
Not ideal if you don't use Kubernetes for your machine learning infrastructure or if your workloads are small and do not require distributed computing.
Stars
1,172
Forks
53
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 12, 2026
Commits (30d)
2
Dependencies
6
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/mlops/run-house/kubetorch"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related tools
skypilot-org/skypilot
Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage...
dstackai/dstack
dstack is an open-source control plane for running development, training, and inference jobs on...
ray-project/kuberay
A toolkit to run Ray applications on Kubernetes
kubeflow/kale
Kubeflow’s superfood for Data Scientists
volcano-sh/volcano
A Cloud Native Batch System (Project under CNCF)