deployKF is a next-generation machine learning toolkit for Kubernetes which effortlessly integrates Kubeflow and other leading ML/AI tools.
Crafted with ❤️ by the developers of Kubeflow.
deployKF is the best way to build reliable ML Platforms on Kubernetes.
- deployKF supports leading MLOps & Data tools from both Kubeflow, and other projects
- deployKF has a Helm-like interface, with values for configuring all aspects of the deployment (no need to edit Kubernetes YAML)
- deployKF does NOT install resources directly in your cluster, instead it generates ArgoCD Applications to provide native GitOps support
Currently, deployKF supports MLOps tools from the Kubeflow ecosystem like Kubeflow Pipelines and Kubeflow Notebooks. We are actively adding support for other popular tools such as MLFlow (Model Registry), Apache Airflow, and Feast.
For more information, please see supported tools and future tools!
deployKF was originally created by Mathew Wicks (GitHub: @thesuperzapper), a Kubeflow lead and maintainer of the popular Apache Airflow Helm Chart. However, deployKF is now a community-led project that welcomes contributions from anyone who wants to help.
The creator of deployKF (Mathew Wicks), operates a US-based MLOps company called Aranui Solutions that provides commercial support and consulting for deployKF.
Connect on LinkedIn or email [email protected] to learn more!
deployKF is a new project, and we are still building our community.
Please consider adding your organization to our list of adopters.
Kubeflow and deployKF are two different but related projects:
- deployKF is a tool for deploying Kubeflow and other MLOps tools on Kubernetes as a cohesive platform.
- Kubeflow is a project that develops MLOps tools, including Kubeflow Pipelines, Kubeflow Notebooks, Katib, and more.
For more details, see our detailed deployKF vs Kubeflow comparison.
Yes! For more information please see our community page.
