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Kubeflow is an open source machine learning platform that runs on Kubernetes, providing tools for the complete ML lifecycle from development to deployment. This guide is for cluster administrators and ML platform engineers who want to run Kubeflow on a CoreWeave Kubernetes Service (CKS) cluster to support end-to-end ML workflows, from experimentation through deployment. This guide shows you how to set up Kubeflow on CKS by covering the following:
  • Configure your cluster for Kubeflow compatibility.
  • Install certificate management components.
  • Deploy Kubeflow with the default OSS manifests.
  • Access the Kubeflow dashboard.

Prerequisites

Before you install Kubeflow, ensure you have the following:
  • A Kubernetes cluster on CoreWeave accessible with kubectl.
  • kustomize installed and configured to work with your cluster.

Setup

  1. Clone the Kubeflow manifests repository and navigate to it by running the following commands:
  2. Edit the Cilium config to handle Kubeflow’s service traffic in a way that’s compatible with CKS networking:
    Add the following value, then save and exit:
    For example, the cilium-config file section should look similar to this:
    Apply the changes:
    Note: Disregard deprecation warnings.
  3. Install cert-manager and the cert-issuer so Kubeflow components can request and manage the TLS certificates they require:
  4. Install Kubeflow with the OSS default manifests. The loop retries the apply until all resources are accepted, because some custom resources depend on CRDs that are still being registered:
After completing these steps, you have a Kubeflow installation running on your CKS cluster, with cert-manager configured and the default Kubeflow components deployed.

Use Kubeflow

After you install Kubeflow, you can access the dashboard and other components. The default namespace for Kubeflow is kubeflow. To start using Kubeflow, port-forward the main dashboard service:
To view the Kubeflow dashboard, go to http://localhost:8080. The default credentials are used for basic authentication. Access the dashboard with the following credentials: User: user@example.com Password: 12341234
Last modified on June 10, 2026