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mlx-install-with-kubeflow.md

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Install Kfctl

Note: kfctl is currently available for Linux and macOS users only. If you use Windows, you can install kfctl on Windows Subsystem for Linux (WSL). Refer to the official instructions for setting up WSL.

Run the following commands to set up and deploy Kubeflow:

  1. Download the latest kfctl {{% kf-latest-version %}} release from the [Kubeflow releases page](https://github.com/kubeflow/kfctl/releases/tag/{{% kf-latest-version %}}).

Note: You're strongly recommended to install kfctl v1.2 or above because kfctl v1.2 addresses several critical bugs that can break the Kubeflow deployment.

  1. Extract the archived TAR file:

    tar -xvf kfctl_{{% kf-latest-version %}}_<platform>.tar.gz

  2. Make kfctl binary easier to use (optional). If you don’t add the binary to your path, you must use the full path to the kfctl binary each time you run it.

    export PATH=$PATH:<path to where kfctl was unpacked>

Deploy MLX

  1. Now you can apply MLX KfDef custom resource on Kubernetes to deploy MLX.

  2. For IKS / Minikube use the following KFDEF

    export KFDEF_URL=https://raw.githubusercontent.com/machine-learning-exchange/manifests/mlx/kfdef/kfctl_ibm_tekton.yaml

    OR

    For Openshift we need to set the proper scc. Use the following KFDEF

    export KFDEF_URL=https://raw.githubusercontent.com/machine-learning-exchange/manifests/mlx/kfdef/kfctl_mlx_openshift_tekton.yaml

  3. Download the KFDEF to local:

    export KFDEF=$(echo "${KFDEF_URL}" | rev | cut -d/ -f1 | rev)
curl -L ${KFDEF_URL} > ${KFDEF}

  4. Use kfctl to deploy MLX

    kfctl apply -V -f ${KFDEF}

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