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mlx-install-with-kubeflow.md

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MLX Deployment on Kubernetes or OpenShift (Asset Catalog and Execution Engine)

Prerequisites

  • An existing Kubernetes cluster. Version 1.17+
  • The minimum recommended capacity requirement for MLX is 8 vCPUs and 16GB RAM
  • If you are using IBM Cloud, follow the appropriate instructions for standing up your Kubernetes cluster using the IBM Cloud Kubernetes Service
  • If you are using OpenShift on IBM Cloud, please follow the instructions for standing up your IBM Cloud Red Hat OpenShift cluster
  • kustomize v3.2.0 is installed
    • Kustomize v3.2.0 quick install:
    OS=$(uname) 
    curl -L https://github.com/kubernetes-sigs/kustomize/releases/download/v3.2.0/kustomize_3.2.0_${OS}_amd64 --output kustomize
    chmod +x kustomize
    mv kustomize /usr/local/bin
    

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 release from the Kubeflow releases page.

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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