Install Kubeflow anywhere

Create and train machine learning models on your laptop, in your data centre, or in the cloud.

Install Kubernetes

How to deploy Kubeflow

If you already have Ubuntu or another Linux, the following instructions are all you need. However, if you are on Windows or Mac, consider using to easily create an Ubuntu VM to work with.

For a more detailed guide, consider following the Deploy Kubeflow on Ubuntu, Windows and macOS tutorial.

The following step assumes you want to install as your Kubernetes cluster.

  1. Requirements

    In order to install kubeflow you will need an Ubuntu machine with 16Gb of RAM and 50Gb of free disk.

  2. Install MicroK8s

    MicroK8s can be installed with one command.

    You can enable features on your Kubernetes cluster with the following commands:

    If you have a GPU, run (optional):

  3. Enable Kubeflow

    Run the following command to enable Kubeflow.

    This will take a few minutes.

  4. Access Kubeflow dashboard

    After installing kubeflow, an IP address and credentials will be prompted on your terminal.

    If you installed Microk8s on your local host, you simply need to access the IP address provided on your browser: https://[kubeflow dashboard IP].

  5. Next Steps

    To get more information on this install process, including screenshots of the process, please visit the Deploy Kubeflow on Ubuntu, Windows and macOS.

    More recommended reading:

    • - the main Kubeflow website
    • - several examples to help you get started with leveraging Kubeflow
    • - use or create standard workflows for your models, automating tasks from training to production
    • - interact with Kubeflow through Python code
    • - open source library to help you develop and train ML models
    • - high-performance benchmarks

    For tailored Enterprise training and assistance, please consider our AI Consulting and Delivery services.

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