This document will outline steps that will get your local installation of Kubeflow running on top of Microk8s inside of a native Hypervisor. Multipass is used to create a the native VM. Microk8s is used to provide a simple, single-node Kubernetes cluster.
By the end of this document, you’ll have a local installation of a Kubernetes cluster along with all the default core components of Kubeflow deployed as services in the pods. You should be able to access JupyterHub notebooks, and the Kubeflow Dashboard.
If you do not already have a multipass installed, install a new one.
Install Multipass using the native Mac OS installer.
It can be installed with the following command on any snap-enabled linux:
$ sudo snap install multipass --beta --classic
This cloud-init file can be used repeatedly, each time a new multipass VM is created
wget https://bit.ly/2tOfMUA -O kubeflow.init
You can mount a local volume into the VM. The second command adds the local directory.
$ multipass launch bionic -n kubeflow -m 8G -d 40G -c 4 --cloud-init kubeflow.init $ multipass mount . kubeflow:/multipass
Note: These are the minimum recommended settings on the VM created by Multipass for the Kubeflow deployment. You are free to adjust them higher based on your host machine capabilities and workload requirements.
Log into the VM and install some basic supporting tools. This will install kubernetes, powered by microk8s, and other tools necessary to deploy Kubeflow
multipass shell kubeflow # log into vm sudo /kubeflow/install-kubeflow-pre-micro.sh # install microk8s, etc.
This step assumes you’ve stored your github token in a file in the host machine. If you
haven’t already done this, please put:
export GITHUB_TOKEN=<your token> into /multipass/github-token.txt
source /multipass/github-token.txt # exports your github token /kubeflow/install-kubeflow.sh # waits until all pods are “running”; prints the port
This script will print out the port number of JupyterHub.
You can get the IP address of the VM using
multipass list. Assuming you’ve used the same name (kubeflow) above, you can now access the JupyterHub page from your browser at http://
For JupyterHub, you’ll be landing on a login page.
If the page doesn’t refresh, please see troubleshooting.
Refer to the user guide