Kubeflow is a novel open source tool for Machine Learning workflow orchestration on Kubernetes. It has great powers, but deploying it may not be so easy, depending on how and where you deploy your Kubernetes.
This tutorial will show you an easy way to deploy Kubeflow using MicroK8s, a lightweight version of Kubernetes, in a few simple steps.
What you’ll learn
- How to deploy MicroK8s on Ubuntu, Windows or MacOS
- How to deploy Kubeflow on top of MicroK8s
- How to access your Kubeflow dashboard
What you’ll need
- Desktop or Virtual Machine with Ubuntu (16.04 LTS or above), Windows or MacOS
- A minimum of 4 CPU, 16GB RAM, 50GB Disk (recommended 8 CPU, 32GB RAM, 60GB Disk)
- Hyper V, if using Multipass on a Windows machine (not available on Windows 10 Home)
- Some basic command-line knowledge