Getting Started with Kubeflow

Get your machine-learning workflow up and running on Kubeflow

There are various ways to install Kubeflow. Choose one of the following options to suit your environment (cloud, on premises (on prem), or local):

To use Kubeflow on Google Cloud Platform (GCP) and Kubernetes Engine (GKE), follow the GCP deployment guide.
To use Kubeflow on Amazon Web Services (AWS), follow the AWS deployment guide.
If you have an existing Kubernetes cluster or want to use Kubeflow on prem, follow the guide to deploying Kubeflow on Kubernetes.
If you want to run Kubernetes locally in a virtual machine (VM), choose one of the following options:
- MiniKF setup
  - MiniKF is a fast and easy way to get started with Kubeflow.
  - It installs with just two commands and then you are up for experimentation, and for running complete Kubeflow Pipelines.
  - MiniKF runs on all major operating systems (Linux, macOS, Windows).
- Minikube setup
  - Minikube uses virtualization applications like VirtualBox or VMware Fusion to host the VM and provides a CLI that you can use outside the VM.
  - Minikube defines a fully-baked ISO image that contains a minimal operating system and Kubernetes already installed.
  - This option may be useful if you are just starting to learn and already have one of the virtualization applications installed.
- MicroK8s setup
  - MicroK8s can provide the following benefits:
    - A small, fast, secure, single node Kubernetes installation that installs on any Linux system as a snap.
    - Strong isolation and update semantics - your cluster is updated within a short period after upstream Kubernetes releases.
    - Built-in support to enable an installed GPU: microk8s.enable gpu
  - MicroK8s requires Linux. If you are not on a Linux machine, or you want to confine your Kubeflow to a disposable machine, the installation guide show you how to use Multipass to launch a VM. Benefits include:
    - Ubuntu Cloud Images already integrated.
    - Lightweight hypervisor using native operating system mechanisms (for example, Hypervisor Framework on macOS, Hyper-V on Windows 10, or QEMU/KVM for Linux).
    - No need to install a separate virtualization application.
    - Use of cloud-init to customize the VM.