+++
title = "Getting Started with Kubeflow"
description = "Get your machine-learning workflow up and running on Kubeflow"
weight = 1
+++

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](/docs/gke/deploy/).
* To use Kubeflow on Amazon Web Services (AWS),
  follow the [AWS deployment guide](/docs/aws/deploy/).
* If you have an existing Kubernetes cluster or want to use Kubeflow on prem,
  follow the [guide to deploying Kubeflow on 
  Kubernetes](/docs/started/getting-started-k8s/).
* If you want to run Kubernetes locally in a virtual machine (VM), choose one of 
  the following options:

   * [MiniKF setup](/docs/started/getting-started-minikf/)
      * 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](/docs/started/getting-started-minikube/)
      * Minikube uses virtualization applications like 
        [VirtualBox](https://www.virtualbox.org/) or [VMware
        Fusion](https://www.vmware.com/products/fusion.html) to host the VM
	      and provides a CLI that you can use outside the VM.
      * Minikube defines a fully-baked
       [ISO image](https://en.wikipedia.org/wiki/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](/docs/started/getting-started-multipass/)
      * [MicroK8s](https://microk8s.io/) can provide the following benefits:
          - A small, fast, secure, single node Kubernetes installation that installs on any
            Linux system as a [snap](https://snapcraft.io/microk8s).
          - 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](https://github.com/CanonicalLtd/multipass) to launch a VM.
        Benefits include:
          - [Ubuntu Cloud Images](http://cloud-images.ubuntu.com/) already
            integrated.
          - Lightweight hypervisor using native operating system mechanisms
            (for example, [Hypervisor
            Framework](https://developer.apple.com/documentation/hypervisor) on
            macOS, [Hyper-V on Windows
            10](https://docs.microsoft.com/en-us/virtualization/hyper-v-on-windows/quick-start/enable-hyper-v), or
            QEMU/KVM for Linux).
          - No need to install a separate virtualization application.
          - Use of `cloud-init` to customize the VM.
    
## Troubleshooting

See the [Kubeflow troubleshooting guide](/docs/other-guides/troubleshooting/).

## Resources

* The [documentation](/docs/) provides in-depth instructions for using Kubeflow.
* Self-paced scenarios for learning and trying out Kubeflow:
  * [Codelabs](https://codelabs.developers.google.com/?cat=tensorflow)
      * [Introduction to Kubeflow on Google Kubernetes
        Engine](https://codelabs.developers.google.com/codelabs/kubeflow-introduction/index.html)
      * [Kubeflow End to End: GitHub Issue
        Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-e2e-gis/index.html)
      * [Kubeflow Pipelines: GitHub Issue
        Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-pipelines-gis/index.html)
  * [Katacoda](https://www.katacoda.com/kubeflow)
      * [Deploying GitHub Issue Summarization with
        Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-github-issue-summarization)
      * [Deploying
        Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow)
      * [Deploying Kubeflow with
        Ksonnet](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow-with-ksonnet)
      * [Deploying Pytorch with
        Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploy-pytorch-with-kubeflow)
  * [Qwiklabs](https://qwiklabs.com/catalog?keywords=kubeflow)
      * [Introduction to Kubeflow on Google Kubernetes
        Engine](https://qwiklabs.com/focuses/960?locale=en&parent=catalog)
      * [Kubeflow End to End: GitHub Issue
        Summarization](https://qwiklabs.com/focuses/1257?locale=en&parent=catalog)