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Getting-started guide: Linked to AWS docs and did a tech writer review (#672)
* Getting-started guide: Linked to AWS docs and did a tech writer review. * Accepting review suggestion Co-Authored-By: sarahmaddox <sarahmaddox@users.noreply.github.com> * Accepting review suggestion Co-Authored-By: sarahmaddox <sarahmaddox@users.noreply.github.com> * Accepting review suggestion Co-Authored-By: sarahmaddox <sarahmaddox@users.noreply.github.com> * Accepting review suggestion Co-Authored-By: sarahmaddox <sarahmaddox@users.noreply.github.com> * Accepting review suggestion Co-Authored-By: sarahmaddox <sarahmaddox@users.noreply.github.com> * Accepting review changes
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content/docs/started/getting-started.md

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title = "Getting Started with Kubeflow"
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description = "Quickly get running with your ML Workflow"
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description = "Get your machine-learning workflow up and running on Kubeflow"
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weight = 1
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There are a variety of ways to install Kubeflow
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There are various ways to install Kubeflow. Choose one of the following options
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to suit your environment (cloud, on premises (on prem), or local):
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* GCP users should follow the [guide for deploying on GCP](/docs/gke/deploy/)
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* On prem users or users with an existing Kubernetes cluster should follow the [guide for deploying on kubernetes](/docs/started/getting-started-k8s/)
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* Users who want to run Kubernetes locally in a virtual machine can select one of the following options
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* To use Kubeflow on Google Cloud Platform (GCP) and Kubernetes Engine (GKE),
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follow the [GCP deployment guide](/docs/gke/deploy/).
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* To use Kubeflow on Amazon Web Services (AWS),
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follow the [AWS deployment guide](/docs/aws/deploy/).
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* If you have an existing Kubernetes cluster or want to use Kubeflow on prem,
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follow the [guide to deploying Kubeflow on
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Kubernetes](/docs/started/getting-started-k8s/).
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* If you want to run Kubernetes locally in a virtual machine (VM), choose one of
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the following options:
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* [MiniKF setup](/docs/started/getting-started-minikf/)
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* MiniKF is a fast and easy way to get started with Kubeflow.
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* It installs with just two commands and then you are up for
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experimentation, and for running complete Kubeflow Pipelines.
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experimentation, and for running complete Kubeflow Pipelines.
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* MiniKF runs on all major operating systems (Linux, macOS, Windows).
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* [Minikube setup](/docs/started/getting-started-minikube/)
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* Minikube leverages virtualization applications like [Virtual
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Box](https://www.virtualbox.org/) or [VMware
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Fusion](https://www.vmware.com/products/fusion.html) to host the virtual
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machine and provides a CLI that can be leveraged outside of the VM.
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* Minikube defines a fully baked ISO that contains a minimal operating
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system and kubernetes already installed.
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* Minikube uses virtualization applications like
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[VirtualBox](https://www.virtualbox.org/) or [VMware
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Fusion](https://www.vmware.com/products/fusion.html) to host the VM
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and provides a CLI that you can use outside the VM.
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* Minikube defines a fully-baked
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[ISO image](https://en.wikipedia.org/wiki/ISO_image) that contains a
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minimal operating system and Kubernetes already installed.
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* This option may be useful if you are just starting to learn and already
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have one of the virtualization applications already installed.
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have one of the virtualization applications installed.
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* [Microk8s setup](/docs/started/getting-started-multipass/)
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* The benefits of using [Microk8s](https://microk8s.io/) include:
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- Can be installed on any Linux system as a
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[snap](https://snapcraft.io/)
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- Strong isolation and update semantics - your single-node cluster
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will be updated within a short period after upstream Kubernetes
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releases.
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- GPU pass through built in - e.g. **microk8s.enable gpu**
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* If you are not on a Linux machine, or you want to use Kubeflow in a
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confined environment, then use
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[Multipass](https://github.com/CanonicalLtd/multipass) to launch a
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virtual machine. Benefits include:
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- Ubuntu [cloud-images](http://cloud-images.ubuntu.com/) already
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integrated.
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- Lightweight hypervisor using native operating system mechanisms
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(e.g. [Hypervisor
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Framework](https://developer.apple.com/documentation/hypervisor) on
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MacOS, [Hyper-V on Windows
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10](https://docs.microsoft.com/en-us/virtualization/hyper-v-on-windows/quick-start/enable-hyper-v),
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QEMU/KVM for linux)
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- Eliminates the need to install a separate virtualization
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application.
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- You can use cloud-init to customize the VM (as you might in a cloud)
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* [MicroK8s setup](/docs/started/getting-started-multipass/)
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* [MicroK8s](https://microk8s.io/) can provide the following benefits:
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- A small, fast, secure, single node Kubernetes installation that installs on any
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Linux system as a [snap](https://snapcraft.io/microk8s).
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- Strong isolation and update semantics - your cluster
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is updated within a short period after upstream Kubernetes
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releases.
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- Built-in support to enable an installed GPU:
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`microk8s.enable gpu`
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* MicroK8s requires Linux. If you are not on a Linux machine, or you want
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to confine your Kubeflow to a disposable machine, the installation guide
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show you how to use
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[Multipass](https://github.com/CanonicalLtd/multipass) to launch a VM.
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Benefits include:
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- [Ubuntu Cloud Images](http://cloud-images.ubuntu.com/) already
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integrated.
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- Lightweight hypervisor using native operating system mechanisms
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(for example, [Hypervisor
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Framework](https://developer.apple.com/documentation/hypervisor) on
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macOS, [Hyper-V on Windows
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10](https://docs.microsoft.com/en-us/virtualization/hyper-v-on-windows/quick-start/enable-hyper-v), or
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QEMU/KVM for Linux).
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- No need to install a separate virtualization application.
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- Use of `cloud-init` to customize the VM.
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## Troubleshooting
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For detailed troubleshooting instructions, please refer to the [troubleshooting
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guide](/docs/other-guides/troubleshooting/).
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See the [Kubeflow troubleshooting guide](/docs/other-guides/troubleshooting/).
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## Resources
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* The [documentation](/docs/) provides in-depth instructions for using Kubeflow
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* The [documentation](/docs/) provides in-depth instructions for using Kubeflow.
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* Self-paced scenarios for learning and trying out Kubeflow:
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* [Codelabs](https://codelabs.developers.google.com/?cat=tensorflow)
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* [Introduction to Kubeflow on Google Kubernetes

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