mirror of https://github.com/kubeflow/website.git
91 lines
4.8 KiB
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91 lines
4.8 KiB
Markdown
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title = "Getting Started with Kubeflow"
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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 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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* 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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* 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 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 installed.
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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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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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* 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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Engine](https://codelabs.developers.google.com/codelabs/kubeflow-introduction/index.html)
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* [Kubeflow End to End: GitHub Issue
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Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-e2e-gis/index.html)
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* [Kubeflow Pipelines: GitHub Issue
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Summarization](https://codelabs.developers.google.com/codelabs/cloud-kubeflow-pipelines-gis/index.html)
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* [Katacoda](https://www.katacoda.com/kubeflow)
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* [Deploying GitHub Issue Summarization with
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Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-github-issue-summarization)
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* [Deploying
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Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow)
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* [Deploying Kubeflow with
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Ksonnet](https://www.katacoda.com/kubeflow/scenarios/deploying-kubeflow-with-ksonnet)
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* [Deploying Pytorch with
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Kubeflow](https://www.katacoda.com/kubeflow/scenarios/deploy-pytorch-with-kubeflow)
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* [Qwiklabs](https://qwiklabs.com/catalog?keywords=kubeflow)
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* [Introduction to Kubeflow on Google Kubernetes
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Engine](https://qwiklabs.com/focuses/960?locale=en&parent=catalog)
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* [Kubeflow End to End: GitHub Issue
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Summarization](https://qwiklabs.com/focuses/1257?locale=en&parent=catalog)
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