How to: Install with a Single Command
#### Prerequisites
- 16 GB of RAM recommended.
- 8 CPU cores recommended.
- `kind` version 0.27+.
- `docker` or a more modern tool such as `podman` to run the OCI images for the Kind cluster.
- Linux kernel subsystem changes to support many pods:
    - `sudo sysctl fs.inotify.max_user_instances=2280`
    - `sudo sysctl fs.inotify.max_user_watches=1255360`
- You can exclude components from the `example/kustomization.yaml` to fit Kubeflow into 4-8 GB of memory and 2-4 CPU cores.

#### Create Kind Cluster
```sh
cat <
/tmp/kubeflow-config
export KUBECONFIG=/tmp/kubeflow-config
```

#### Create a Secret Based on Existing Credentials to Pull the Images
```sh
docker login

kubectl create secret generic regcred \
    --from-file=.dockerconfigjson=$HOME/.docker/config.json \
    --type=kubernetes.io/dockerconfigjson
```

You can install all Kubeflow official components (residing under `applications`) and all common services (residing under `common`) using the following command:

```sh
while ! kustomize build example | kubectl apply --server-side --force-conflicts -f -; do echo "Retrying to apply resources"; sleep 20; done
```

Once everything is installed successfully, you can access the Kubeflow Central Dashboard [by logging in to your cluster](#connect-to-your-kubeflow-cluster).

Congratulations! You can now start experimenting and running your end-to-end ML workflows with Kubeflow.