This repository contains Kustomize manifests that point to the upstream manifest of each Kubeflow component and provides an easy way for people to change their deployment according to their need. ArgoCD application manifests for each componenet will be used to deploy Kubeflow. The intended usage is for people to fork this repository, make their desired kustomizations, run a script to change the ArgoCD application specs to point to their fork of this repository, and finally apply a master ArgoCD application that will deploy all other applications.

To run the below script yq version 4 must be installed

Overview of the steps:

• fork this repo
• modify the kustomizations for your purpose
• run ./setup_repo.sh <your_repo_fork_url>
• commit and push your changes
• run kubectl apply -f kubeflow.yaml

• argocd: Kustomize files for ArgoCD
• argocd-applications: ArgoCD application for each Kubeflow component
• cert-manager: Kustomize files for installing cert-manager v1.2
• kubeflow: Kustomize files for installing Kubeflow componenets
  • common/dex-istio: Kustomize files for Dex auth installation
  • common/oidc-authservice: Kustomize files for OIDC authservice
  • roles-namespaces: Kustomize files for Kubeflow namespace and ClusterRoles
  • user-namespace: Kustomize manifest to create the profile and namespace for the default Kubeflow user
  • katib: Kustomize files for installing Katib
  • kfserving: Kustomize files for installing KFServing
    • knative: Kustomize files for installing KNative
  • central-dashboard: Kustomize files for installing the Central Dashboard
  • jupyter-web-app: Kustomize files for installing the Jupyter Web App
    • notebook-controller: Kustomize files for installing the Notebook Controller
  • pod-defaults: Kustomize files for installing Pod Defaults (a.k.a. admission webhook)
  • profile-controller_access-management: Kustomize files for installing the Profile Controller and Access Management
  • tensorboards-web-app: Kustomize files for installing the Tensorboards Web App
    • tensorboard-controller: Kustomize files for installing the Tensorboard Controller
  • volumes-web-app: Kustomize files for installing the Volumes Web App
  • operators: Kustomize files for installing the various operators
  • pipelines: Kustomize files for installing Kubeflow Pipelines
• metallb: Kustomize files for installing MetalLB
• rook-ceph: Kustomize files for installing Rook Ceph with Block (default), Object and File storage

• kustomization.yaml: Kustomization file that references the ArgoCD application files in argocd-applications
• kubeflow.yaml: ArgoCD application that deploys the ArgoCD applications referenced in kustomization.yaml

• kubectl (latest)
• kustomize 4.0.5
• docker (if using kind)

curl -Lo ./kind https://kind.sigs.k8s.io/dl/v0.10.0/kind-linux-amd64
chmod +x ./kind
mv ./kind /<some-dir-in-your-PATH>/kind

Note - This will overwrite any existing ~/.kube/config file Please back up your current file if it already exists

kind create cluster --config kind/kind-cluster.yaml

kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.3.6/components.yaml
kubectl patch deployment metrics-server -n kube-system -p '{"spec":{"template":{"spec":{"containers":[{"name":"metrics-server","args":["--cert-dir=/tmp", "--secure-port=4443", "--kubelet-insecure-tls","--kubelet-preferred-address-types=InternalIP"]}]}}}}'

Edit the IP range in configmap.yaml so that it is within the range of your docker network. To get your docker network range, run the following command:

docker network inspect -f '{{.IPAM.Config}}' kind

After updating the metallb configmap, deploy it by running:

kustomize build metallb/ | kubectl apply -f -

Deploy Argo CD with the following commaind:

kustomize build argocd/ | kubectl apply -f -

Expose Argo CD with a LoadBalancer to access the UI by executing:

kubectl patch svc argocd-server -n argocd -p '{"spec": {"type": "LoadBalancer"}}'

Get the IP of the Argo CD endpoint:

kubectl get svc argocd-server -n argocd

Login with the username admin and the output of the following command as the password:

kubectl -n argocd get secret argocd-initial-admin-secret -o jsonpath="{.data.password}" | base64 -d

To deploy Kubeflow, execute the following command:

kubectl apply -f kubeflow.yaml

Note - This deploys all components of Kubeflow 1.3, it might take a while for everything to get started. Also, it is unknown what hardware specifications are needed for this at the current time, so your mileage may vary. Also, this deployment is using the manifests in this repository directly. For instructions how to customize the deployment and have Argo CD use those manifests see the next section.

Get the IP of the Kubeflow gateway with the following command:

kubectl get svc istio-ingressgateway -n istio-system

Login to Kubeflow with "email-address" user and password 12341234

Run: kind delete cluster

For this installation the HA version of ArgoCD is used. Due to Pod Tolerations, 3 nodes will be required for this installation. If you do not wish to use a HA installation of ArgoCD, edit this kustomization.yaml and remove /ha from the URI.

1. Next, to install ArgoCD execute the following command:

   kustomize build argocd/ | kubectl apply -f -

2. Install the ArgoCD CLI tool from https://github.com/argoproj/argo-cd/releases/latest

3. Access the ArgoCD UI by exposing it through a LoadBalander, Ingress or by port-fowarding using kubectl port-forward svc/argocd-server -n argocd 8080:443

4. Login to the ArgoCD CLI. First get the default password for the admin user: kubectl -n argocd get secret argocd-initial-admin-secret -o jsonpath="{.data.password}" | base64 -d

   Next, login with the following command: argocd login <ARGOCD_SERVER> # e.g. localhost:8080 or argocd.example.com

   Finally, update the account password with: argocd account update-password

5. You can now login to the ArgoCD UI with your new password. This UI will be handy to keep track of the created resources while deploying Kubeflow.

The purpose of this repository is to make it easy for people to customize their Kubeflow deployment and have it managed through a GitOps tool like ArgoCD. First, fork this repository and clone your fork locally. Next, apply any customization you require in the kustomize folders of the Kubeflow applications. Next will follow a set of recommended changes that we encourage everybody to make.

The default username, password and namespace of this deployment are: user, 12341234 and kubeflow-user respectively. To change these, edit the user and profile-name (the namespace for this user) in params.env.

Next, in configmap-path.yaml under staticPasswords, change the email, the hash and the username for your used account.

staticPasswords:
- email: user
  hash: $2y$12$4K/VkmDd1q1Orb3xAt82zu8gk7Ad6ReFR4LCP9UeYE90NLiN9Df72
  username: user

The hash is the bcrypt has of your password. You can generate this using https://passwordhashing.com/BCrypt, or with the command below:

python3 -c 'from passlib.hash import bcrypt; import getpass; print(bcrypt.using(rounds=12, ident="2y").hash(getpass.getpass()))'

By default the Istio Ingress Gateway is setup to use a LoadBalancer and to redirect HTTP traffic to HTTPS. Manifests for MetalLB are provided to make it easier for users to use a LoadBalancer Service. Edit the configmap.yaml and set a range of IP addresses MetalLB can use under data.config.address-pools.addresses. This must be in the same subnet as your cluster nodes.

If you do not wish to use a LoadBalancer, change the spec.type in gateway-service.yaml to NodePort.

To provide HTTPS out-of-the-box, the kubeflow-self-signing-issuer used by internal Kubeflow applications is setup to provide a certificate for the Istio Ingress Gateway.

To use a different certificate for the Ingress Gateway, change the spec.issuerRef.name to the cert-manager ClusterIssuer you would like to use in ingress-certificate.yaml and set the spec.commonName and spec.dnsNames[0] to your Kubeflow domain.

If you would like to use LetsEncrypt, a ClusterIssuer template if provided in letsencrypt-cluster-issuer.yaml. Edit this file according to your requirements and uncomment the line in the kustomization.yaml file so it is included in the deployment.

To customize the list of images presented in the Jupyter Web App and other related setting such as allowing custom images, edit the spawner_ui_config.yaml file.

To simplify the process of telling ArgoCD to use your fork of this repo, a script is provided that updates the spec.source.repoURL of all the ArgoCD application specs. Simply run:

./setup_repo.sh <your_repo_fork_url>

To change what Kubeflow or third-party componenets are included in the deployment, edit the root kustomization.yaml and comment or uncomment the components you do or don't want.

Next, commit your changes and push them to your repository.

Once you've commited and pushed your changes to your repository, you can either choose to deploy componenet individually or deploy them all at once. For example, to deploy a single component you can run:

kubectl apply -f argocd-applications/kubeflow-roles-namespaces.yaml

To deploy everything specified in the root kustomization.yaml, execute:

kubectl apply -f kubeflow.yaml

After this, you should start seeing applications being deployed in the ArgoCD UI and what the resources each application create.

By default, all the ArgoCD application specs included here are setup to automatically sync with the specified repoURL. If you would like to change something about your deployment, simply make the change, commit it and push it to your fork of this repo. ArgoCD will automatically detect the changes and update the necessary resources in your cluster.

A large problem for many people is how to easily upload or download data to and from the PVCs mounted as their workspace volumes for Notebook Servers. To make this easier a simple PVCViewer Controller was created (a slightly modified version of the tensorboard-controller). This feature was not ready in time for 1.3, and thus I am only documenting it here as an experimental feature as I believe many people would like to have this functionality. The images are grabbed from my personal dockerhub profile, but I can provide instructions for people that would like to build the images themselves. Also, it is important to note that the PVC Viewer will work with ReadWriteOnce PVCs, even when they are mounted to an active Notebook Server.

Here is an example of the PVC Viewer in action:

To use the PVCViewer Controller, it must be deployed along with an updated version of the Volumes Web App. To do so, deploy experimental-pvcviewer-controller.yaml and experimental-volumes-web-app.yaml instead of the regular Volumes Web App. If you are deploying Kubeflow with the kubeflow.yaml file, you can edit the root kustomization.yaml and comment out the regular Volumes Web App and uncomment the PVCViewer Controller and Experimental Volumes Web App.