The steps are also available in a tutorial video available on the OpenShift youtube channel.
Installing ODH Beta requires 4.x. Documentation for OpenShift can be located (here). All screenshots and instructions are from OpenShift 4.4. For the purposes of this quick start, we used try.openshift.com on AWS. Tutorials have also been tested on Code Ready Containers with 16GB of RAM.
We will not be installing optional components such as Argo, Seldon, AI Library, or Kafka to avoid using too much resources in case your cluster is small.
Installing the Open Data Hub Operator
The Open Data Hub operator is available in the OpenShift 4.x Community Operators section. You can install it from the OpenShift webui by following the steps below:
- From the OpenShift console, log in as a user with
cluster-adminprivileges. For a developer installation from try.openshift.com including AWS and CRC, the
kubeadminuser will work.
- Create a new namespace for your installation of Open Data Hub.
Open Data Hubin the
- Select the new namespace if not already selected.
OperatorHubfor a list of community operators.
- Filter for
Open Data Hubor look under
Big Datafor the icon for
Open Data Hub.
- Click the
Installbutton and follow the installation instructions to install the Open Data Hub operator.
- The subscription creation view will offer a few options including Update Channel, keep the
- To view the status of the Open Data Hub operator installation, find the Open Data Hub Operator under
Installed Operators(inside the namespace you created earlier). Once the STATUS field displays
InstallSucceeded, you can proceed to create a new Open Data Hub deployment.
Create a New Open Data Hub Deployment
The Open Data Hub operator will create new Open Data Hub deployments and manage its components. Let’s create a new Open Data Hub deployment.
Find the Open Data Hub Operator under
Installed Operators(inside the namespace you created earlier)
Click on the Open Data Hub Operator to bring up the detail.
Create Instanceto create a new deployment.
- Here you’ll be presented with a YAML file to customize your deployment. Most options are disabled, and for this tutorial we’ll leave them that way to make sure the components for JupyterHub and Spark fit within our cluster resource constraints. Take note of some parameters:
- the name of your deployment
metadata: name: opendatahub
- only the components listed in the
KFDefresource will be deployed:
spec: applications: - kustomizeConfig: repoRef: name: manifests path: odh-common name: odh-common - kustomizeConfig: repoRef: name: manifests path: radanalyticsio/spark/cluster name: radanalyticsio-cluster - kustomizeConfig: repoRef: name: manifests path: radanalyticsio/spark/operator name: radanalyticsio-spark-operator - kustomizeConfig: parameters: - name: s3_endpoint_url value: s3.odh.com repoRef: name: manifests path: jupyterhub/jupyterhub name: jupyterhub - kustomizeConfig: overlays: - additional repoRef: name: manifests path: jupyterhub/notebook-images name: notebook-images
- the name of your deployment
specof the resource to match the above and click
Create. If you accepted the default name, this will trigger an Open Data Hub deployment named
opendatahubwith JupyterHub and Spark.
Verify the installation by viewing the Open Data Hub tab within the operator details. You Should see
- Verify the installation by viewing the project workload. JupyterHub and Spark Operator should be running.