This operator is the primary operator for Open Data Hub. It is responsible for enabling Data science applications like Jupyter Notebooks, Modelmesh serving, Datascience pipelines etc. The operator makes use of DataScienceCluster CRD to deploy and configure these applications.

Usage

Installation

The latest version of operator can be installed from the community-operators catalog on OperatorHub. It can also be build and installed from source manually, see the Developer guide for further instructions.

1. Subscribe to operator by creating following subscription

   cat <<EOF | oc create -f -
   apiVersion: operators.coreos.com/v1alpha1
   kind: Subscription
   metadata:
     name: opendatahub-operator
     namespace: openshift-operators
   spec:
     channel: fast
     name: opendatahub-operator
     source: community-operators
     sourceNamespace: openshift-marketplace
   EOF

2. Create DataScienceCluster CR to enable components

Dev Preview

Developer Preview of the new Open Data Hub operator codebase is now avaible. Refer Dev-Preview.md for testing preview features.

Developer Guide

Pre-requisites

• Go version go1.18.9
• operator-sdk version can be updated to v1.24.1

Build Image

• Custom operator image can be built using your local repository

  make image -e IMG=quay.io/<username>/opendatahub-operator:<custom-tag>
  

  or (for example to user vhire)

  make image -e IMAGE_OWNER=vhire
  

  The default image used is quay.io/opendatahub/opendatahub-operator:dev-0.0.1 when not supply argument for make image

• Once the image is created, the operator can be deployed either directly, or through OLM. For each deployment method a kubeconfig should be exported

  export KUBECONFIG=<path to kubeconfig>
  

Deployment

Deploying operator locally

• Define operator namespace

  export OPERATOR_NAMESPACE=<namespace-to-install-operator>
  

• Deploy the created image in your cluster using following command:

  make deploy -e IMG=quay.io/<username>/opendatahub-operator:<custom-tag> -e OPERATOR_NAMESPACE=<namespace-to-install-operator>
  

• To remove resources created during installation use:

  make undeploy
  

Deploying operator using OLM

• To create a new bundle in defined operator namespace, run following command:

  export OPERATOR_NAMESPACE=<namespace-to-install-operator>
  make bundle
  

  Note : Skip the above step if you want to run the existing operator bundle.

• Build Bundle Image:

  make bundle-build bundle-push BUNDLE_IMG=quay.io/<username>/opendatahub-operator-bundle:<VERSION>
  

• Run the Bundle on a cluster:

  operator-sdk run bundle quay.io/<username>/opendatahub-operator-bundle:<VERSION> --namespace $OPERATOR_NAMESPACE
  

Example DataScienceCluster

When the operator is installed successfully in the cluster, a user can create a DataScienceCluster CR to enable ODH components. At a given time, ODH supports only one instance of the CR, which can be updated to get custom list of components.

1. Enable all components

     apiVersion: datasciencecluster.opendatahub.io/v1alpha1
     kind: DataScienceCluster
     metadata:
       name: example
     spec:
       components:
         codeflare:
           enabled: true
         dashboard:
           enabled: true
         datasciencepipelines:
           enabled: true
         kserve:
           enabled: true
         modelmeshserving:
           enabled: true
         ray:
           enabled: true
         workbenches:
           enabled: true 

2. Enable only Dashboard and Workbenches

     apiVersion: datasciencecluster.opendatahub.io/v1alpha1
     kind: DataScienceCluster
     metadata:
       name: example
     spec:
       components:
         dashboard:
           enabled: true
         workbenches:
           enabled: true 

Note: Default value for a component is false.

Run e2e Tests

A user can run the e2e tests in the same namespace as the operator. To deploy opendatahub-operator refer to this section. The following environment variables must be set when running locally:

export KUBECONFIG=/path/to/kubeconfig

Once the above variables are set, run the following:

make e2e-test

Additional flags that can be passed to e2e-tests by setting up E2E_TEST_FLAGS variable. Following table lists all the available flags to run the tests:

Flag	Description	Default value
--skip-deletion	To skip running of dsc-deletion test that includes deleting DataScienceCluster resources. Assign this variable to true to skip DataScienceCluster deletion.	false

Example command to run full test suite skipping the test for DataScienceCluster deletion.

make e2e-test -e OPERATOR_NAMESPACE=<namespace> -e E2E_TEST_FLAGS="--skip-deletion=true"