opendatahub-operator

README

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 available. 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

Download manifests

The get_all_manifests.sh script facilitates the process of fetching manifests from remote git repositories. It is configured to work with a predefined map of components and their corresponding manifest locations.

Structure of COMPONENT_MANIFESTS

Each component is associated with its manifest location in the COMPONENT_MANIFESTS map. The key is the component's name, and the value is its location, formatted as <repo-org>:<repo-name>:<branch-name>:<source-folder>:<target-folder>

Workflow

1. The script clones the remote repository <repo-org>/<repo-name> from the specified <branch-name>.
2. It then copies the content from the relative path <source-folder> to the local odh-manifests/<target-folder> folder.

Local Storage

The script utilizes a local, empty folder named odh-manifests to host all required manifests, sourced either directly from the component’s source repository or the default odh-manifests git repository.

Adding New Components

To include a new component in the list of manifest repositories, simply extend the COMPONENT_MANIFESTS map with a new entry, as shown below:

declare -A COMPONENT_MANIFESTS=(
  // existing components ...
  ["new-component"]="<repo-org>:<repo-name>:<branch-name>:<source-folder>:<target-folder>"
)

Customizing Manifests Source

You have the flexibility to change the source of the manifests. Invoke the get_all_manifests.sh script with specific flags, as illustrated below:

./get_all_manifests.sh --odh-dashboard="maistra:odh-dashboard:test-manifests:manifests:odh-dashboard"

If the flag name matches components key defined in COMPONENT_MANIFESTS it will overwrite its location, otherwise the command will fail.

for local development

make get-manifests

This first cleanup your local odh-manifests folder. Ensure back up before run this command if you have local changes of manifests want to reuse later.

for build operator image

make image-build

By default, building an image without any local changes(as a clean build) This is what the production build system is doing.

In order to build an image with local odh-manifests folder, to set IMAGE_BUILD_FLAGS ="--build-arg USE_LOCAL=true" in make. e.g make image-build -e IMAGE_BUILD_FLAGS="--build-arg USE_LOCAL=true"

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
  

Test with customized manifests

There are 2 ways to test your changes with modification:

1. set devFlags.ManifestsUri field of DSCI instance during runtime: this will pull down manifests from remote git repo by using this method, it overwrites manifests and component images if images are set in the params.env file
2. [Under implementation] build operator image with local manifests

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/v1
     kind: DataScienceCluster
     metadata:
       name: example
     spec:
       components:
         codeflare:
           managementState: Managed
         dashboard:
           managementState: Managed
         datasciencepipelines:
           managementState: Managed
         kserve:
           managementState: Managed
         modelmeshserving:
           managementState: Managed
         ray:
           managementState: Managed
         workbenches:
           managementState: Managed
   

2. Enable only Dashboard and Workbenches

     apiVersion: datasciencecluster.opendatahub.io/v1
     kind: DataScienceCluster
     metadata:
       name: example
     spec:
       components:
         dashboard:
           managementState: Managed
         workbenches:
           managementState: Managed
   

Note: Default value for a component is false.

Run functional Tests

The functional tests are writted based on ginkgo and gomega. In order to run the tests, the user needs to setup the envtest which provides a mocked kubernetes cluster. A detailed explanation on how to configure envtest is provided here.

To run the test on individual controllers, change directory into the contorller's folder and run

ginkgo -v

This provides detailed logs of the test spec.

Note: When runninng tests for each controller, make sure to add the BinaryAssetsDirectory attribute in the envtest.Environment in the suite_test.go file. The value should point to the path where the envtest binaries are installed.

In order to run tests for all the controllers, we can use the make command

make unit-test

Note: The make command should be executed on the root project level.

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

Ensure when testing RHODS operator in dev mode, no ODH CSV exists 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"

Troubleshooting

Please refer to troubleshooting documentation