opendatahub-operator

command module
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Published: Nov 3, 2023 License: Apache-2.0 Imports: 35 Imported by: 0

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

Documentation

The Go Gopher

There is no documentation for this package.

Directories

Path Synopsis
apis
datasciencecluster/v1
Package v1 contains API Schema definitions for the datasciencecluster v1 API group
Package v1 contains API Schema definitions for the datasciencecluster v1 API group
dscinitialization/v1
Package v1 contains API Schema definitions for the dscinitialization v1 API group
Package v1 contains API Schema definitions for the dscinitialization v1 API group
codeflare
Package codeflare provides utility functions to config CodeFlare as part of the stack which makes managing distributed compute infrastructure in the cloud easy and intuitive for Data Scientists
Package codeflare provides utility functions to config CodeFlare as part of the stack which makes managing distributed compute infrastructure in the cloud easy and intuitive for Data Scientists
dashboard
Package dashboard provides utility functions to config Open Data Hub Dashboard: A web dashboard that displays installed Open Data Hub components with easy access to component UIs and documentation
Package dashboard provides utility functions to config Open Data Hub Dashboard: A web dashboard that displays installed Open Data Hub components with easy access to component UIs and documentation
datasciencepipelines
Package datasciencepipelines provides utility functions to config Data Science Pipelines: Pipeline solution for end to end MLOps workflows that support the Kubeflow Pipelines SDK and Tekton
Package datasciencepipelines provides utility functions to config Data Science Pipelines: Pipeline solution for end to end MLOps workflows that support the Kubeflow Pipelines SDK and Tekton
kserve
Package kserve provides utility functions to config Kserve as the Controller for serving ML models on arbitrary frameworks
Package kserve provides utility functions to config Kserve as the Controller for serving ML models on arbitrary frameworks
modelmeshserving
Package modelmeshserving provides utility functions to config MoModelMesh, a general-purpose model serving management/routing layer
Package modelmeshserving provides utility functions to config MoModelMesh, a general-purpose model serving management/routing layer
ray
Package ray provides utility functions to config Ray as part of the stack which makes managing distributed compute infrastructure in the cloud easy and intuitive for Data Scientists
Package ray provides utility functions to config Ray as part of the stack which makes managing distributed compute infrastructure in the cloud easy and intuitive for Data Scientists
trustyai
Package trustyai provides utility functions to config TrustyAI, a bias/fairness and explainability toolkit
Package trustyai provides utility functions to config TrustyAI, a bias/fairness and explainability toolkit
workbenches
Package workbenches provides utility functions to config Workbenches to secure Jupyter Notebook in Kubernetes environments with support for OAuth
Package workbenches provides utility functions to config Workbenches to secure Jupyter Notebook in Kubernetes environments with support for OAuth
controllers
datasciencecluster
Package datasciencecluster contains controller logic of CRD DataScienceCluster
Package datasciencecluster contains controller logic of CRD DataScienceCluster
dscinitialization
Package dscinitialization contains controller logic of CRD DSCInitialization.
Package dscinitialization contains controller logic of CRD DSCInitialization.
secretgenerator
Package secretgenerator contains generator logic of secret resources used in Open Data Hub operator
Package secretgenerator contains generator logic of secret resources used in Open Data Hub operator
status
Package status contains different conditions, phases and progresses, being used by DataScienceCluster and DSCInitialization's controller
Package status contains different conditions, phases and progresses, being used by DataScienceCluster and DSCInitialization's controller
pkg
common
Package common contains utility functions used by different components
Package common contains utility functions used by different components
deploy
Package deploy
Package deploy
gvr
tests

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