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Info alert:Important Notice

Please note that more information about the previous v2 releases can be found here. You can use "Find a release" search bar to search for a particular release.

Upgrading Open Data Hub

Overview of upgrading Open Data Hub

As a cluster administrator, you can configure either automatic or manual upgrades for the Open Data Hub Operator.

  • If you configure automatic upgrades, when a new version of the Open Data Hub Operator is available, Operator Lifecycle Manager (OLM) automatically upgrades the running instance of your Operator without human intervention.

  • If you configure manual upgrades, when a new version of the Open Data Hub Operator is available, OLM creates an update request.

    A cluster administrator must manually approve the update request to update the Operator to the new version. See Manually approving a pending Operator upgrade for more information about approving a pending Operator upgrade.

  • By default, the Open Data Hub Operator follows a sequential update process. This means that if there are several minor versions between the current version and the version that you plan to upgrade to, Operator Lifecycle Manager (OLM) upgrades the Operator to each of the minor versions before it upgrades it to the final, target version. If you configure automatic upgrades, OLM automatically upgrades the Operator to the latest available version, without human intervention. If you configure manual upgrades, a cluster administrator must manually approve each sequential update between the current version and the final, target version.

  • When you upgrade Open Data Hub, the upgrade process automatically uses the values of the previous version’s DataScienceCluster object. After the upgrade, you should inspect the default DataScienceCluster object to check and optionally update the managementState status of the components.

    Note

    New components are not automatically added to the DataScienceCluster object during upgrade. If you want to use a new component, you must manually edit the DataScienceCluster object to add the component entry.

  • For any components that you update, Open Data Hub initiates a rollout that affects all pods to use the updated image.

  • Notebook images are integrated into the image stream during the upgrade and subsequently appear in the Open Data Hub dashboard.

    Note
    		 Notebook images are constructed externally; they are prebuilt images that undergo quarterly changes and they do not change with every Open Data Hub upgrade.
Important

After upgrading from Open Data Hub 2.19 to 2.20, existing instances of the model registry component are not updated, which causes the instance pods to use older images than the ones referenced by the operator pod.

To resolve this issue, create a new instance of each existing model registry, using the same database configuration, and delete the old model registry instance. The new model registry instance contains all existing registered models and their metadata.

Upgrading Open Data Hub version 2.0 to version 2.2

You can upgrade the Open Data Hub Operator from version 2.0 or 2.1 to version 2.2 or later by using the OpenShift console.

For information about upgrading from version 1 to version 2, see Upgrading Open Data Hub version 1 to version 2.

Upgrading Open Data Hub involves the following tasks:

  1. Reviewing and understanding the requirements for upgrading Open Data Hub version 2.

  2. Installing version 2.2 or later of Open Data Hub.

  3. If you are using self-signed certificates, adding a CA bundle.

Requirements for upgrading Open Data Hub version 2

This section describes the tasks that you should complete when upgrading Open Data Hub version 2.0 or 2.1 to version 2.2 or later.

Check the components in the DataScienceCluster object

When you upgrade to version 2, the upgrade process automatically uses the values from the DataScienceCluster object in the previous version.

After the upgrade, you should inspect the 2 DataScienceCluster object and optionally update the status of any components as described in Installing Open Data Hub components.

Note

New components are not automatically added to the DataScienceCluster object during upgrade. If you want to use a new component, you must manually edit the DataScienceCluster object to add the component entry.

Note that Open Data Hub Operator versions 2.2 and later use an upgraded API version for a DataScienceCluster instance, resulting in the following differences.

Table 1. DataScienceCluster instance differences
ODH 2.1 and earlier ODH 2.2 and later

API version

v1alpha1

v1

Enable component

.spec.components.[component_name].enabled: true

.spec.components.[component_name].managementState: Managed

Disable component

.spec.components.[component_name].enabled: false

.spec.components.[component_name].managementState: Removed

Migrate data science pipelines

Previously, data science pipelines in Open Data Hub were based on KubeFlow Pipelines v1. Starting with Open Data Hub 2.10.0, data science pipelines are based on KubeFlow Pipelines v2, which uses a different workflow engine. Data science pipelines 2.0 is enabled and deployed by default in Open Data Hub.

Starting with Open Data Hub 2.16, data science pipelines 1.0 resources are no longer supported or managed by Open Data Hub. It is no longer possible to deploy, view, or edit the details of pipelines that are based on data science pipelines 1.0 from either the dashboard or the KFP API server.

Open Data Hub does not automatically migrate existing data science pipelines 1.0 instances to 2.0. Before upgrading to Open Data Hub 2.16, you must manually migrate your existing data science pipelines 1.0 instances. For more information, see Migrating to data science pipelines 2.0.

Important

Data science pipelines 2.0 contains an installation of Argo Workflows. Open Data Hub does not support direct usage of this installation of Argo Workflows.

If you upgrade to Open Data Hub 2.10.0 or later with data science pipelines enabled and an Argo Workflows installation that is not installed by data science pipelines exists on your cluster, Open Data Hub components will not be upgraded. To complete the component upgrade, disable data science pipelines or remove the separate installation of Argo Workflows. The component upgrade will complete automatically.

Recreate model registries

When you upgrade from Open Data Hub 2.19 or earlier to Open Data Hub 2.20 or later versions, existing instances of the model registry component are not updated, which causes the instance pods to use older images than the ones referenced by the operator pod.

To resolve this issue, after upgrading, create a new instance of each existing model registry, using the same database configuration, and delete the old model registry instance. The new model registry instance contains all existing registered models and their metadata.

Installing Open Data Hub version 2

You can install Open Data Hub version 2 on your OpenShift Container Platform from the OpenShift web console. For information about upgrading the Open Hub Operator, see Upgrading Open Data Hub.

Installing Open Data Hub involves the following tasks:

  1. Installing the Open Data Hub Operator.

  2. Installing Open Data Hub components.

  3. Accessing the Open Data Hub dashboard.

Installing the Open Data Hub Operator version 2

Prerequisites

  • You are using OpenShift Container Platform 4.14 or later.

  • Your OpenShift cluster has a minimum of 16 CPUs and 32GB of memory across all OpenShift worker nodes.

  • You have cluster administrator privileges for your OpenShift Container Platform cluster.

  • If you are installing Open Data Hub 2.10.0 or later with data science pipelines, ensure your cluster does not have a separate installation of Argo Workflows that was not installed by Open Data Hub.

    Important

    Data science pipelines 2.0 includes an installation of Argo Workflows. Open Data Hub does not support direct customer usage of this installation of Argo Workflows.

    If there is an existing installation of Argo Workflows that is not installed by data science pipelines on your cluster, data science pipelines will be disabled after you install Open Data Hub.

    To enable data science pipelines, remove the separate installation of Argo Workflows from your cluster. Data science pipelines will be enabled automatically.

    Argo Workflows resources that are created by Open Data Hub have the following labels in the OpenShift Console under Administration > CustomResourceDefinitions, in the argoproj.io group:

     labels:
    app.kubernetes.io/part-of: data-science-pipelines-operator
    app.opendatahub.io/data-science-pipelines-operator: 'true'
Procedure

  1. Log in to your OpenShift Container Platform as a user with cluster-admin privileges. If you are performing a developer installation on try.openshift.com, you can log in as the kubeadmin user.

  2. Select Operators → OperatorHub.

  3. On the OperatorHub page, in the Filter by keyword field, enter Open Data Hub Operator.

  4. Click the Open Data Hub Operator tile.

  5. If the Show community Operator window opens, read the information and then click Continue.

  6. Read the information about the Operator and then click Install.

  7. On the Install Operator page, follow these steps:

    1. For Update channel, select fast.

      Note

      Version 2 of the Open Data Hub Operator represents an alpha release, accessible only on the fast channel. Later releases will change to the rolling channel when the Operator is more stable.

    2. For Version, select the version of the Operator that you want to install.

    3. For Installation mode, leave All namespaces on the cluster (default) selected.

    4. For Installed Namespace, select the openshift-operators namespace.

    5. For Update approval, select automatic or manual updates.

      • Automatic: When a new version of the Operator is available, Operator Lifecycle Manager (OLM) automatically upgrades the running instance of your Operator.

      • Manual: When a new version of the Operator is available, OLM notifies you with an update request that you must manually approve to upgrade the running instance of your Operator.

  8. Click Install. The installation might take a few minutes.

Verification

  • Select Operators → Installed Operators to verify that the Open Data Hub Operator is listed with Succeeded status.

Next Step

  • Install Open Data Hub components.

Additional resources

Installing Open Data Hub components

You can use the OpenShift web console to install specific components of Open Data Hub on your cluster when version 2 of the Open Data Hub Operator is already installed on the cluster.

Prerequisites

  • You have installed version 2 of the Open Data Hub Operator.

  • You can log in as a user with cluster-admin privileges.

  • If you want to use the trustyai component, you must enable user workload monitoring as described in Configuring monitoring for the multi-model serving platform.

  • If you want to use the kserve, modelmesh, or modelregistry components, you must have already installed the following Operator or Operators for the component. For information about installing an Operator, see Adding Operators to a cluster.

Table 2. Required Operators for components
Component Required Operators Catalog

kserve

Red Hat OpenShift Serverless Operator, Red Hat OpenShift Service Mesh Operator, Red Hat Authorino Operator

Red Hat

modelmesh

Prometheus Operator

Community

modelregistry

Red Hat Authorino Operator, Red Hat OpenShift Serverless Operator, Red Hat OpenShift Service Mesh Operator

NOTE: To use the model registry feature, you must install the required Operators in a specific order. For more information, see Configuring the model registry component.

Red Hat
Procedure

  1. Log in to your OpenShift Container Platform as a user with cluster-admin privileges. If you are performing a developer installation on try.openshift.com, you can log in as the kubeadmin user.

  2. Select Operators → Installed Operators, and then click the Open Data Hub Operator.

  3. On the Operator details page, click the DSC Initialization tab, and then click Create DSCInitialization.

  4. On the Create DSCInitialization page, configure by using Form view or YAML view. For general information about the supported components, see Tiered Components.

    • Configure by using Form view:

      1. In the Name field, enter a value.

      2. In the Components section, expand each component and set the managementState to Managed or Removed.

    • Configure by using YAML view:

      1. In the spec.components section, for each component shown, set the value of the managementState field to either Managed or Removed.

  5. Click Create.

  6. Wait until the status of the DSCInitialization is Ready.

  7. Click the Data Science Cluster tab, and then click Create DataScienceCluster.

  8. On the Create DataScienceCluster page, configure the DataScienceCluster by using Form view or YAML view. For general information about the supported components, see Tiered Components.

    • Configure by using Form view:

      1. In the Name field, enter a value.

      2. In the Components section, expand each component and set the managementState to Managed or Removed.

    • Configure by using YAML view:

      1. In the spec.components section, for each component shown, set the value of the managementState field to either Managed or Removed.

  9. Click Create.

Verification

  1. Select Home → Projects, and then select the opendatahub project.

  2. On the Project details page, click the Workloads tab and confirm that the Open Data Hub core components are running. For more information, see Tiered Components.

Next Step

  • Access the Open Data Hub dashboard.

Additional resources

Upgrading Open Data Hub version 1 to version 2

You can upgrade the Open Data Hub Operator from version 1 to version 2 by using the OpenShift console.

For information about upgrading from version 2.0, see Upgrading Open Data Hub version 2.0 to version 2.2.

Upgrading Open Data Hub involves the following tasks:

  1. Reviewing and understanding the requirements for upgrading Open Data Hub version 1.

  2. Upgrading the Open Data Hub Operator version 1.

  3. Installing Open Data Hub components.

Requirements for upgrading Open Data Hub version 1

This section describes the tasks that you should complete when upgrading Open Data Hub version 1 to version 2.

Note

After you install Open Data Hub 2, pipelines created with data science pipelines 1.0 continue to run, but are inaccessible from the Open Data Hub dashboard. If you are a current data science pipelines user, do not install Open Data Hub with data science pipelines 2.0 until you are ready to migrate to the new pipelines solution.

Check the components in the DataScienceCluster object

When you upgrade to version 2, the upgrade process automatically uses the values from the DataScienceCluster object in the previous version.

After the upgrade, you should inspect the 2 DataScienceCluster object and optionally update the status of any components as described in Installing Open Data Hub components.

Note

New components are not automatically added to the DataScienceCluster object during upgrade. If you want to use a new component, you must manually edit the DataScienceCluster object to add the component entry.

Recreate existing pipeline runs

When you upgrade to Open Data Hub 2, any existing pipeline runs that you created in version 1 continue to refer to the previous version’s image (as expected).

After upgrading, you must delete the pipeline runs (not the pipelines) and create new pipeline runs. The pipeline runs that you create in version 2 correctly refer to the version 2 image.

For more information about pipeline runs, see Managing pipeline runs.

Address KServe requirements

For KServe (single-model serving platform), you must meet these requirements:

  • Install dependent Operators, including the Red Hat OpenShift Serverless and Red Hat OpenShift Service Mesh Operators. For more information, see Serving large models.

  • After upgrading, you must inspect the default DataScienceCluster object and verify that the value of the managementState field for the kserve component is Managed.

  • In Open Data Hub version 1, the KServe component is a Limited Availability feature. If you enabled the kserve component and created models in version 1, then after you upgrade to version 2, you must update some Open Data Hub resources as follows:

    1. Log in to the OpenShift Container Platform console as a cluster administrator:

      $ oc login

    2. Update the DSC Initialization resource:

      $ oc patch $(oc get dsci -A -oname) --type='json' -p='[{"op": "replace", "path": "/spec/serviceMesh/managementState", "value":"Unmanaged"}]'

    3. Update the Data Science Cluster resource:

      $ oc patch $(oc get dsc -A -oname) --type='json' -p='[{"op": "replace", "path": "/spec/components/kserve/serving/managementState", "value":"Unmanaged"}]'

    4. Update the InferenceServices CRD:

      $ oc patch crd inferenceservices.serving.kserve.io --type=json -p='[{"op": "remove", "path": "/spec/conversion"}]'

    5. Optionally, restart the Operator pod.

  • If you deployed a model by using KServe in Open Data Hub version 1, when you upgrade to version 2 the model does not automatically appear in the Open Data Hub dashboard. To update the dashboard view, redeploy the model by using the Open Data Hub dashboard.

Upgrading the Open Data Hub Operator version 1

Prerequisites

  • You have installed version 1 of the Open Data Hub Operator.

  • You are using OpenShift Container Platform 4.14 or later.

  • Your OpenShift cluster has a minimum of 16 CPUs and 32GB of memory across all OpenShift worker nodes.

  • You can log in as a user with cluster-admin privileges.

Procedure

  1. Log in to the OpenShift Container Platform web console as a user with cluster-admin privileges.

  2. Select Operators → Installed Operators, and then click the 1.x version of the Open Data Hub Operator.

  3. Click the Subscription tab.

  4. Under Update channel, click the pencil icon.

  5. In the Change Subscription update channel dialog, select fast, and then click Save.

    If you configured the Open Data Hub Operator with automatic update approval, the upgrade begins. If you configured the Operator with manual update approval, perform the actions in the next step.

  6. To approve a manual update, perform these actions:

    1. Next to Upgrade status, click 1 requires approval.

    2. Click Preview InstallPlan.

    3. Review the manual install plan, and then click Approve.

Verification

  • Select Operators → Installed Operators to verify that the Open Data Hub Operator is listed with the 2.x version number and Succeeded status.

Next Steps

  • Install Open Data Hub components.

  • Access the Open Data Hub dashboard.

Additional resources

Installing Open Data Hub components

You can use the OpenShift web console to install specific components of Open Data Hub on your cluster when version 2 of the Open Data Hub Operator is already installed on the cluster.

Prerequisites

  • You have installed version 2 of the Open Data Hub Operator.

  • You can log in as a user with cluster-admin privileges.

  • If you want to use the trustyai component, you must enable user workload monitoring as described in Configuring monitoring for the multi-model serving platform.

  • If you want to use the kserve, modelmesh, or modelregistry components, you must have already installed the following Operator or Operators for the component. For information about installing an Operator, see Adding Operators to a cluster.

Table 3. Required Operators for components
Component Required Operators Catalog

kserve

Red Hat OpenShift Serverless Operator, Red Hat OpenShift Service Mesh Operator, Red Hat Authorino Operator

Red Hat

modelmesh

Prometheus Operator

Community

modelregistry

Red Hat Authorino Operator, Red Hat OpenShift Serverless Operator, Red Hat OpenShift Service Mesh Operator

NOTE: To use the model registry feature, you must install the required Operators in a specific order. For more information, see Configuring the model registry component.

Red Hat
Procedure

  1. Log in to your OpenShift Container Platform as a user with cluster-admin privileges. If you are performing a developer installation on try.openshift.com, you can log in as the kubeadmin user.

  2. Select Operators → Installed Operators, and then click the Open Data Hub Operator.

  3. On the Operator details page, click the DSC Initialization tab, and then click Create DSCInitialization.

  4. On the Create DSCInitialization page, configure by using Form view or YAML view. For general information about the supported components, see Tiered Components.

    • Configure by using Form view:

      1. In the Name field, enter a value.

      2. In the Components section, expand each component and set the managementState to Managed or Removed.

    • Configure by using YAML view:

      1. In the spec.components section, for each component shown, set the value of the managementState field to either Managed or Removed.

  5. Click Create.

  6. Wait until the status of the DSCInitialization is Ready.

  7. Click the Data Science Cluster tab, and then click Create DataScienceCluster.

  8. On the Create DataScienceCluster page, configure the DataScienceCluster by using Form view or YAML view. For general information about the supported components, see Tiered Components.

    • Configure by using Form view:

      1. In the Name field, enter a value.

      2. In the Components section, expand each component and set the managementState to Managed or Removed.

    • Configure by using YAML view:

      1. In the spec.components section, for each component shown, set the value of the managementState field to either Managed or Removed.

  9. Click Create.

Verification

  1. Select Home → Projects, and then select the opendatahub project.

  2. On the Project details page, click the Workloads tab and confirm that the Open Data Hub core components are running. For more information, see Tiered Components.

Next Step

  • Access the Open Data Hub dashboard.

Additional resources

Adding a CA bundle after upgrading

Open Data Hub provides support for using self-signed certificates. If you have upgraded Open Data Hub, you can add self-signed certificates to the Open Data Hub deployments and Data Science Projects in your cluster.

There are two ways to add a Certificate Authority (CA) bundle to Open Data Hub. You can use one or both of these methods:

  • For OpenShift Container Platform clusters that rely on self-signed certificates, you can add those self-signed certificates to a cluster-wide Certificate Authority (CA) bundle (ca-bundle.crt) and use the CA bundle in Open Data Hub.

  • You can use self-signed certificates in a custom CA bundle (odh-ca-bundle.crt) that is separate from the cluster-wide bundle.

For more information, see Understanding certificates in Open Data Hub.

Prerequisites
Procedure

  1. Log in to the OpenShift Container Platform as a cluster administrator.

  2. Click Operators → Installed Operators and then click the Open Data Hub Operator.

  3. Click the DSC Initialization tab.

  4. Click the default-dsci object.

  5. Click the YAML tab.

  6. Add the following to the spec section, setting the managementState field to Managed:

    spec:
  trustedCABundle:
    managementState: Managed
    customCABundle: ""

  7. If you want to use self-signed certificates added to a cluster-wide CA bundle, log in to the OpenShift Container Platform as a cluster administrator and follow the steps as described in Configuring the cluster-wide proxy during installation.

  8. If you want to use self-signed certificates in a custom CA bundle that is separate from the cluster-wide bundle, follow these steps:

    1. Add the custom certificate to the customCABundle field of the default-dsci object, as shown in the following example:

      spec:
  trustedCABundle:
    managementState: Managed
    customCABundle: |
      -----BEGIN CERTIFICATE-----
      examplebundle123
      -----END CERTIFICATE-----

    2. Click Save.

      The Open Data Hub Operator creates an odh-trusted-ca-bundle ConfigMap containing the certificates in all new and existing non-reserved namespaces.

Verification

  • If you are using a cluster-wide CA bundle, run the following command to verify that all non-reserved namespaces contain the odh-trusted-ca-bundle ConfigMap:

    $ oc get configmaps --all-namespaces -l app.kubernetes.io/part-of=opendatahub-operator | grep odh-trusted-ca-bundle

  • If you are using a custom CA bundle, run the following command to verify that a non-reserved namespace contains the odh-trusted-ca-bundle ConfigMap and that the ConfigMap contains your customCABundle value. In the following command, example-namespace is the non-reserved namespace and examplebundle123 is the customCABundle value.

    $ oc get configmap odh-trusted-ca-bundle -n example-namespace -o yaml | grep examplebundle123