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Red Hat OpenShift Data Science Adminis General Information about Installation diff --git a/rhods-admin/1.33/chapter1/section1.html b/rhods-admin/1.33/chapter1/section1.html index cd7d13d..0183a80 100644 --- a/rhods-admin/1.33/chapter1/section1.html +++ b/rhods-admin/1.33/chapter1/section1.html @@ -53,10 +53,10 @@

Red Hat OpenShift Data Science Adminis General Information about Installation @@ -174,7 +174,7 @@

General Information about Installation

diff --git a/rhods-admin/1.33/chapter1/section2.html b/rhods-admin/1.33/chapter1/section2.html index 1c1608a..2fa9342 100644 --- a/rhods-admin/1.33/chapter1/section2.html +++ b/rhods-admin/1.33/chapter1/section2.html @@ -3,7 +3,7 @@ - Section 2 :: Red Hat OpenShift Data Science Administration + Installation using the Web Console :: Red Hat OpenShift Data Science Administration @@ -53,10 +53,10 @@

Red Hat OpenShift Data Science Adminis General Information about Installation @@ -128,7 +128,7 @@

Red Hat OpenShift Data Science Adminis @@ -137,11 +137,350 @@

Red Hat OpenShift Data Science Adminis
-

Section 2

- +

Installation using the Web Console

+
+
+
+

Red Hat Openshift Data Science is available as an operator via Openshift Operator Hub. You will install the Red Hat Openshift Data Science operator V2 using the Openshift web console in this section.

+
+
+
+
+

Installation of Openshift Data Science dependecies

+
+
+

As described in the General Information about Installation section you may need to install other operators depending on the components and features of Openshift Data Science you want to use. +In general not installing dependencies before the Red Hat Openshift Data Science does not impact the installation process itself, however it may impact initialization of the components that depend on them. Hence it’s better to install the dependencies beforehand.

+
+
+
+
Red Hat Openshift Pipelines Operator
+
+

The Red Hat Openshift Pipelines Operator is required if you want to install the Red Hat Openshift Data Science Pipelines component.

+
+
NVIDIA GPU Operator
+
+

The NVIDIA GPU Operator is required for GPU support in Red Hat Openshift Data Science.

+
+
Node Feature Discovery Operator
+
+

The Node Feature Discovery Operator is a prerequisity for the NVIDIA GPU Operator.

+
+
+
+
+

The following demonstration shows the installation of the Red Hat Openshift Pipelines Operator which is a dependency of the Data Science Pipelines component installed by default. Installation of the two other operators is very similar.

+
+
+

Demo: Installation of the Red Hat Openshift Pipelines operator

+
+
    +
  1. +

    Login to Red Hat Openshift using a user which has the cluster-admin role assigned.

    +
  2. +
  3. +

    Navigate to OperatorsOperatorHub and search for Red Hat Openshift Pipelines

    +
    +
    +pipeline search +
    +
    +
  4. +
  5. +

    Click on the Red Hat Openshift Pipelines operator and in the pop up window click on Install to open the operator’s installation view.

    +
    +
    +pipeline install1 +
    +
    +
  6. +
  7. +

    In the installation view choose the Update channel and the Update approval parameters. You can accept the default values. The Installation mode and the Installed namespace parameters are fixed.

    +
    +
    +pipeline install2 +
    +
    +
  8. +
  9. +

    Click on the Install button at the bottom of to view the to proceed with the installation. A window showing the installation progress will pop up.

    +
    +
    +pipeline install3 +
    +
    +
  10. +
  11. +

    When the installation finishes the operator is ready to be used by the Red Hat Openshift Data Science.

    +
    +
    +pipeline install4 +
    +
    +
  12. +
+
+
+
+
+
+

Demo: Installation of the Red Hat Openshift Data Science operator

+
+
+ + + + + +
+ + +The installation requires a user with the cluster-admin role +
+
+
+
    +
  1. +

    Login to the Red Hat Openshift using a user which has the cluster-admin role assigned.

    +
  2. +
  3. +

    Navigate to OperatorsOperatorHub and search for Red Hat Openshift Data Science.

    +
    +
    +rhods install1 +
    +
    +
  4. +
  5. +

    Click on the Red Hat Openshift Data Science operator and in the pop up window click on Install to open the operator’s installation view.

    +
    + + + + + +
    + + +Make sure you select Openshift Data Science from Red Hat not the Community version. +
    +
    +
    +
    +rhods install2 +
    +
    +
  6. +
  7. +

    In the installation view window choose the alpha Update Channel, Automatic Update approval and keep the default Installed Namespace. Click on the Install button to start the installation.

    +
    +
    +rhods2 install view +
    +
    +
    +

    Operator Installation progress window will pop up. The installation may take a couple of minutes.

    +
    +
    +
    +rhods2 install +
    +
    +
  8. +
  9. +

    When the operator’s installation is finished, click on the Create DataScienceCluster button to create and configure your cluster.

    +
    +
    +rhods2 install finished +
    +
    +
  10. +
  11. +

    In the Create DataScienceCluster view select components that will be installed and managed by the operator.

    +
    +

    There are following components to choose from:

    +
    +
    +
      +
    • +

      CodeFlare: CodeFlare simplifies the integration, scaling and acceleration of complex multi-step analytics and machine learning pipelines on the hybrid multi-cloud.CodeFlare, an open-source framework for simplifying the integration and efficient scaling of big data and AI workflows onto the hybrid cloud. CodeFlare is built on top of Ray, an emerging open-source distributed computing framework for machine learning applications. CodeFlare extends the capabilities of Ray by adding specific elements to make scaling workflows easier.

      +
    • +
    • +

      Ray: Ray is an open technology for “fast and simple distributed computing.” It makes it easy for data scientists and application developers to run their code in a distributed fashion. It also provides a lean and easy interface for distributed programming with many different libraries, best suited to perform machine learning and other intensive compute tasks.

      +
    • +
    • +

      Dashboard: A web dashboard that displays installed Data Science components with easy access to component UIs and documentation

      +
    • +
    • +

      Data Science Pipelines: Data Science Pipelines allow building portable machine learning workflows with data science pipelines, using Docker containers. This enables you to standardize and automate machine learning workflows to enable you to develop and deploy your data science models.

      +
    • +
    • +

      KServe: Kserve, or KFServing, is a Kubernetes-based serverless framework for inferencing (scoring) deep learning models. It provides a consistent and Kubernetes-native way to deploy, serve, and manage machine learning models in production environments. KServe is designed to be scalable and efficient, allowing for automatic scaling of model serving based on demand.

      +
    • +
    • +

      ModelMeshServing: ModelMesh Serving is the Controller for managing ModelMesh, a general-purpose model serving management/routing layer.

      +
    • +
    • +

      Workbenches: Workbenches allow to examine and work with data models in an isolated area. It enables you to create a new Jupyter notebook from an existing notebook container image to access its resources and properties. For data science projects that require data to be retained, you can add container storage to the workbench you are creating.

      +
    • +
    +
    +
    +

    For this demonstration accept the default (pre-selected) components selection - Dashboard, Data Science Pipelines, Model Mesh Serving and Workbenches.

    +
    +
    +

    You can choose to create the DataScienceCluster using either the Form view or the YAML View. The Form view is a web based form and 'YAML view' is based on a YAML definition of the DataScience cluster resource. The following picture shows the Form view.

    +
    +
    +
    +rhods2 create cluster +
    +
    +
    +

    If you choose the YAML view, you are presented with a template of the YAML DataScienceCluster resource definition similar to the one below.

    +
    +
    +
    +
    apiVersion: datasciencecluster.opendatahub.io/v1
    +kind: DataScienceCluster
    +metadata:
    +  name: default
    +  labels:
    +    app.kubernetes.io/name: datasciencecluster
    +    app.kubernetes.io/instance: default
    +    app.kubernetes.io/part-of: rhods-operator
    +    app.kubernetes.io/managed-by: kustomize
    +    app.kubernetes.io/created-by: rhods-operator
    +spec:
    +  components:
    +    codeflare:
    +      managementState: Removed  (1)
    +    dashboard:
    +      managementState: Managed  (2)
    +    datasciencepipelines:
    +      managementState: Managed
    +    kserve:
    +      managementState: Removed
    +    modelmeshserving:
    +      managementState: Managed
    +    ray:
    +      managementState: Removed
    +    workbenches:
    +      managementState: Managed
    +
    +
    +
    + + + + + + + + + +
    1For components you do not want to install use Removed
    2For components you want to install and manage by the operator use Managed
    +
    +
    +

    After naming the cluster and choosing the components you wish the operator to install and manage click on the Create button.

    +
    +
  12. +
  13. +

    After creating the DataScienceCluster a view showing the DataScienceCluster details opens. Wait until the status of the cluster reads Phase: Ready. This represents the status of the whole cluster.

    +
    +
    +rhods2 clusters +
    +
    +
    +

    You may also check the status of individual installed components by looking at their conditions. Click on the default cluster and switch to the YAML view. Scroll down to view conditions.

    +
    +
    +
    +rhods2 conditions +
    +
    +
    +

    Each condition is represented by a type and a status. The Type is a string describing the condition, for instance odh-dashboardReady and the status says whether it is true or not. The following example shows the Ready status of the Dashboard component.

    +
    +
    +
    +
    - lastHeartbeatTime: '2023-11-13T10:53:20Z'
    +  lastTransitionTime: '2023-11-13T10:53:20Z'
    +  message: Component reconciled successfully
    +  reason: ReconcileCompleted
    +  status: 'True'
    +  type: odh-dashboardReady
    +
    +
    +
    +

    The following list shows the conditions you may want to check:

    +
    +
    +
      +
    • +

      rayReady

      +
    • +
    • +

      codeflareReady

      +
    • +
    • +

      model-meshReady

      +
    • +
    • +

      workbenchesReady

      +
    • +
    • +

      data-science-pipelines-operatorReady

      +
    • +
    • +

      odh-dashboardReady

      +
    • +
    +
    +
  14. +
  15. +

    The operator should be installed and configured now. +In the applications window in the right upper corner of the screen the Red Hat Openshift Data Science dashboard should be available.

    +
    +
    +rhods verify1 +
    +
    +
  16. +
  17. +

    Click on the Red Hat Openshift Data Science button to log in to the Red Hat Openshift Data Science.

    +
    +
    +rhods verify2 +
    +
    +
    + + + + + +
    + + +It may take a while to start all the service pods hence the login window may not be accessible immediately. If you are getting an error, check the status of the pods in the project redhat-ods-applications. +Navigate to Workloadspods and select project redhat-ods-applications. All pods must be running and be ready. If they are not, wait until they become running and ready. +
    +
    +
    +
    +rhods verify pods +
    +
    +
  18. +
+
+
+
diff --git a/rhods-admin/1.33/chapter1/section3.html b/rhods-admin/1.33/chapter1/section3.html index bd0a0ad..87355f8 100644 --- a/rhods-admin/1.33/chapter1/section3.html +++ b/rhods-admin/1.33/chapter1/section3.html @@ -3,7 +3,7 @@ - Section 3 :: Red Hat OpenShift Data Science Administration + Installation Using the Command Line Interface :: Red Hat OpenShift Data Science Administration @@ -53,10 +53,10 @@

Red Hat OpenShift Data Science Adminis General Information about Installation @@ -128,7 +128,7 @@

Red Hat OpenShift Data Science Adminis @@ -137,12 +137,666 @@

Red Hat OpenShift Data Science Adminis
-

Section 3

+

Installation Using the Command Line Interface

+
+
-

This is Section 3 of Chapter 1 in the hello quick course…​.

+

This section covers installation of the Red Hat Openshift Data Science from the command line interface. Command line installation requires a bit more understanding of openshift resources than the web based installation hence before we get to the actual installation we will go over some theory related to the CLI-based operator installation.

+
+
+
+
+

Introduction to CLI-based operator installations

+
+
+

In OpenShift, the Operator Lifecycle Manager (OLM) helps users install and manage operators and their associated services. +Operator Lifecycle Manager (OLM) uses following resources:

+
+
+
+
Catalog Resource
+
+

Each catalog source resource references an operator repository. Periodically, the OLM +examines the catalog sources in the cluster and retrieves information about the operators in +each source.

+
+
Package manifest
+
+

The OLM creates a package manifest for each available operator. The package manifest +contains the required information to install an operator, such as the available channels.

+
+
Operator group
+
+

Operator groups define how the OLM presents operators across namespaces.

+
+
Subscription
+
+

Cluster administrators create subscriptions to install operators.

+
+
Operator
+
+

The OLM creates operator resources to store information about installed operators.

+
+
Install plan
+
+

The OLM creates install plan resources as part of the installation and update process. When +requiring approvals, administrators must approve install plans.

+
+
Cluster service version (CSV)
+
+

Each version of an operator has a corresponding CSV. The CSV contains the information that +the OLM requires to install the operator.

+
+
+
+
+

When installing an operator, an administrator must create only the Operator Group (unless the target namespace is openshift-operators where the Operator Group resource already exists) and the Subscription. Optionally a Namespace can be created if it does not exists. Other resources are created by the OLM.

+
+
+

Following are examples of the resources an adminstrator must create.

+
+
+
+
Namespace
+
+
+
+
+
+
+
apiVersion: v1
+kind: Namespace
+metadata:
+  name: operator_namespace (1)
+spec: {}
+
+
+
+ + + + + +
1Name of the namespace to create.
+
+
+
+
+ + + + + +
+ + +Namespace has to be only created if it does not already exist. An operator can be installed into an existing namespace. +
+
+
+
+
Operator group
+
+
+
+
+
+
+
apiVersion: operators.coreos.com/v1
+kind: OperatorGroup
+metadata:
+  name: Operator_group_name (1)
+  namespace: operator_namespace (2)
+spec: {}
+
+
+
+ + + + + + + + + +
1Name of the operator group resource.
2Name of the namespace to create the operator group resource in.
+
+
+
+
+
+
Subscription
+
+
+
+
+
+

When a Subscription resource is created the OLM starts the installation of the operator based on the details set in the Subscription resource.

+
+
+
+
apiVersion: operators.coreos.com/v1alpha1
+kind: Subscription
+metadata:
+  name: Subscription_name  (1)
+  namespace: operator_namespace (2)
+spec:
+  channel: channel (3)
+  installPlanApproval: Manual/Automatic (4)
+  name: Operator_name
+  source: Catalog_source
+  sourceNamespace: openshift-marketplace
+
+
+
+ + + + + + + + + + + + + + + + + +
1Name of the subscription resource.
2Name of the namespace to create the subscription resource in.
3Update channel to install the operator from. For more information about finding available channels see the Finding Update Channels section.
4installPlanApproval attribute can be either Automatic or Manual. For more details about manual installation approval se the Approving Installation Manualy section.
+
+
+
+
+

Finding Update Channels

+
+
+
+

Update channels and other details about the operator can be found in a resource packagemanifest. +It can be however a little challenging to search the packagemanifest as it is quite complex. JQuery is a powerfull tool to filter values from JSON resource manifests.

+
+
+

The following example lists available channels for the rhods-operator operator.

+
+
+
+
$ oc get packagemanifest rhods-operator -o json|jq '.status.channels[].name'
+"beta"
+"embedded"
+"stable"
+"alpha"
+
+
+
+
+
+
+

Approving Installation Manualy

+
+

As a part of the installation process OLM creates an installplan resource in the namespace the operator will be installed into. The installplan resource contains information about the installation and updates. When the installPlanApproval parameter of a Subscription is set to Manual, the installation has to be manually approved by patching the corresponding installplan resource in order to start.

+
+
+
+
+
+
$ oc get installplan -n operator_namespace
+NAME            CSV                     APPROVAL   APPROVED
+install-vpgls   operator_csv   Manual     false   (1)
+
+$ oc patch installplan install-vpgls --type merge -p '{"spec":{"approved":true}}' -n operator_namespace
+installplan.operators.coreos.com/install-vpgls patched  (2)
+
+$ oc get installplan -n redhat-ods-operator
+NAME            CSV                     APPROVAL   APPROVED
+install-vpgls   operator_name   Manual     true  (3)
+
+
+
+ + + + + + + + + + + + + +
1Approval has not been set.
2The patch command approves the installation.
3Approval has been set and installation starts.
+
+
+
+
+
+

Checking Installation Progress

+
+

Installation progress can be found in the operator’s status. +The following example shows a quick check of the current status of the Openshift Pipelines operator.

+
+
+
+
$ oc get olm|grep ^clusterserviceversion|grep openshift-pipelines-operator
+clusterserviceversion.../openshift-pipelines-operator...   Pending  (1)
+
+$ oc get olm|grep ^clusterserviceversion|grep openshift-pipelines-operator
+openshift-pipelines-operator*
+clusterserviceversion.../openshift-pipelines-operator...   Succeeded  (2)
+
+
+
+ + + + + + + + + +
1The operator is installing.
2The operator has been successfully installed.
+
+
+

If you are interested in more details, you can get the operator’s manifest and check it’s status attribude. JQuery can be used to filter the status out.

+
+
+
+
$ oc get operators
+NAME                                                  AGE
+mcg-operator.openshift-storage                        7h24m
+ocs-operator.openshift-storage                        7h24m
+odf-csi-addons-operator.openshift-storage             7h24m
+odf-operator.openshift-storage                        7h25m
+openshift-pipelines-operator-rh.openshift-operators   20m    (1)
+
+$ oc get operator openshift-pipelines-operator-rh.openshift-operators -o json| \
+jq '.status.components.refs[]|select(.kind=="ClusterServiceVersion").conditions[]'
+
+{
+  "lastTransitionTime": "2023-11-01T21:01:25Z",
+  "lastUpdateTime": "2023-11-01T21:01:26Z",
+  "message": "installing: waiting for deployment openshift-pipelines-...",
+  "reason": "InstallWaiting", (1)
+  "status": "True",           (2)
+  "type": "Installing"        (3)
+}
+
+
+
+ + + + + + + + + + + + + +
1Reason for the condition.
2Status of the conditions.
3Type of the condition. Type Installing together with status True indicate that the installation is in progress. Type Succeeded together with status True and reason InstallSucceeded indicate that the installation has been successfull.
+
+
+
+
+
+

Installation of Red Hat Openshift Data Science dependencies

+
+
+

As described in the General Information about Installation section you may need to install other operators depending on the components and features of Openshift Data Science you want to use. +In general not installing dependencies before the Red Hat Openshift Data Science does not impact the installation process itself, however it may impact initialization of the components that depend on them. Hence it’s better to install the dependencies beforehand.

+
+
+
+
Red Hat Openshift Pipelines Operator
+
+

The Red Hat Openshift Pipelines Operator is required if you want to install the Red Hat Openshift Data Science Pipelines component.

+
+
NVIDIA GPU Operator
+
+

The NVIDIA GPU Operator is required for GPU support in Red Hat Openshift Data Science.

+
+
Node Feature Discovery Operator
+
+

The Node Feature Discovery Operator is a prerequisity for the NVIDIA GPU Operator.

+
+
+
+
+

The following demonstration shows the installation of the Red Hat Openshift Pipelines Operator which is a dependency of the Data Science Pipelines component installed by default. Installation of the two other operators is very similar.

+
+
+

Demo: Installation of the Red Hat Openshift Pipelines Operator

+
+ + + + + +
+ + +If you have already installed the Red Hat Openshift Data Science operator during the previous demonstration, you have to uninstall it. Follow the Uninstalling Red Hat Openshift Data Science demo to uninstall the Red Hat Openshift Data Science operator first and Uninstalling Red Hat Openshift Pipelines to uninstall Red Hat Openshift Pipelines first. +
+
+
+
    +
  1. +

    Log in as a user with the cluster-admin role assigned.

    +
    +
    +
    $ oc login -u admin -p password https://api...:6443
    +Login successful.
    +
    +You have access to 74 projects, the list has been suppressed. You can list all projects with 'oc projects'
    +
    +Using project "default".
    +
    +
    +
  2. +
  3. +

    The Pipelines operator’s default namespace is openshift-operators, hence neither the namespace nor operator group resources must be created. Create only the Subscription resource to start the installation.

    +
    +
    +
    +
    +
    $ cat <<EOF > pipelines-subs.yaml
    +apiVersion: operators.coreos.com/v1alpha1
    +kind: Subscription
    +metadata:
    +  name: openshift-pipelines-operator-rh
    +  namespace: openshift-operators
    +spec:
    +  channel: latest (1)
    +  installPlanApproval: Automatic (2)
    +  name: openshift-pipelines-operator-rh
    +  source: redhat-operators
    +  sourceNamespace: openshift-marketplace
    +EOF
    +
    +$ oc create -f pipelines-subs.yaml
    +
    +
    +
    + + + + + + + + + +
    1The update channel to install the operator from. To find all available channels see the Finding Update Channels section.
    2In case the installPlanApproval is set to Manual, approve the installation first to start it. Refer to the Approving Installation Manualy section for more information.
    +
    +
    +
    +
  4. +
  5. +

    You may check the installation progress using the operator’s status information. For more information see the Checking Installation Progress section.

    +
  6. +
+
+
+
+
+
+

Demo: Installation of the Red Hat Openshift Data Science operator

+
+
+
    +
  1. +

    Log in as a user with the cluster-admin role assigned.

    +
    +
    +
    $ oc login -u admin -p password https://api...:6443
    +Login successful.
    +
    +You have access to 74 projects, the list has been suppressed. You can list all projects with 'oc projects'
    +
    +Using project "default".
    +
    +
    +
  2. +
  3. +

    Unless you choose to install it into the openshift-operators namespace, create the Namespace and Operator Group in it first.

    +
    +
    +
    +
    +
    $ cat <<EOF > rhods-ns.yaml
    +apiVersion: v1
    +kind: Namespace
    +metadata:
    +  annotations:
    +      openshift.io/display-name: "Red Hat OpenShift Data Science"
    +  labels:
    +    openshift.io/cluster-monitoring: 'true'
    +  name: redhat-ods-operator
    +spec: {}
    +EOF
    +
    +$ oc create -f rhods-ns.yaml
    +namespace/redhat-ods-operator created
    +
    +$ cat <<EOF > rhods-og.yaml
    +apiVersion: operators.coreos.com/v1
    +kind: OperatorGroup
    +metadata:
    +  name: redhat-ods-operator
    +  namespace: redhat-ods-operator
    +spec: {}
    +EOF
    +
    +$ oc create -f rhods-og.yaml
    +operatorgroup.operators.coreos.com/redhat-ods-operator created
    +
    +
    +
    +
    +
  4. +
  5. +

    Now create the operator’s subscription to start the installation.

    +
    +
    +
    +
    +
    $ cat <<EOF > rhods-subs.yaml
    +apiVersion: operators.coreos.com/v1alpha1
    +kind: Subscription
    +metadata:
    +  name: rhods-operator
    +  namespace: redhat-ods-operator
    +spec:
    +  channel: embedded (1)
    +  installPlanApproval: Manual (2)
    +  name: rhods-operator
    +  source: redhat-operators
    +  sourceNamespace: openshift-marketplace
    +EOF
    +
    +$ oc create -f rhods-subs.yaml
    +subscription.operators.coreos.com/rhods-operator created
    +
    +
    +
    + + + + + + + + + +
    1The update channel to install the operator from. To find all available channels see the the Finding Update Channels section.
    2Installplans will be approved manually.
    +
    +
    +
    +
  6. +
  7. +

    Approve the installation manually. Refer to the Approving Installation Manualy section for more information

    +
    +
    +
    $ oc get installplan -n redhat-ods-operator
    +NAME            CSV                     APPROVAL   APPROVED
    +install-qsrhj   rhods-operator.2.1.2   Manual   false
    +
    +$ oc patch installplan install-qsrhj --type merge -p '{"spec":{"approved":true}}' -n redhat-ods-operator
    +installplan.operators.coreos.com/install-qsrhj patched  (2)
    +
    +$ oc get installplan -n redhat-ods-operator
    +NAME            CSV                     APPROVAL   APPROVED
    +install-qsrhj   redhat-ods-operator   Manual     true  (3)
    +
    +
    +
  8. +
  9. +

    Check the installation progress using the operator’s status information. For more information see the Checking Installation Progress section.

    +
    +
    +
    $ oc get olm|grep ^clusterserviceversion|grep redhat-ods-operator
    +clusterserviceversion.../openshift-pipelines-operator...   Succeeded  (1)
    +
    +
    +
    + + + + + +
    1Make sure that the status is Succeeded
    +
    +
  10. +
  11. +

    Finally create your Openshift DataScience Cluster resource to configure your cluster.

    +
    +
    +
    cat <<EOF > rhods-cluster.yaml
    +apiVersion: datasciencecluster.opendatahub.io/v1
    +kind: DataScienceCluster
    +metadata:
    +  labels:
    +    app.kubernetes.io/created-by: rhods-operator
    +    app.kubernetes.io/instance: default
    +    app.kubernetes.io/managed-by: kustomize
    +    app.kubernetes.io/name: datasciencecluster
    +    app.kubernetes.io/part-of: rhods-operator
    +  name: default  (1)
    +spec:
    +  components:
    +    codeflare:
    +      managementState: Removed (2)
    +    dashboard:
    +      managementState: Managed (3)
    +    datasciencepipelines:
    +      managementState: Managed
    +    kserve:
    +      managementState: Removed
    +    modelmeshserving:
    +      managementState: Managed
    +    ray:
    +      managementState: Removed
    +    workbenches:
    +      managementState: Managed
    +EOF
    +
    +oc create -f rhods-cluster.yaml
    +
    +
    +
    + + + + + + + + + + + + + +
    1Name of the cluster
    2Use Removed for components that will not be installed.
    3Use Managed for components that will be installed.
    +
    +
  12. +
  13. +

    Now the cluster has been configured and you can check the contition of individual components of the Red Hat Openshift Data Science.

    +
    +
    +
    $ oc get DataScienceCluster default -o json| jq '.status.conditions'
    +...output ommited...
    +  {
    +    "lastHeartbeatTime": "2023-11-13T11:04:37Z",
    +    "lastTransitionTime": "2023-11-13T11:04:37Z",
    +    "message": "Component reconciled successfully",
    +    "reason": "ReconcileCompleted",
    +    "status": "True", (1)
    +    "type": "workbenchesReady" (2)
    +  }
    +...output ommited...
    +
    +
    +
    + + + + + + + + + +
    1Status of the condition
    2Type of the condition. Type workbenchesReady together with status True indicate that the Workbench component is ready.
    +
    +
  14. +
+
+
+ + + + + +
+ + +It may take some time for all the application pods to start hence the Red Hat Openshift Data Science dashboard may not be available immediately. You may check the condition of componens or alternatively you can check the status of the application pods in the redhat-ods-applications namespace. Once all pods are running and ready, you can open the dashboard in the Openshift Web Console. +
+
+
+
+
$ oc get pods -n redhat-ods-applications
+NAME                                               READY   STATUS              RESTARTS   AGE
+etcd-cc4d875c-8trld                                0/1     PodInitializing     0          7s
+modelmesh-controller-5749b94578-2j8nv              0/1     Running             0          7s
+modelmesh-controller-5749b94578-jcxc7              0/1     ContainerCreating   0          7s
+modelmesh-controller-5749b94578-rww94              0/1     ContainerCreating   0          7s
+notebook-controller-deployment-685bb8f9d6-6dtbh    0/1     Running             0          29s
+odh-model-controller-7d495b56cb-8pnn9              0/1     Running             0          7s
+odh-model-controller-7d495b56cb-8xh5h              0/1     Running             0          7s
+odh-model-controller-7d495b56cb-kcmqr              0/1     Running             0          7s
+odh-notebook-controller-manager-866b7cf859-2wf2j   1/1     Running             0          29s
+rhods-dashboard-7bd94f464f-7lvn8                   1/2     Running             0          47s
+rhods-dashboard-7bd94f464f-hksf6                   1/2     Running             0          47s
+rhods-dashboard-7bd94f464f-n5rbz                   1/2     Running             0          47s
+rhods-dashboard-7bd94f464f-pg984                   1/2     Running             0          47s
+rhods-dashboard-7bd94f464f-xd255                   1/2     Running             0          47s
+
+
+
diff --git a/rhods-admin/1.33/chapter2/index.html b/rhods-admin/1.33/chapter2/index.html index fa35f5c..8bcfefe 100644 --- a/rhods-admin/1.33/chapter2/index.html +++ b/rhods-admin/1.33/chapter2/index.html @@ -53,10 +53,10 @@

Red Hat OpenShift Data Science Adminis General Information about Installation @@ -163,7 +163,7 @@

Controlling User Access and Managing Resources

diff --git a/rhods-admin/1.33/chapter2/resources.html b/rhods-admin/1.33/chapter2/resources.html index 5ea4c54..3ad32af 100644 --- a/rhods-admin/1.33/chapter2/resources.html +++ b/rhods-admin/1.33/chapter2/resources.html @@ -53,10 +53,10 @@

Red Hat OpenShift Data Science Adminis General Information about Installation diff --git a/rhods-admin/1.33/chapter2/users.html b/rhods-admin/1.33/chapter2/users.html index 66f4d85..f75afef 100644 --- a/rhods-admin/1.33/chapter2/users.html +++ b/rhods-admin/1.33/chapter2/users.html @@ -53,10 +53,10 @@

Red Hat OpenShift Data Science Adminis General Information about Installation diff --git a/rhods-admin/1.33/chapter3/custom.html b/rhods-admin/1.33/chapter3/custom.html index 1c19152..c16ad7a 100644 --- a/rhods-admin/1.33/chapter3/custom.html +++ b/rhods-admin/1.33/chapter3/custom.html @@ -53,10 +53,10 @@

Red Hat OpenShift Data Science Adminis General Information about Installation diff --git a/rhods-admin/1.33/chapter3/index.html b/rhods-admin/1.33/chapter3/index.html index 6e65232..14acad5 100644 --- a/rhods-admin/1.33/chapter3/index.html +++ b/rhods-admin/1.33/chapter3/index.html @@ -53,10 +53,10 @@

Red Hat OpenShift Data Science Adminis General Information about Installation diff --git a/rhods-admin/1.33/index.html b/rhods-admin/1.33/index.html index 4238035..9cd78d1 100644 --- a/rhods-admin/1.33/index.html +++ b/rhods-admin/1.33/index.html @@ -52,10 +52,10 @@

Red Hat OpenShift Data Science Administra General Information about Installation

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