ENG-6697: Fixes broken links, prereqs, YAML refs, and adds note about…

modules/configuring-quota-management-for-distributed-workloads.adoc

@@ -21,6 +21,13 @@ ifdef::cloud-service[]
 * You have downloaded and installed the OpenShift command-line interface (CLI). See link:https://docs.openshift.com/dedicated/cli_reference/openshift_cli/getting-started-cli.html#installing-openshift-cli[Installing the OpenShift CLI] (Red Hat OpenShift Dedicated) or link:https://docs.openshift.com/rosa/cli_reference/openshift_cli/getting-started-cli.html#installing-openshift-cli[Installing the OpenShift CLI] (Red Hat OpenShift Service on AWS).
 endif::[]
 
+ifndef::upstream[]
+* You have enabled the required distributed workloads components as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/#configuring-the-distributed-workloads-components_distributed-workloads[Configuring the distributed workloads components].
+endif::[]
+ifdef::upstream[]
+* You have enabled the required distributed workloads components as described in link:{odhdocshome}/working_with_distributed_workloads/#configuring-the-distributed-workloads-components_distributed-workloads[Configuring the distributed workloads components].
+endif::[]
+
 * You have sufficient resources. In addition to the base {productname-short} resources, you need 1.6 vCPU and 2 GiB memory to deploy the distributed workloads infrastructure.
 
 * The resources are physically available in the cluster.

modules/configuring-the-codeflare-operator.adoc

@@ -14,6 +14,13 @@ ifdef::cloud-service[]
 * You have logged in to OpenShift with the `cluster-admin` role.
 endif::[]
 
+ifndef::upstream[]
+* You have enabled the required distributed workloads components as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/#configuring-the-distributed-workloads-components_distributed-workloads[Configuring the distributed workloads components].
+endif::[]
+ifdef::upstream[]
+* You have enabled the required distributed workloads components as described in link:{odhdocshome}/working_with_distributed_workloads/#configuring-the-distributed-workloads-components_distributed-workloads[Configuring the distributed workloads components].
+endif::[]
+
 
 .Procedure
 ifdef::upstream,self-managed[]
@@ -33,7 +40,7 @@ endif::[]
 . Search for the *codeflare-operator-config* config map, and click the config map name to open the *ConfigMap details* page.
 
 . Click the *YAML* tab to show the config map specifications.
-. In the `data` > `config.yaml` > `kuberay` section, you can edit the following entries:
+. In the `data:config.yaml:kuberay` section, you can edit the following entries:
 +
 ingressDomain::
 This configuration option is null (`ingressDomain: ""`) by default.

modules/configuring-the-distributed-workloads-components.adoc

@@ -38,13 +38,6 @@ Instead, users must configure the Ray job specification to set `submissionMode=H
 * You have access to the data sets and models that the distributed workload uses.
 * You have access to the Python dependencies for the distributed workload.
 
-ifndef::upstream[]
-* You have created the required Kueue resources as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/working-with-distributed-workloads_distributed-workloads#configuring-quota-management-for-distributed-workloads_distributed_workloads[Configuring quota management for distributed workloads].
-endif::[]
-ifdef::upstream[]
-* You have created the required Kueue resources as described in link:{odhdocshome}/working_with_distributed_workloads/#configuring-quota-management-for-distributed-workloads_distributed_workloads[Configuring quota management for distributed workloads].
-endif::[]
-
 ifndef::upstream[]
 * You have removed any previously installed instances of the CodeFlare Operator, as described in the Knowledgebase solution link:https://access.redhat.com/solutions/7043796[How to migrate from a separately installed CodeFlare Operator in your data science cluster].
 endif::[]
@@ -138,7 +131,9 @@ endif::[]
 . Click the *Data Science Cluster* tab.
 . Click the default instance name (for example, *default-dsc*) to open the instance details page.
 . Click the *YAML* tab to show the instance specifications.
-. In the `spec.components` section, ensure that the `managementState` field is set correctly for the required components depending on whether the distributed workload is run from a pipeline or notebook or both, as shown in the following table.
+. Enable the required distributed workloads components.
+In the `spec:components` section, set the `managementState` field correctly for the required components.
+The list of required components depends on whether the distributed workload is run from a pipeline or notebook or both, as shown in the following table.
 +
 .Components required for distributed workloads
 [cols="34,20,20,26"]

modules/running-distributed-data-science-workloads-disconnected-env.adoc

@@ -18,7 +18,7 @@ To run a distributed data science workload in a disconnected environment, you mu
 * You have created a data science project.
 
 .Procedure
-. Configure the disconnected data science cluster to run distributed workloads as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/working-with-distributed-workloads_distributed-workloads#configuring-distributed-workloads_distributed-workloads[Configuring distributed workloads].
+. Configure the disconnected data science cluster to run distributed workloads as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/#configuring-distributed-workloads_distributed-workloads[Configuring distributed workloads].
 . In the `ClusterConfiguration` section of the notebook or pipeline, ensure that the `image` value specifies a Ray cluster image that can be accessed from the disconnected environment:
 * Notebooks use the Ray cluster image to create a Ray cluster when running the notebook.
 * Pipelines use the Ray cluster image to create a Ray cluster during the pipeline run.
@@ -33,7 +33,7 @@ PIP_TRUSTED_HOST: pypi-notebook.apps.mylocation.com
 where
 * `PIP_INDEX_URL` specifies the base URL of your private PyPI server (the default value is https://pypi.org).
 * `PIP_TRUSTED_HOST` configures Python to mark the specified host as trusted, regardless of whether that host has a valid SSL certificate or is using a secure channel.
-. Run the distributed data science workload, as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/working-with-distributed-workloads_distributed-workloads#running-distributed-data-science-workloads-from-notebooks_distributed-workloads[Running distributed data science workloads from notebooks] or link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/working-with-distributed-workloads_distributed-workloads#running-distributed-data-science-workloads-from-ds-pipelines_distributed-workloads[Running distributed data science workloads from data science pipelines].
+. Run the distributed data science workload, as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/#running-distributed-data-science-workloads-from-notebooks_distributed-workloads[Running distributed data science workloads from notebooks] or link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/#running-distributed-data-science-workloads-from-ds-pipelines_distributed-workloads[Running distributed data science workloads from data science pipelines].
 
 .Verification
 The notebook or pipeline run completes without errors:

modules/running-distributed-data-science-workloads-from-ds-pipelines.adoc

@@ -1,6 +1,6 @@
 :_module-type: PROCEDURE
 
-[id="running-distributed-data-science-workloads-from-ds-pipeline_{context}"]
+[id="running-distributed-data-science-workloads-from-ds-pipelines_{context}"]
 = Running distributed data science workloads from data science pipelines
 
 [role='_abstract']
@@ -15,14 +15,21 @@ ifdef::cloud-service[]
 endif::[]
 
 ifndef::upstream[]
-* You have created the required Kueue resources as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/working-with-distributed-workloads_distributed-workloads#configuring-quota-management-for-distributed-workloads_distributed_workloads[Configuring quota management for distributed workloads].
+* You have access to a data science cluster that is configured to run distributed workloads as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/#configuring-distributed-workloads_distributed-workloads[Configuring distributed workloads].
 endif::[]
 ifdef::upstream[]
-* You have created the required Kueue resources as described in link:{odhdocshome}/working_with_distributed_workloads/#configuring-quota-management-for-distributed-workloads_distributed_workloads[Configuring quota management for distributed workloads].
+* You have access to a data science cluster that is configured to run distributed workloads as described in link:{odhdocshome}/working_with_distributed_workloads/#configuring-distributed-workloads_distributed-workloads[Configuring distributed workloads].
+endif::[]
+
+ifndef::upstream[]
+* You have created the required Kueue resources as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/#configuring-quota-management-for-distributed-workloads_distributed-workloads[Configuring quota management for distributed workloads].
+endif::[]
+ifdef::upstream[]
+* You have created the required Kueue resources as described in link:{odhdocshome}/working_with_distributed_workloads/#configuring-quota-management-for-distributed-workloads_distributed-workloads[Configuring quota management for distributed workloads].
 endif::[]
 
 ifndef::upstream[]
-* Optional: You have defined a _default_ local queue for the Ray cluster by creating a `LocalQueue` resource and adding the following annotation to the configuration details for that `LocalQueue` resource, as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/working-with-distributed-workloads_distributed-workloads#configuring-quota-management-for-distributed-workloads_distributed_workloads[Configuring quota management for distributed workloads]:
+* Optional: You have defined a _default_ local queue for the Ray cluster by creating a `LocalQueue` resource and adding the following annotation to the configuration details for that `LocalQueue` resource, as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/#configuring-quota-management-for-distributed-workloads_distributed-workloads[Configuring quota management for distributed workloads]:
 +
 [source,bash]
 ----
@@ -35,7 +42,7 @@ If you do not create a default local queue, you must specify a local queue in ea
 ====
 endif::[]
 ifdef::upstream[]
-* Optional: You have defined a _default_ local queue for the Ray cluster by creating a `LocalQueue` resource and adding the following annotation to the configuration details for that `LocalQueue` resource, as described in link:{odhdocshome}/working_with_distributed_workloads/#configuring-quota-management-for-distributed-workloads_distributed_workloads[Configuring quota management for distributed workloads]:
+* Optional: You have defined a _default_ local queue for the Ray cluster by creating a `LocalQueue` resource and adding the following annotation to the configuration details for that `LocalQueue` resource, as described in link:{odhdocshome}/working_with_distributed_workloads/#configuring-quota-management-for-distributed-workloads_distributed-workloads[Configuring quota management for distributed workloads]:
 +
 [source,bash]
 ----
@@ -48,13 +55,6 @@ If you do not create a default local queue, you must specify a local queue in ea
 ====
 endif::[]
 
-ifndef::upstream[]
-* You have access to a data science cluster that is configured to run distributed workloads as described in link:{rhoaidocshome}{default-format-url}/working_with_distributed_workloads/working-with-distributed-workloads_distributed-workloads#configuring-distributed-workloads_distributed-workloads[Configuring distributed workloads].
-endif::[]
-ifdef::upstream[]
-* You have access to a data science cluster that is configured to run distributed workloads as described in link:{odhdocshome}/working_with_distributed_workloads/#configuring-distributed-workloads_distributed-workloads[Configuring distributed workloads].
-endif::[]
-
 * You have access to S3-compatible object storage.
 * You have logged in to {productname-long}.
 * You have created a data science project.
@@ -175,6 +175,10 @@ if __name__ == '__main__':
 <2> Authenticates with the cluster by using values that you specify when creating the pipeline run
 // Commenting out second part of callout 2 until RHOAIENG-880 is fixed
 //; you can omit this section if the Ray cluster is configured to use the same namespace as the data science project
+[NOTE]
+----
+If your cluster uses self-signed certificates, include `ca-cert-path=__<path>__` in the `TokenAuthentication` parameter list, where `__<path>__` is the path to the cluster-wide Certificate Authority (CA) bundle that contains the self-signed certificates.
+----
 <3> Specifies the Ray cluster configuration: replace these example values with the values for your Ray cluster
 <4> Specifies the location of the Ray cluster image: if using a disconnected environment, replace the default value with the location for your environment
 <5> Specifies the local queue to which the Ray cluster will be submitted: you can omit this line if you configured a default local queue
@@ -209,10 +213,10 @@ ifdef::upstream[]
 endif::[]
 
 ifndef::upstream[]
-. When the pipeline run is complete, confirm that it is included in the list of triggered pipeline runs, as described in link:{rhoaidocshome}{default-format-url}/working_on_data_science_projects/working-with-data-science-pipelines_ds-pipelines#viewing-triggered-pipeline-runs_ds-pipelines[Viewing triggered pipeline runs].
+. When the pipeline run is complete, confirm that it is included in the list of triggered pipeline runs, as described in link:{rhoaidocshome}{default-format-url}/working_on_data_science_projects/working-with-data-science-pipelines_ds-pipelines#viewing-the-details-of-a-pipeline-run_ds-pipelines[Viewing the details of a pipeline run].
 endif::[]
 ifdef::upstream[]
-. When the pipeline run is complete, confirm that it is included in the list of triggered pipeline runs, as described in link:{odhdocshome}/working_on_data_science_projects/#viewing-triggered-pipeline-runs_ds-pipelines[Viewing triggered pipeline runs].
+. When the pipeline run is complete, confirm that it is included in the list of triggered pipeline runs, as described in link:{odhdocshome}/working_on_data_science_projects/#viewing-the-details-of-a-pipeline-run_ds-pipelines[Viewing the details of a pipeline run].
 endif::[]