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ENG-10137: Removes prereq and step about cert generation #390

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Aug 1, 2024
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ENG-10137: Removes prereq and step about cert generation #390

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16 changes: 0 additions & 16 deletions modules/running-distributed-data-science-workloads-disconnected-env.adoc
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,6 @@ To run a distributed data science workload in a disconnected environment, you mu
* You have installed {productname-long} and created a mirror image as described in link:{rhoaidocshome}{default-format-url}/installing_and_uninstalling_openshift_ai_self-managed_in_a_disconnected_environment[Installing and uninstalling {productname-short} Self-Managed in a disconnected environment].
* You can access the following software from the disconnected cluster:
** A Ray cluster image
** An image that includes the `openssl` package, for the creation of TLS certificates when creating Ray clusters
** The data sets and models to be used by the workload
** The Python dependencies for the workload, either in a Ray image or in your own Python Package Index (PyPI) server that is available from the disconnected cluster
* You have logged in to {productname-long}.
Expand All @@ -34,21 +33,6 @@ endif::[]
. In the `ClusterConfiguration` section of the notebook or pipeline, ensure that the `image` value specifies a Ray cluster image that you can access 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.
. In the CodeFlare Operator config map, ensure that the `kuberay:certGeneratorImage` value specifies an image that contains the `openssl` package, and that you can access the image from the disconnected environment.
The following example shows the default value provided by {productname-short}:
+
[source,bash]
----
kind: ConfigMap
apiVersion: v1
metadata:
name: codeflare-operator-config
namespace: redhat-ods-applications
data:
config.yaml: |
kuberay:
certGeneratorImage: "registry.redhat.io/ubi9@sha256:770cf07083e1c85ae69c25181a205b7cdef63c11b794c89b3b487d4670b4c328"
----
. If any of the Python packages required by the workload are not available in the Ray cluster, configure the Ray cluster to download the Python packages from a private PyPI server.
+
For example, set the `PIP_INDEX_URL` and `PIP_TRUSTED_HOST` environment variables for the Ray cluster, to specify the location of the Python dependencies, as shown in the following example:
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