Creating your project and pipeline server

As a preliminary step, each of you is going to

Create a Data Science project
- this will help keep your things together
Create a Data Connection
- we need that for the pipeline server to store its artifacts
Deploy a Data Science Pipeline Server
- we will need one, and it’s better to create it from the start
Launch a Workbench
- we will use it to review content and notebooks
Clone the git repo into your Workbench
- this contains all the code from the prototype

The instructions below will guide you through these steps. Follow them carefully.

Create a project

First, in the OpenShift AI Dashboard application, navigate to the Data Science Projects menu on the left:
Create a project with the same name as your user id
- You have been assigned a unique user ID: userX
- You need to now create a project with the exact same name: userX
  
  Your assigned user is userX. Don’t mess that up or things will break later on
Leave the resource name unchanged
Optionally, enter your first and last name in the description of the project.
It should look like this:

It should NOT be userX like in the screenshot. (for you, X should be a number instead)

Create a Data Connection for the pipeline server

We have deployed an instance of Minio in the cluster to act as a simple Object Storage for our purposes.
You will need to Add data connection that points to it.
Here is the information you need to enter:
- Name:
  Shared Minio - pipelines
- Access Key:
  minio
- Secret Key:
  minio123
- Endpoint:
  http://minio.ic-shared-minio.svc.cluster.local:9000/
- Region:
  none
- Bucket:
  userX
  Once again, the bucket you will use has to match with the user ID you were provided
The result should look like:

Create a Pipeline Server

It is highly recommended to create your pipeline server before creating a workbench. So let’s do that now!

In your Data Science Project (DSP), click on Create a pipeline Server
Select the Data Connection created earlier (Shared Minio - pipelines) and click the Configure button:
When your pipeline server is ready, your screen will look like the following:

At this point, your pipeline server is ready and deployed.

You need to wait until that screen is ready. If it’s still spinning, wait for it to complete. If you continue and create your workbench before the pipeline server is ready, your workbench will not be able to submit pipelines to it.