Running a script to install local object storage buckets and create connections

For convenience, run a script (provided in the following procedure) that automatically completes these tasks:

Creates a Minio instance in your project.
Creates two storage buckets in that Minio instance.
Generates a random user id and password for your Minio instance.
Creates two connections in your project, one for each bucket and both using the same credentials.
Installs required network policies for service mesh functionality.

The script is based on a guide for deploying Minio.

The Minio-based Object Storage that the script creates is not meant for production usage.

If you want to connect to your own storage, see Creating connections to your own S3-compatible object storage.

Prerequisites

You must know the OpenShift resource name for your data science project so that you run the provided script in the correct project. To get the project’s resource name:

In the OpenShift AI dashboard, select Data Science Projects and then click the ? icon next to the project name. A text box appears with information about the project, including its resource name:

The following procedure describes how to run the script from the OpenShift console. If you are knowledgeable in OpenShift and can access the cluster from the command line, instead of following the steps in this procedure, you can use the following command to run the script:

oc apply -n <your-project-name/> -f https://github.com/rh-aiservices-bu/fraud-detection/raw/main/setup/setup-s3.yaml

Procedure

In the OpenShift AI dashboard, click the application launcher icon and then select the OpenShift Console option.
In the OpenShift console, click + in the top navigation bar.
Select your project from the list of projects.
Verify that you selected the correct project.

Copy the following code and paste it into the Import YAML editor.

This code gets and applies the setup-s3-no-sa.yaml file.

---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: demo-setup
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: demo-setup-edit
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: edit
subjects:
  - kind: ServiceAccount
    name: demo-setup
---
apiVersion: batch/v1
kind: Job
metadata:
  name: create-s3-storage
spec:
  selector: {}
  template:
    spec:
      containers:
        - args:
            - -ec
            - |-
              echo -n 'Setting up Minio instance and connections'
              oc apply -f https://github.com/rh-aiservices-bu/fraud-detection/raw/main/setup/setup-s3-no-sa.yaml
          command:
            - /bin/bash
          image: image-registry.openshift-image-registry.svc:5000/openshift/tools:latest
          imagePullPolicy: IfNotPresent
          name: create-s3-storage
      restartPolicy: Never
      serviceAccount: demo-setup
      serviceAccountName: demo-setup

Click Create.

Verification

In the OpenShift console, you should see a "Resources successfully created" message and the following resources listed:
- demo-setup
- demo-setup-edit
- create-s3-storage
In the OpenShift AI dashboard:
1. Select Data Science Projects and then click the name of your project, Fraud detection.
2. Click Connections. You should see two connections listed: My Storage and Pipeline Artifacts.

Next steps

If you want to complete the pipelines section of this workshop, go to Enabling data science pipelines.

Otherwise, skip to Creating a workbench.