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RHEcosystemAppEng
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ds-project-setup

Automate Data Science Project setup on OpenShift AI with namespaces, S3 connections, pipelines, and model serving.

48|31|Updated Feb 2, 2026
Search Tags:#project setup#namespace#Data Science#OpenShift AI#S3 data connection#pipeline server
One-click install
npx skills add https://github.com/RHEcosystemAppEng/agentic-plugins --skill ds-project-setup
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ds-project-setup
Source: https://github.com/RHEcosystemAppEng/agentic-plugins/tree/main/rh-ai-engineer/skills/ds-project-setup
Command: npx skills add https://github.com/RHEcosystemAppEng/agentic-plugins --skill ds-project-setup

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires rhoai, openshift, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies the setup of Data Science Projects on OpenShift AI by automating namespace creation, S3 data connections, pipeline server configuration, and model serving enablement.

Core Features & Use Cases

  • Namespace Setup: Automates the creation of a new namespace with proper labels and dashboard integration.
  • S3 Data Connections: Adds S3-compatible data connections to the project for data storage.
  • Pipeline Server Configuration: Sets up the pipeline server with external storage.
  • Model Serving Enablement: Enables model serving on the project with single or multi-model serving mode.
  • Use Case: Ideal for bootstrapping a complete data science project environment before deploying models or workbenches.

Quick Start

Create a Data Science Project called 'my-project' with S3 data connections and model serving enabled.

Frequently Asked Questions about ds-project-setup

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up a Data Science Project on OpenShift AI?▼

To set up a Data Science Project on OpenShift AI, you can automate namespace creation, configure S3 data connections, set up the pipeline server, and enable model serving. This automates the complete project environment bootstrap.

Can I configure S3 data connections for my OpenShift AI pipeline server?▼

Yes, you can configure S3-compatible data connections and external storage when setting up your pipeline server on OpenShift AI. This automates data storage integration for your Data Science Project.

Do I need RHOAI tools to enable model serving on OpenShift AI?▼

Yes, RHOAI tools are required for project management and OpenShift for pipeline server and data connections to enable model serving. These dependencies are required to automate the project setup.

What is the best way to bootstrap a data science environment before deploying models?▼

The best way to bootstrap a data science environment is automating namespace creation, S3 data connections, pipeline server configuration, and model serving enablement. This prepares the complete OpenShift AI project workspace.

Does OpenShift AI support single and multi-model serving modes for Data Science Projects?▼

Yes, OpenShift AI supports enabling model serving on Data Science Projects with both single and multi-model serving modes. This configuration is automated during the project setup process.

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