AI067 Red Hat OpenShift AI Technical Overview — Lesson 2: Projects, Workbenches, Notebooks, Data Connections, and Collaboration

Learning Objectives

• Configure the main services, objects, and controls involved in projects, workbenches, and notebooks.
• Apply data connections and collaboration while preserving reviewable technical evidence.
• Recognize and correct the risk where a valid command creates the wrong outcome because variables, identity, or sequencing are incorrect.

Detailed Topics

• projects: apply the concept to an enterprise AI team evaluating OpenShift AI as a shared platform for governed model development and delivery, record the relevant settings or decisions, and explain the operational consequence.
• workbenches: apply the concept to an enterprise AI team evaluating OpenShift AI as a shared platform for governed model development and delivery, record the relevant settings or decisions, and explain the operational consequence.
• notebooks: apply the concept to an enterprise AI team evaluating OpenShift AI as a shared platform for governed model development and delivery, record the relevant settings or decisions, and explain the operational consequence.
• data connections: apply the concept to an enterprise AI team evaluating OpenShift AI as a shared platform for governed model development and delivery, record the relevant settings or decisions, and explain the operational consequence.
• collaboration: apply the concept to an enterprise AI team evaluating OpenShift AI as a shared platform for governed model development and delivery, record the relevant settings or decisions, and explain the operational consequence.

Instructor Demonstration

The instructor demonstrates projects, workbenches, notebooks, data connections, and collaboration by tracing the relevant architecture, commands, configuration, messages, and evidence. The walkthrough highlights how a valid command creates the wrong outcome because variables, identity, or sequencing are incorrect and shows how to isolate the cause without masking dependent issues.

Hands-On Exercise

Implement the core workflow and compare expected versus observed behavior for Projects, Workbenches, Notebooks, Data Connections, and Collaboration. Add verified outcomes to the OpenShift AI capability assessment, stakeholder map, governance requirements, and adoption roadmap.

1. Confirm the scope, versions, access, dependencies, and success criteria.
2. Perform the workflow while recording commands, settings, output, and platform events.
3. Test one expected case and one controlled exception specific to this lesson.
4. Retest the correction and document ownership, rollback, and follow-up actions.

Scenario Analysis

• Identify which dependency most strongly influences projects in the stated scenario.
• Compare two approaches for data connections and explain the security, reliability, and support trade-offs.
• Decide what evidence must be retained in the OpenShift AI capability assessment, stakeholder map, governance requirements, and adoption roadmap before operational acceptance.

Troubleshooting Guidance

Begin with the first observable difference from the expected result. Check configuration, permissions, sequencing, and functional behavior separately, then correlate logs, events, commands, and configuration history. Do not accept the initial assumption that a valid command creates the wrong outcome because variables, identity, or sequencing are incorrect; confirm the cause with a reproducible retest.

Validation Checklist

• The required configuration, permissions, sequencing, and functional behavior were checked and recorded.
• The normal path and a course-specific exception were tested.
• The OpenShift AI capability assessment, stakeholder map, governance requirements, and adoption roadmap links conclusions to commands, configuration, logs, or other objective evidence.
• Corrective actions, rollback steps, ownership, and handover notes are complete.

Lesson Outcome

Learners can apply Projects, Workbenches, Notebooks, Data Connections, and Collaboration, explain the observed Red Hat platform behavior, and support the result with a reviewable OpenShift AI capability assessment, stakeholder map, governance requirements, and adoption roadmap.