AI067 Red Hat OpenShift AI Technical Overview — Lesson 4: Use Cases, Operating Model, Skills, Risks, Value, and Adoption Roadmap

Learning Objectives

• Operate, troubleshoot, document, and improve use cases, operating model, and skills.
• Apply risks and value and adoption roadmap while preserving reviewable technical evidence.
• Recognize and correct the risk where the technical fix is successful but monitoring, rollback, ownership, or handover remains incomplete.

Detailed Topics

• use cases: 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.
• operating model: 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.
• skills: 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.
• risks and value: 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.
• adoption roadmap: 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 use cases, operating model, skills, risks, value, and adoption roadmap by tracing the relevant architecture, commands, configuration, messages, and evidence. The walkthrough highlights how the technical fix is successful but monitoring, rollback, ownership, or handover remains incomplete and shows how to isolate the cause without masking dependent issues.

Hands-On Exercise

Run an operational review and produce support-ready evidence for Use Cases, Operating Model, Skills, Risks, Value, and Adoption Roadmap. 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 use cases in the stated scenario.
• Compare two approaches for risks and value 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 monitoring, troubleshooting, rollback, ownership, and handover separately, then correlate logs, events, commands, and configuration history. Do not accept the initial assumption that the technical fix is successful but monitoring, rollback, ownership, or handover remains incomplete; confirm the cause with a reproducible retest.

Validation Checklist

• The required monitoring, troubleshooting, rollback, ownership, and handover 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 Use Cases, Operating Model, Skills, Risks, Value, and Adoption Roadmap, 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.