AU374 Developing Advanced Automation with Red Hat Ansible Automation Platform — Lesson 1: Advanced Playbook Design, Data Structures, Filters, Lookups, and Error Handling

Learning Objectives

• Interpret the architecture, dependencies, and expected behavior of advanced playbooks, data structures, and filters.
• Apply lookups and error handling while preserving reviewable technical evidence.
• Recognize and correct the risk where a hidden prerequisite causes the first configuration step to produce an incomplete result.

Detailed Topics

• advanced playbooks: apply the concept to an automation engineering team building scalable, testable content for Ansible Automation Platform, record the relevant settings or decisions, and explain the operational consequence.
• data structures: apply the concept to an automation engineering team building scalable, testable content for Ansible Automation Platform, record the relevant settings or decisions, and explain the operational consequence.
• filters: apply the concept to an automation engineering team building scalable, testable content for Ansible Automation Platform, record the relevant settings or decisions, and explain the operational consequence.
• lookups: apply the concept to an automation engineering team building scalable, testable content for Ansible Automation Platform, record the relevant settings or decisions, and explain the operational consequence.
• error handling: apply the concept to an automation engineering team building scalable, testable content for Ansible Automation Platform, record the relevant settings or decisions, and explain the operational consequence.

Instructor Demonstration

The instructor demonstrates advanced playbook design, data structures, filters, lookups, and error handling by tracing the relevant architecture, commands, configuration, messages, and evidence. The walkthrough highlights how a hidden prerequisite causes the first configuration step to produce an incomplete result and shows how to isolate the cause without masking dependent issues.

Hands-On Exercise

Build a baseline and capture the initial state for Advanced Playbook Design, Data Structures, Filters, Lookups, and Error Handling. Add verified outcomes to the advanced automation collection, execution environment definition, test pipeline, and controller-ready release package.

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 advanced playbooks in the stated scenario.
• Compare two approaches for lookups and explain the security, reliability, and support trade-offs.
• Decide what evidence must be retained in the advanced automation collection, execution environment definition, test pipeline, and controller-ready release package before operational acceptance.

Troubleshooting Guidance

Begin with the first observable difference from the expected result. Check architecture, access, dependencies, and starting conditions separately, then correlate logs, events, commands, and configuration history. Do not accept the initial assumption that a hidden prerequisite causes the first configuration step to produce an incomplete result; confirm the cause with a reproducible retest.

Validation Checklist

• The required architecture, access, dependencies, and starting conditions were checked and recorded.
• The normal path and a course-specific exception were tested.
• The advanced automation collection, execution environment definition, test pipeline, and controller-ready release package 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 Advanced Playbook Design, Data Structures, Filters, Lookups, and Error Handling, explain the observed Red Hat platform behavior, and support the result with a reviewable advanced automation collection, execution environment definition, test pipeline, and controller-ready release package.