Try the Ansible playbook generation lab with Gemini and OpenAI

Summary

The official Visual Studio Code extension for Red Hat Ansible Automation Platform includes an automation coding assistant, formerly called Ansible Lightspeed. Initially integrated with IBM watsonx, the extension now supports Google Gemini and OpenAI-compatible endpoints through Red Hat AI. An updated interactive lab demonstrates these capabilities through an end-to-end scenario involving database installation and HTML landing page deployment across two nodes. Learners write natural language prompts to generate Ansible playbooks and roles, evaluate output, and utilize real-time automated linting and integrated documentation. By serving an open-source model through a preconfigured OpenAI-compatible endpoint, the refreshed environment removes external credential setup steps.

Context

The Ansible VS Code extension's automation coding assistant required hands-on demonstration of its expanded model support and a simplified workflow to replace lab setups that previously required leaving the environment to fetch credentials.

Approach / What changed

Red Hat updated the interactive lab hosted in code-server to connect to an open-source model using a preconfigured OpenAI-compatible endpoint, walking users through prompt creation, playbook generation, execution across two nodes, and role generation.

Takeaways

• The automation coding assistant in the Ansible VS Code extension supports model integrations with Google Gemini and OpenAI-compatible endpoints via Red Hat AI alongside IBM watsonx.
• The extension provides automatic linting on AI-generated playbooks and roles, with single-click documentation retrieval for unfamiliar modules and syntax.
• The updated lab leverages a preconfigured OpenAI-compatible endpoint hosting an open-source model to remove external credential onboarding steps.

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