Introduction¶
Welcome to the CI/CD for Agentic AI learning path. In this module, you will build a CI/CD pipeline that tests a Google ADK travel agent, captures Monocle traces on failure, and automatically creates GitHub issues assigned to AI coding agents for remediation.
What you will learn¶
- How to instrument a Google ADK agent with Monocle
- How to write agent tests using the MonocleValidator and Fluent API frameworks
- How to build GitHub Actions workflows that capture traces on failure
- How to auto-assign AI coding agents (Claude, Copilot) to investigate and fix failures
- How to integrate Okahu Cloud evaluations into CI/CD
Scenario¶
You are building a CI/CD pipeline for a travel booking agent built with Google ADK (Agent Development Kit). When tests fail, you want the pipeline to automatically create a GitHub issue with the full Monocle trace embedded, assign it to an AI coding agent, and have the agent investigate and fix the issue.
Architecture overview¶
graph TD
Push[Code Push / Manual Trigger] --> GHA[GitHub Actions]
GHA --> Test[Run Agent Tests]
Test -->|Pass| Done[Pipeline Succeeds]
Test -->|Fail| Collect[Collect Monocle Traces]
Collect --> Issue[Create GitHub Issue]
Issue --> Assign[Assign AI Coding Agent]
Assign --> Claude[Claude Code Agent]
Assign --> Copilot[GitHub Copilot]
Claude --> Fix[Investigate & Fix]
Copilot --> Fix
Source code¶
okahu-demos/adk-travel-agent-with-cicd
Time to complete¶
~45 minutes