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Duration 14 hours
Course Outline
Foundations of LLMs and Agent Frameworks<\/p>
- The role of large language models in infrastructure automation<\/li>
- Core principles of multi-agent workflows<\/li>
- Applying AutoGen, CrewAI, and LangChain to DevOps scenarios<\/li>
Configuring LLM Agents for DevOps<\/p>
- Installing AutoGen and defining agent profiles<\/li>
- Integrating OpenAI APIs and alternative LLM providers<\/li>
- Establishing workspaces and CI/CD-ready environments<\/li>
Streamlining Test and Code Quality Processes<\/p>
- Utilising LLMs to generate unit and integration tests<\/li>
- Enforcing linting, commit rules, and code review standards via agents<\/li>
- Automating pull request summarisation and tagging<\/li>
Managing Alerts and Detecting Changes with LLMs<\/p>
- Creating responder agents for pipeline failure notifications<\/li>
- Interpreting logs and traces through language models<\/li>
- Identifying high-risk changes or misconfigurations proactively<\/li>
Orchestrating Multi-Agent Systems in DevOps<\/p>
- Role-based agent coordination (planner, executor, reviewer)<\/li>
- Implementing agent messaging loops and memory management<\/li>
- Incorporating human-in-the-loop controls for critical systems<\/li>
Ensuring Security, Governance, and Observability<\/p>
- Mitigating data exposure risks and ensuring LLM safety in infrastructure<\/li>
- Auditing agent actions and defining operational scope<\/li>
- Monitoring pipeline behaviour and collecting model feedback<\/li>
Practical Applications and Custom Scenarios<\/p>
- Designing agent workflows for incident response<\/li>
- Connecting agents with GitHub Actions, Slack, or Jira<\/li>
- Strategies for scaling LLM integration within DevOps<\/li>
Conclusion and Future Directions<\/p>
Requirements
- Proficiency with DevOps tooling and pipeline automation<\/li>
- Working knowledge of Python and Git-based workflows<\/li>
- Familiarity with LLMs or experience with prompt engineering<\/li>
Target Audience<\/p>
- Innovation engineers and leads of AI-integrated platforms<\/li>
- LLM developers specialising in DevOps or automation<\/li>
- DevOps professionals seeking to explore intelligent agent frameworks<\/li>
