Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to LLMs and Agent Frameworks
- The role of large language models in infrastructure automation.
- Core concepts underlying multi-agent workflows.
- Application of AutoGen, CrewAI, and LangChain in DevOps scenarios.
Configuring LLM Agents for DevOps Tasks
- Installation of AutoGen and setup of agent profiles.
- Integration with OpenAI API and alternative LLM providers.
- Configuration of workspaces and CI/CD-compatible environments.
Automating Test and Code Quality Processes
- Using LLMs to generate unit and integration tests.
- Enforcing linting, commit standards, and code review guidelines via agents.
- Automation of pull request summarization and tagging.
LLM Agents for Alert Management and Change Detection
- Designing responder agents for pipeline failure alerts.
- Analysis of logs and traces using language models.
- Proactive identification of high-risk changes or misconfigurations.
Multi-Agent Coordination in DevOps
- Role-based orchestration of agents (planner, executor, reviewer).
- Management of agent messaging loops and memory states.
- Designing human-in-the-loop mechanisms for critical systems.
Security, Governance, and Observability
- Managing data exposure and ensuring LLM safety within infrastructure.
- Auditing agent actions and limiting operational scope.
- Monitoring pipeline behavior and incorporating model feedback.
Real-World Applications and Custom Scenarios
- Creating agent workflows for incident response.
- Integration of agents with GitHub Actions, Slack, or Jira.
- Best practices for scaling LLM integration within DevOps.
Summary and Future Directions
Requirements
- Practical experience with DevOps tooling and pipeline automation.
- Proficiency in Python and Git-based workflows.
- Foundational understanding of LLMs or prior exposure to prompt engineering.
Target Audience
- Innovation engineers and leads managing AI-integrated platforms.
- LLM developers focused on DevOps or automation domains.
- DevOps professionals seeking to explore intelligent agent frameworks.
