Automating DevOps Workflows with AI Agents on Azure

As software systems grow more complex, traditional DevOps workflows can become bottlenecks. Integrating artificial intelligence into your pipelines allows you to automate repetitive tasks, resolve incidents faster, and optimize your entire development lifecycle. This text-based course guides you through the foundational concepts of agentic DevOps, showing you how to leverage AI assistants to boost productivity and system reliability. You will learn how to design, configure, and manage AI-driven workflows that assist with code generation, pipeline orchestration, and site reliability engineering. What you'll learn: - Understand the core principles of agentic DevOps and how AI agents differ from traditional automation - Configure GitHub Copilot to accelerate code writing, unit testing, and infrastructure-as-code creation - Explore Azure DevOps MCP Server to connect AI models with your development repositories - Apply AI-driven site reliability engineering patterns to automate incident response and log analysis - Design effective prompts tailored for DevOps tasks, ensuring accurate and secure AI-generated outputs - Practice troubleshooting pipeline failures and optimizing deployment configurations using written scenarios You will start with the essential terminology of AI agents and DevOps before moving into practical text-based guides on tool integration. The material transitions from basic setup to real-world operational scenarios, ensuring you build a solid conceptual and practical foundation. This course is designed for beginners, system administrators, and junior developers who want to understand the intersection of AI and modern operations. No prior experience with AI agents is required, though a basic familiarity with cloud concepts is helpful. Start reading today to transform your operational workflows with the power of intelligent automation.