Introduction
Cloud administrators and DevOps engineers spend significant time on repetitive tasks. Deploying environments, validating compliance, and generating documentation follow predictable patterns. These responsibilities are time-intensive, and troubleshooting configurations adds to the burden.
Suppose you're a cloud administrator at a mid-sized company. Every week, your team receives requests for new Azure updates. The requests vary in architecture: a web application with a database, a networking fix, or a containerized microservices setup. Each request involves the same sequence of steps: gather requirements, assess the architecture, write infrastructure-as-code templates, deploy resources, and create documentation. You have automated parts of this workflow with scripts and templates. You use AI assistants to help draft code faster. Even so, you still coordinate these steps manually. You copy outputs from one tool into another and catch errors between stages.
In this module, you explore how agentic DevOps transforms this workflow. You learn the progression from manual operations through scripted automation and AI-assisted prompts to multi-agent orchestration. You examine the building blocks that make agents work: agent definitions, skills, instructions, and prompts. You also discover how to compose them into pipelines that handle end-to-end infrastructure tasks autonomously.
By the end of this module, you're able to describe how AI agents can orchestrate traditional ops tasks and design multi-agent workflows that reduce manual coordination in your infrastructure operations.
Note
We recognize that different people like to learn in different ways. You can choose to complete this module in video-based format or you can read the content as text and images. The text contains greater detail than the videos, so in some cases you might want to refer to it as supplemental material to the video presentation.