What you'll learn:
- Deploy and scale Azure AI Agents on Azure Container Apps with real-world production patterns.
- Implement autoscaling, revisions, and secrets management to handle enterprise workloads.
- Integrate Azure OpenAI, storage, and event-driven triggers into containerized AI agent workflows.
- Design a production-ready architecture that balances cost, performance, and scalability.
- Troubleshoot, monitor, and optimize Azure Container Apps for AI workloads in production.
Building AI agents is exciting — but getting them from “it works on my machine” to running reliably in production is the real challenge. This course, Productionizing Azure AI Agents with Azure Container Apps (ACA), is designed to help you bridge that gap.
You’ll start by understanding how Azure Container Apps provides a serverless, container-native platform that makes running AI agents at scale simple. From there, we’ll dive into deploying Azure AI Agents, integrating them with Azure OpenAI and Azure AI Foundry, and managing workloads in a production environment.
Key topics include:
Deploying AI agents into Azure Container Apps with best practices.
Using autoscaling, secrets, and revisions to ensure secure and scalable deployments.
Integrating event-driven triggers, storage, and APIs into your AI workflows.
Monitoring, troubleshooting, and optimizing for performance and cost efficiency.
By the end of this course, you’ll know how to design, deploy, and scale AI agents that are enterprise-ready — with the same tools used by modern cloud teams.
This course is perfect for AI developers, cloud engineers, and DevOps professionals who want hands-on experience with productionizing AI. Whether you’re building prototypes with Azure OpenAI or managing workloads for a team, this course will give you the skills and confidence to run AI agents in the cloud — the right way.
