What you'll learn

Building production AI backends requires more than calling an API. You need to understand how LLMs operate as stateless services, how Azure enforces rate limits, and how to design persistent storage for non-deterministic outputs. In this course, Strategic Foundations for Generative AI on Azure, you'll gain the ability to architect an LLM-backed pipeline using Azure managed services. First, you'll explore the Microsoft Foundry platform, differentiating between Foundry Tools and Foundry Models and understanding the stateless nature of LLM inference. Next, you'll discover how Azure enforces token-per-minute quotas and the strategies for designing resilient integrations using exponential backoff and request shaping. Then, you'll evaluate authentication approaches, contrasting API keys with Managed Identity for production environments. Finally, you'll assess architectural alternatives like Durable Functions and Power Automate alongside hardening layers such as Azure AI Content Safety for screening untrusted input before it reaches the LLM. When you're finished with this course, you'll have the skills and knowledge of Azure generative AI architecture needed to design and plan an end-to-end AI backend on Azure.