Managing Generative AI APIs with Azure API Management

As organizations rapidly adopt generative AI, managing the security, cost, and reliability of large language model APIs becomes a critical challenge. Developers and administrators need robust tools to control access, monitor usage, and prevent service overloads. This text-based course guides you through the process of configuring Azure API Management specifically for generative AI workloads. You will transition from basic gateway setups to advanced management strategies, ensuring your AI integrations are secure, cost-effective, and highly available. What you'll learn: Understand core API management concepts and foundational Azure gateway architecture; Configure rate limiting and throttling tailored for token-based generative AI usage; Implement security policies to protect sensitive model endpoints and manage API keys; Set up caching strategies to reduce latency and lower consumption costs; Design smart routing and circuit breaker patterns to handle API downtime and failovers; Monitor performance metrics and analyze usage patterns for AI workloads. The course begins with foundational definitions and key terminology before moving into step-by-step written guides and policy configuration examples. You will read detailed explanations and analyze configuration snippets to build a production-ready API gateway. This course is designed for beginners, developers, and IT professionals looking to manage AI services, with no prior experience in API management required. Start reading today to master the infrastructure behind modern generative AI applications.