Modern AI applications rely on far more than a model endpoint. They need secure deployment, resilient data layers, event-driven integration, careful configuration, and clear operational insight. This guide frames those demands through the Microsoft Azure services measured by AI-200, helping readers connect exam objectives with the decisions cloud developers face when building production-ready solutions.




The journey starts with container images, ACR tasks, App Service, Container Apps, KEDA, and AKS, then moves into Cosmos DB, PostgreSQL, pgvector, Redis, and retrieval-augmented generation patterns. It continues through Service Bus, Event Grid, Azure Functions, Key Vault, App Configuration, OpenTelemetry, Azure Monitor, Application Insights, and KQL, with scenarios, reviews, and exam tips that clarify how the pieces work together.




Readers finish with a practical view of how to choose services, secure identities and secrets, manage scale, design vector search, handle messages, deploy serverless APIs, and investigate logs and traces. By the end of this book, they can approach AI-200 questions with stronger judgment and apply the same reasoning to Azure development work.