May 3
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In this video, I walk you through the enterprise AI gateway pattern on Azure, built around Azure API Management. - Why calling Azure OpenAI directly breaks in production - How APIM becomes a control plane between your apps and AI backends - Eliminating API keys entirely using Managed Identity (with Bicep) - Enforcing per-app token quotas using azure-openai-token-limit policy - Semantic caching with Azure Managed Redis to reduce token spend - Backend pools with priority routing and circuit breakers (with Bicep) - The full architecture: apps → APIM policies → AI backends ───────────────────────── TIMESTAMPS ───────────────────────── 0:00 — Introduction 0:50 — The Problem in a nutshell 1:36 — APIM as an AI gateway 2:42 — Security pattern 5:08 — Token limits, per-app quotas + semantic caching 6:53 — Resiliency: backend pools, circuit breakers 8:18 — The full production architecture 14:30 — Closing ───────────────────────── CONNECT WITH ME: ───────────────────────── - GitHub: [https://github.com/brayaON] - Twitter/X: [https://x.com/brayaON20] - LinkedIn: [https://www.linkedin.com/in/bof23402] - Website: [https://boflabs.dev/] ───────────────────────── TAGS: ───────────────────────── #foundry #azureaifoundry #aiservices #azuredevops #devops #cloudcomputing #azureai #azureopenai #apimanagement #cloudarchitecture