Azure OpenAI Architecture: The Decisions That Actually Matter (Part 1) (opens in new tab)

Generative AI demos often succeed because they hide the hard parts of architecture. They usually run under ideal conditions: low, steady traffic, no sudden bursts, no competing teams, and minimal regulatory scrutiny. In production, however, Azure OpenAI systems face a very different reality – variable loads, service quotas, compliance constraints, evolving model versions, and the need for cost visibility. The difference between a great demo and a resilient production platform isn’t the model ...