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Deploying Azure OpenAI via Bicep: Key Considerations & Lab Setup

· 15 min read
Craig Dempsey
Cloud Devops Engineer @ Digital Reflections

Introduction​

Azure OpenAI enables organizations to leverage powerful AI models such as GPT-4o, o3-mini, and Whisper for a variety of use cases, from chatbots to code generation and beyond. However, deploying Azure OpenAI via Infrastructure as Code (IaC) using Bicep requires careful planning to ensure a scalable, cost-effective, and secure deployment.

In this article, we’ll set up a simple lab environment to explore the key concepts behind deploying Azure OpenAI with Bicep. This will help us gain a deeper understanding of the service’s deployment types, regional availability, quota limitations, and model options. By the end, we’ll have a working Azure OpenAI deployment with a few models to experiment with helping us plan more advanced deployments in the future.