customize

Azure OpenAI deployment customization involves configuring model version, SKU, capacity, and RAI policy through an interactive guided flow. This process validates capacity ranges and SKU compatibility to ensure repeatable, error-free configurations across environments.

Yes, Azure OpenAI deployments support cross-region spillover when capacity is unavailable. The guided customization workflow configures cross-region fallback, dynamic quota, and priority processing to maintain availability for production-grade setups.

Yes, the Azure OpenAI guided deployment workflow supports PTU deployments, dev/test environments, and performance-tuned production setups. It allows full customization control over dynamic quota, priority processing, and spillover configurations tailored to each environment.

An RAI policy in Azure OpenAI deployment defines content filtering rules for responsible AI usage. During the guided customization workflow, you configure this policy alongside model version, SKU, and capacity to enforce content safety across development and production environments.

You validate SKU compatibility and capacity ranges for Azure OpenAI models by using a guided deployment customization workflow. This process automatically enforces correct configurations and validates capacity limits, preventing errors before finalizing deployments.