azure-aigateway

Centralized AI gateway routing directs traffic across multiple Azure OpenAI endpoints to enforce policies, apply auditing, and ensure observable operation. You specify model endpoints, routing criteria, and compliance needs to control model access.

LLM gateway governance applies policy enforcement, token budgets, and auditing to multi-model AI traffic. You need it when managing multiple Azure OpenAI deployments requires SLA governance, compliance tracking, and risk-controlled rollouts.

Yes, a centralized AI gateway enforces token budgets and compliance rules across LLM endpoints. By specifying compliance needs and cost models, the gateway ensures secure, observable operation for all routed AI traffic.

Configure your AI gateway by providing model endpoints, routing criteria, and governance policies in an activation request. The gateway then applies these rules to route traffic and observe routing behavior across deployments.

Yes, the gateway supports canary and blue-green deployment rollouts for Azure OpenAI models. This enables risk-controlled rollouts and SLA governance, allowing you to test new model versions before full traffic routing.

Routing AI traffic through a centralized gateway provides observability and auditing for multi-model deployments. This approach ensures SLA governance by monitoring throughput, cost models, and routing behavior across all endpoints.