This reference architecture demonstrates how to deploy a robust GenAI pipeline using Azure AI Foundry while adhering to strict security standards.
Highlights of this pattern
Zero-Trust Network Architecture
Achieving complete isolation by injecting the Orchestrator (ACA) and data layer into private subnets. This architecture eliminates public internet exposure, relying on strictly governed NSGs and subnet delegation to secure the perimeter.
Private Backbone Connectivity
Leveraging Azure Private Link to ensure all traffic between the Orchestrator, Azure OpenAI, and Vector Search traverses solely over the Microsoft backbone network—mitigating data exfiltration risks and meeting compliance mandates.
Identity-First Security
Replacing vulnerable keys with Microsoft Entra Workload ID. The GenAI pipeline authenticates via Managed Identities, enforcing granular Role-Based Access Control (RBAC) and adhereing to least-privilege principles.
Full-Stack AI Observability
Integrated Azure Monitor and Application Insights provide end-to-end visibility. Custom dashboards track LLM token usage (FinOps), request latency, and Content Safety violations to ensure operational reliability.
This is how you build a foundation for AI that is scalable, auditable, and secure by design.