This section provides information about the GPT-RAG infrastructure models. It includes an overview of the GPT-RAG/Simple Architecture (NoSecure) and GPT-RAG/Zero Trust architectures. The connectivity components and AI workloads involved in each architecture are described. Additionally, there is an architecture deep dive section that explains the data ingestion, orchestrator, and app front-end components of the system. There are also technical references related to the Architecture.
Connectivity Components:
- Azure Virtual Network (vnet) to Secure Data Flow (Isolated, Internal inbound & outbound connections).
- Azure Front Door (LB L7) + Web Application Firewall (WAF) to Secure Internet Facing Components.
- Bastion (RDP/SSH over TLS), secure remote desktop access solution for VMs in the virtual network.
- Jumpbox, a secure jump host to access VMs in private subnets.
AI Workloads:
- Azure Open AI, a managed AI service for running advanced language models like GPT-4.
- Private DNS Zones for name resolution within the virtual network and between VNets.
- Cosmos DB, a globally distributed, multi-model database service to support AI applications with Analytical Storage enabled for future usage.
- Web applications in Azure Web App.
- Azure AI services for building intelligent applications.
- High Availability & Disaster Recovery Ready Solution.
- Audit Logs, Monitoring & Observability (App Insight)
- Continuous Operational Improvement
1 Data ingestion Optimizes data preparation for Azure OpenAI
2 Orchestrator The system's dynamic backbone ensuring scalability and a consistent user experience
3 App Front-End Built with Azure App Services and the Backend for Front-End pattern, offers a smooth and scalable user interface