Platform & DevOps
Microsoft Azure

Secure Azure AI Application Platform

A production-minded Azure platform combining protected ingress, private service connectivity, managed application services, AI capabilities, and repeatable infrastructure delivery.

Anonymized architecture case study
Architecture diagram for a secure Azure AI application platform
Architecture view with client and environment identifiers removed.

Case Study Overview

An internet-facing AI application needed a reliable public entry point while keeping compute, data, containers, secrets, and model services on controlled paths. The platform also needed to remain operable and repeatable across environments.

Outcome

A clear platform blueprint that improves service isolation, operational visibility, and deployment consistency while keeping AI services inside the wider application security model.

Architecture Approach

  1. 1Place Azure Front Door and Web Application Firewall at the public edge for routing and request protection.
  2. 2Segment application and managed-service traffic with virtual networks, private endpoints, and private DNS.
  3. 3Use managed application, database, container, secret, AI, and monitoring services with explicit trust boundaries.
  4. 4Represent the platform as reusable Terraform modules so environment changes remain reviewable and repeatable.

Role & Scope

Solution architecture, security boundaries, and Terraform planning

Technology Stack

Azure Front Door
WAF
Azure VNet
Private Endpoint
Container Apps
MySQL
Key Vault
Azure AI Foundry
Azure Monitor
Terraform