* Update azure-architecture-autopilot: 19 new service types (72 total) + advisor improvements - Added service types: apim, service_bus, logic_apps, event_grid, container_apps, postgresql, mysql, load_balancer, nat_gateway, expressroute, sentinel, data_explorer, signalr, notification_hub, spring_apps, static_web_app, digital_twins, backup - Updated phase1-advisor prompt with improved guidance - Synced icons.py updates Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: regenerate README docs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: whoniiii <whoniiii@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Azure Architecture Autopilot
Design → Diagram → Bicep → Deploy — all from natural language
Azure Architecture Autopilot designs Azure infrastructure from natural language,
generates interactive diagrams, produces modular Bicep templates, and deploys — all through conversation.
It also scans existing resources, visualizes them as architecture diagrams, and refines them on the fly.
↑ Auto-generated interactive diagram — drag, zoom, click for details, export to PNG
↑ Real Azure resources deployed from the generated Bicep templates
How It Works • Features • Prerequisites • Usage • Architecture
🔄 How It Works
Path A: "Build me a RAG chatbot on Azure"
↓
🎨 Design → 🔧 Bicep → ✅ Review → 🚀 Deploy
Path B: "Analyze my current Azure resources"
↓
🔍 Scan → 🎨 Modify → 🔧 Bicep → ✅ Review → 🚀 Deploy
| Phase | Role | What Happens |
|---|---|---|
| 0 | 🔍 Scanner | Scans existing Azure resources via az CLI → auto-generates architecture diagram |
| 1 | 🎨 Advisor | Interactive design through conversation — asks targeted questions with smart defaults |
| 2 | 🔧 Generator | Produces modular Bicep: main.bicep + modules/*.bicep + .bicepparam |
| 3 | ✅ Reviewer | Compiles with az bicep build, checks security & best practices |
| 4 | 🚀 Deployer | validate → what-if → preview diagram → create (5-step mandatory sequence) |
✨ Features
| Feature | Description | |
|---|---|---|
| 📦 | Zero Dependencies | 605+ Azure icons bundled — no pip install, works offline |
| 🎨 | Interactive Diagrams | Drag-and-drop HTML with zoom, click details, PNG export |
| 🔍 | Resource Scanning | Analyze existing Azure infra → auto-generate architecture diagrams |
| 💬 | Natural Language | "It's slow", "reduce costs", "add security" → guided resolution |
| 📊 | Live Verification | API versions, SKUs, model availability fetched from MS Docs in real-time |
| 🔒 | Secure by Default | Private Endpoints, RBAC, managed identity — no secrets in files |
| ⚡ | Parallel Preload | Next-phase info loaded while waiting for user input |
| 🌐 | Multi-Language | Auto-detects user language — responds in English, Korean, or any language |
⚙️ Prerequisites
| Tool | Required | Install |
|---|---|---|
| GitHub Copilot CLI | ✅ | Install guide |
| Azure CLI | ✅ | winget install Microsoft.AzureCLI / brew install azure-cli |
| Python 3.10+ | ✅ | winget install Python.Python.3.12 / brew install python |
No additional packages required — the diagram engine is bundled in
scripts/.
🤖 Recommended Models
| Models | Notes | |
|---|---|---|
| 🏆 Best | Claude Opus 4.5 / 4.6 | Most reliable for all 5 phases |
| ✅ Recommended | Claude Sonnet 4.5 / 4.6 | Best cost-performance balance |
| ⚠️ Minimum | Claude Sonnet 4, GPT-5.1+ | May skip steps in complex architectures |
🚀 Usage
Path A — Build new infrastructure
"Build a RAG chatbot with Foundry and AI Search"
"Create a data platform with Databricks and ADLS Gen2"
"Deploy Fabric + ADF pipeline with private endpoints"
"Set up a microservices architecture with AKS and Cosmos DB"
Path B — Analyze & modify existing resources
"Analyze my current Azure infrastructure"
"Scan rg-production and show me the architecture"
"What resources are in my subscription?"
Then modify through conversation:
"Add 3 VMs to this architecture"
"The Foundry endpoint is slow — what can I do?"
"Reduce costs — downgrade AI Search to Basic"
"Add private endpoints to all services"
📂 Output Structure
<project-name>/
├── 00_arch_current.html ← Scanned architecture (Path B)
├── 01_arch_diagram_draft.html ← Design diagram
├── 02_arch_diagram_preview.html ← What-if preview
├── 03_arch_diagram_result.html ← Deployment result
├── main.bicep ← Orchestration
├── main.bicepparam ← Parameter values
└── modules/
└── *.bicep ← Per-service modules
📁 Architecture
SKILL.md ← Lightweight router (~170 lines)
│
├── scripts/ ← Embedded diagram engine
│ ├── generator.py ← Interactive HTML generator
│ ├── icons.py ← 605+ Azure icons (Base64 SVG)
│ └── cli.py ← CLI entry point
│
└── references/ ← Phase instructions + patterns
├── phase0-scanner.md ← 🔍 Resource scanning
├── phase1-advisor.md ← 🎨 Architecture design
├── bicep-generator.md ← 🔧 Bicep generation
├── bicep-reviewer.md ← ✅ Code review
├── phase4-deployer.md ← 🚀 Deployment pipeline
├── service-gotchas.md ← Required properties & PE mappings
├── azure-common-patterns.md ← Security & naming patterns
├── azure-dynamic-sources.md ← MS Docs URL registry
├── architecture-guidance-sources.md
└── ai-data.md ← AI/Data service domain pack
Self-contained —
SKILL.mdis a lightweight router. All phase logic lives inreferences/. The diagram engine is embedded inscripts/with no external dependencies.
📊 Supported Services (70+ types)
All Azure services supported. AI/Data services have optimized templates; others are auto-looked up from MS Docs.
Key types: ai_foundry · openai · ai_search · storage · adls · keyvault · fabric · databricks · aks · vm · app_service · function_app · cosmos_db · sql_server · postgresql · mysql · synapse · adf · apim · service_bus · logic_apps · event_grid · event_hub · container_apps · app_insights · log_analytics · firewall · front_door · load_balancer · expressroute · sentinel · redis · iot_hub · digital_twins · signalr · acr · bastion · vpn_gateway · data_explorer · document_intelligence ...
📄 License
MIT © Jeonghoon Lee


