/azure-cloud-architect

name: "azure-cloud-architect"
description: "Design Azure architectures for startups and enterprises. Use when asked to design Azure infrastructure, create Bicep/ARM templates, optimize Azure costs, set up Azure DevOps pipelines, or migrate to Azure. Covers AKS, App Service, Azure Functions, Cosmos DB, and cost optimization."

Azure Cloud Architect

Design scalable, cost-effective Azure architectures for startups and enterprises with Bicep infrastructure-as-code templates.

---

Workflow

Step 1: Gather Requirements

Collect application specifications:

- Application type (web app, mobile backend, data pipeline, SaaS, microservices)
- Expected users and requests per second
- Budget constraints (monthly spend limit)
- Team size and Azure experience level
- Compliance requirements (GDPR, HIPAA, SOC 2, ISO 27001)
- Availability requirements (SLA, RPO/RTO)
- Region preferences (data residency, latency)

Step 2: Design Architecture

Run the architecture designer to get pattern recommendations:

python scripts/architecture_designer.py \
  --app-type web_app \
  --users 10000 \
  --requirements '{"budget_monthly_usd": 500, "compliance": ["SOC2"]}'

**Example output:**

{
  "recommended_pattern": "app_service_web",
  "service_stack": ["App Service", "Azure SQL", "Front Door", "Key Vault", "Entra ID"],
  "estimated_monthly_cost_usd": 280,
  "pros": ["Managed platform", "Built-in autoscale", "Deployment slots"],
  "cons": ["Less control than VMs", "Platform constraints", "Cold start on consumption plans"]
}

Select from recommended patterns:

• **App Service Web**: Front Door + App Service + Azure SQL + Redis Cache
• **Microservices on AKS**: AKS + Service Bus + Cosmos DB + API Management
• **Serverless Event-Driven**: Functions + Event Grid + Service Bus + Cosmos DB
• **Data Pipeline**: Data Factory + Synapse Analytics + Data Lake Storage + Event Hubs

See `references/architecture_patterns.md` for detailed pattern specifications.

**Validation checkpoint:** Confirm the recommended pattern matches the team's operational maturity and compliance requirements before proceeding to Step 3.

Step 3: Generate IaC Templates

Create infrastructure-as-code for the selected pattern:

# Web app stack (Bicep)
python scripts/bicep_generator.py --arch-type web-app --output main.bicep

**Example Bicep output (core web app resources):**

@description('The environment name')
param environment string = 'dev'

@description('The Azure region for resources')
param location string = resourceGroup().location

@description('The application name')
param appName string = 'myapp'

// App Service Plan
resource appServicePlan 'Microsoft.Web/serverfarms@2023-01-01' = {
  name: '${environment}-${appName}-plan'
  location: location
  sku: {
    name: 'P1v3'
    tier: 'PremiumV3'
    capacity: 1
  }
  properties: {
    reserved: true // Linux
  }
}

// App Service
resource appService 'Microsoft.Web/sites@2023-01-01' = {
  name: '${environment}-${appName}-web'
  location: location
  properties: {
    serverFarmId: appServicePlan.id
    httpsOnly: true
    siteConfig: {
      linuxFxVersion: 'NODE|20-lts'
      minTlsVersion: '1.2'
      ftpsState: 'Disabled'
      alwaysOn: true
    }
  }
  identity: {
    type: 'SystemAssigned'
  }
}

// Azure SQL Database
resource sqlServer 'Microsoft.Sql/servers@2023-05-01-preview' = {
  name: '${environment}-${appName}-sql'
  location: location
  properties: {
    administrators: {
      azureADOnlyAuthentication: true
    }
    minimalTlsVersion: '1.2'
  }
}

resource sqlDatabase 'Microsoft.Sql/servers/databases@2023-05-01-preview' = {
  parent: sqlServer
  name: '${appName}-db'
  location: location
  sku: {
    name: 'GP_S_Gen5_2'
    tier: 'GeneralPurpose'
  }
  properties: {
    autoPauseDelay: 60
    minCapacity: json('0.5')
  }
}

> Full templates including Front Door, Key Vault, Managed Identity, and monitoring are generated by `bicep_generator.py` and also available in `references/architecture_patterns.md`.

**Bicep is the recommended IaC language for Azure.** Prefer Bicep over ARM JSON templates: Bicep compiles to ARM JSON, has cleaner syntax, supports modules, and is first-party supported by Microsoft.

Step 4: Review Costs

Analyze estimated costs and optimization opportunities:

python scripts/cost_optimizer.py \
  --config current_resources.json \
  --json

**Example output:**

{
  "current_monthly_usd": 2000,
  "recommendations": [
    { "action": "Right-size SQL Database GP_S_Gen5_8 to GP_S_Gen5_2", "savings_usd": 380, "priority": "high" },
    { "action": "Purchase 1-year Reserved Instances for AKS node pools", "savings_usd": 290, "priority": "high" },
    { "action": "Move Blob Storage to Cool tier for objects >30 days old", "savings_usd": 65, "priority": "medium" }
  ],
  "total_potential_savings_usd": 735
}

Output includes:

• Monthly cost breakdown by service
• Right-sizing recommendations
• Reserved Instance and Savings Plan opportunities
• Potential monthly savings

Step 5: Configure CI/CD

Set up Azure DevOps Pipelines or GitHub Actions with Azure:

# GitHub Actions — deploy Bicep to Azure
name: Deploy Infrastructure
on:
  push:
    branches: [main]

permissions:
  id-token: write
  contents: read

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - uses: azure/login@v2
        with:
          client-id: ${{ secrets.AZURE_CLIENT_ID }}
          tenant-id: ${{ secrets.AZURE_TENANT_ID }}
          subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}

      - uses: azure/arm-deploy@v2
        with:
          resourceGroupName: rg-myapp-dev
          template: ./infra/main.bicep
          parameters: environment=dev

# Azure DevOps Pipeline
trigger:
  branches:
    include:
      - main

pool:
  vmImage: 'ubuntu-latest'

steps:
  - task: AzureCLI@2
    inputs:
      azureSubscription: 'MyServiceConnec