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

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: 'MyServiceConnection'
      scriptType: 'bash'
      scriptLocation: 'inlineScript'
      inlineScript: |
        az deployment group create \
          --resource-group rg-myapp-dev \
          --template-file infra/main.bicep \
          --parameters environment=dev

Step 6: Security Review

Validate security posture before production:

• Identity: Entra ID (Azure AD) with RBAC, Managed Identity for service-to-service auth — never store credentials in code
• Secrets: Key Vault for all secrets, certificates, and connection strings
• Network: NSGs on all subnets, Private Endpoints for PaaS services, Application Gateway with WAF
• Encryption: TLS 1.2+ in transit, Azure-managed or customer-managed keys at rest
• Monitoring: Microsoft Defender for Cloud enabled, Azure Policy for guardrails
• Compliance: Azure Policy assignments for SOC 2 / HIPAA / ISO 27001 initiatives

If deployment fails:

1. Check the deployment status:

   az deployment group show \
     --resource-group rg-myapp-dev \
     --name main \
     --query 'properties.error'
   

2. Review Activity Log for RBAC or policy errors.
3. Validate the Bicep template before deploying:

   az bicep build --file main.bicep
   az deployment group validate \
     --resource-group rg-myapp-dev \
     --template-file main.bicep
   

Common failure causes:

• RBAC permission errors — verify the deploying principal has Contributor on the resource group
• Resource provider not registered — run

  az provider register --namespace Microsoft.Web

• Naming conflicts — Azure resource names are often globally unique (storage accounts, web apps)
• Quota exceeded — request quota increase via Azure Portal > Subscriptions > Usage + quotas

Tools

architecture_designer.py

Generates architecture pattern recommendations based on requirements.

python scripts/architecture_designer.py \
  --app-type web_app \
  --users 50000 \
  --requirements '{"budget_monthly_usd": 1000, "compliance": ["HIPAA"]}' \
  --json

Input: Application type, expected users, JSON requirements Output: Recommended pattern, service stack, cost estimate, pros/cons

cost_optimizer.py

Analyzes Azure resource configurations for cost savings.

python scripts/cost_optimizer.py --config resources.json --json

Input: JSON file with current Azure resource inventory Output: Recommendations for:

• Idle resource removal
• VM and database right-sizing
• Reserved Instance purchases
• Storage tier transitions
• Unused public IPs and load balancers

bicep_generator.py

Generates Bicep template scaffolds from architecture type.

python scripts/bicep_generator.py --arch-type microservices --output main.bicep

Output: Production-ready Bicep templates with:

• Managed Identity (no passwords)
• Key Vault integration
• Diagnostic settings for Azure Monitor
• Network security groups
• Tags for cost allocation

Quick Start

Web App Architecture (< $100/month)

Ask: "Design an Azure web app for a startup with 5000 users"

Result:
- App Service (B1 Linux) for the application
- Azure SQL Serverless for relational data
- Azure Blob Storage for static assets
- Front Door (free tier) for CDN and routing
- Key Vault for secrets
- Estimated: $40-80/month

Microservices on AKS ($500-2000/month)

Ask: "Design a microservices architecture on Azure for a SaaS platform with 50k users"

Result:
- AKS cluster with 3 node pools (system, app, jobs)
- API Management for gateway and rate limiting
- Cosmos DB for multi-model data
- Service Bus for async messaging
- Azure Monitor + Application Insights for observability
- Multi-zone deployment

Serverless Event-Driven (< $200/month)

Ask: "Design an event-driven backend for processing orders"

Result:
- Azure Functions (Consumption plan) for compute
- Event Grid for event routing
- Service Bus for reliable messaging
- Cosmos DB for order data
- Application Insights for monitoring
- Estimated: $30-150/month depending on volume

Data Pipeline ($300-1500/month)

Ask: "Design a data pipeline for ingesting 10M events/day"

Result:
- Event Hubs for ingestion
- Stream Analytics or Functions for processing
- Data Lake Storage Gen2 for raw data
- Synapse Analytics for warehouse
- Power BI for dashboards

Input Requirements

Provide these details for architecture design:

JSON Format:

{
  "application_type": "saas_platform",
  "expected_users": 10000,
  "requests_per_second": 100,
  "budget_monthly_usd": 500,
  "team_size": 3,
  "azure_experience": "intermediate",
  "compliance": ["SOC2"],
  "availability_sla": "99.9%"
}

Anti-Patterns

Output Formats

Architecture Design

• Pattern recommendation with rationale
• Service stack diagram (ASCII)
• Monthly cost estimate and trade-offs

IaC Templates

• Bicep: Recommended — first-party, module support, clean syntax
• ARM JSON: Generated from Bicep when needed
• Terraform HCL: Multi-cloud compatible using azurerm provider

Cost Analysis

• Current spend breakdown with optimization recommendations
• Priority action list (high/medium/low) and implementation checklist

Cross-References

engineering-team/aws-solution-architect

engineering-team/gcp-cloud-architect

engineering-team/senior-devops

engineering/terraform-patterns

engineering/ci-cd-pipeline-builder

Reference Documentation

references/architecture_patterns.md

references/service_selection.md

references/best_practices.md