🌍 Environment Management¶

Manage multiple environments (Dev/Test/Prod) with proper configuration, deployment strategies, and environment-specific settings.

📋 Table of Contents¶

Environment Strategy
Configuration Management
Deployment Process
Environment Variables
Best Practices
Summary

🏗️ Environment Strategy¶

Environment Setup¶

Environments:
├── Development (DEV)
│   ├── Data Factory: adf-project-dev
│   ├── Resource Group: rg-adf-dev
│   └── Purpose: Active development
├── Testing (TEST)
│   ├── Data Factory: adf-project-test
│   ├── Resource Group: rg-adf-test
│   └── Purpose: QA and validation
└── Production (PROD)
    ├── Data Factory: adf-project-prod
    ├── Resource Group: rg-adf-prod
    └── Purpose: Live workloads

⚙️ Configuration Management¶

ARM Template Parameters¶

{
  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentParameters.json#",
  "contentVersion": "1.0.0.0",
  "parameters": {
    "factoryName": {
      "value": "adf-project-prod"
    },
    "AzureSqlDatabase_connectionString": {
      "value": "Server=tcp:sql-prod.database.windows.net,1433;Database=salesdb;"
    },
    "AzureBlobStorage_accountName": {
      "value": "staprod"
    }
  }
}

Environment-Specific Parameters¶

{
  "dev": {
    "sqlServer": "sql-dev.database.windows.net",
    "storageAccount": "stadev",
    "keyVault": "kv-dev"
  },
  "test": {
    "sqlServer": "sql-test.database.windows.net",
    "storageAccount": "statest",
    "keyVault": "kv-test"
  },
  "prod": {
    "sqlServer": "sql-prod.database.windows.net",
    "storageAccount": "staprod",
    "keyVault": "kv-prod"
  }
}

🚀 Deployment Process¶

Pre-Production Checklist¶

Deployment Steps¶

Stop Triggers (Production)

# Stop all triggers
$triggers = Get-AzDataFactoryV2Trigger -ResourceGroupName "rg-adf-prod" -DataFactoryName "adf-project-prod"
$triggers | ForEach-Object { Stop-AzDataFactoryV2Trigger -ResourceGroupName "rg-adf-prod" -DataFactoryName "adf-project-prod" -Name $_.Name -Force }

Deploy ARM Template

az deployment group create \
  --resource-group "rg-adf-prod" \
  --template-file "ARMTemplateForFactory.json" \
  --parameters @ARMTemplateParametersForFactory.prod.json

Start Triggers (Production)

# Start all triggers
$triggers | ForEach-Object { Start-AzDataFactoryV2Trigger -ResourceGroupName "rg-adf-prod" -DataFactoryName "adf-project-prod" -Name $_.Name -Force }

📊 Environment Variables¶

Use Global Parameters¶

{
  "environment": {
    "dev": {
      "type": "string",
      "value": "development"
    },
    "test": {
      "type": "string",
      "value": "testing"
    },
    "prod": {
      "type": "string",
      "value": "production"
    }
  }
}

🎯 Best Practices¶

Environment Isolation¶

Separate subscriptions or resource groups
Different service principals per environment
Isolated networks (VNets)

Configuration Management¶

Store environment configs in Key Vault
Use ARM template parameters
Implement global parameters
Version control all configurations

Deployment Automation¶

Automated testing before deployment
Blue-green deployment strategy
Automated rollback capability
Deployment notifications

Security¶

Least privilege access per environment
Separate service principals
Environment-specific managed identities
Regular security audits

✅ Summary¶

Congratulations! You've completed the Azure Data Factory Tutorial Series.

What You've Learned¶

✅ ADF fundamentals and architecture
✅ Environment setup and configuration
✅ Integration runtime setup
✅ Multi-source data integration
✅ Secure connectivity patterns
✅ Pipeline development and orchestration
✅ Data transformation techniques
✅ Error handling and monitoring
✅ CI/CD implementation
✅ Environment management

Next Steps¶

Build Production Pipelines: Apply learnings to real projects
Explore Advanced Features: Azure Purview integration, Delta Lake
Join Community: Participate in forums and user groups
Continuous Learning: Stay updated with new features

Additional Resources¶

Feedback¶

We'd love to hear about your experience with this tutorial series!

GitHub Issues: Report problems or suggest improvements
Discussions: Share your implementations and ask questions
LinkedIn: Connect with the Azure Data Factory community

🎉 Tutorial Complete! You're now ready to build enterprise-scale data integration solutions with Azure Data Factory.

Module Progress: 18 of 18 complete

Tutorial Version: 1.0 Last Updated: January 2025