Service Layer
The Service Layer provides application services and cross-cutting concerns that support business operations while maintaining clear separation from domain logic. These services implement the application layer patterns in the Onion Architecture.
Components
Blob Storage Services
Data Processing Services
Architecture Role in DDD & Onion Architecture
The Service Layer implements the Application Layer in the Onion Architecture, orchestrating business operations and providing external integrations:
┌─────────────────────────────────────────────────────────────────┐
│ 🌐 Presentation Layer │
│ (Controllers, API Endpoints) │
│ │
│ Uses: Application services for file uploads, data processing │
└─────────────────────────┬───────────────────────────────────────┘
│
┌─────────────────────────┴───────────────────────────────────────┐
│ 🎯 Application Layer │
│ (Use Cases, Application Services) │
│ │
│ 🔧 DKNet.Svc.BlobStorage.* - File storage operations │
│ 📊 DKNet.Svc.Transformation - Data processing pipelines │
│ 🎭 Orchestrates domain operations with external services │
└─────────────────────────┬───────────────────────────────────────┘
│
┌─────────────────────────┴───────────────────────────────────────┐
│ 💼 Domain Layer │
│ (Entities, Aggregates, Domain Services) │
│ │
│ No direct dependencies on service implementations │
│ May define service contracts/interfaces │
└─────────────────────────┬───────────────────────────────────────┘
│
┌─────────────────────────┴───────────────────────────────────────┐
│ 🗄️ Infrastructure Layer │
│ (Data Access, External APIs) │
│ │
│ Implements: Concrete service implementations │
│ Integrates: AWS S3, Azure Storage, Local file system │
└─────────────────────────────────────────────────────────────────┘
Key Design Patterns Implemented
1. Provider Pattern
- Abstractions: Define service contracts independent of implementation
- Multiple Providers: Support different storage backends (AWS, Azure, Local)
- Configuration-Driven: Select providers through configuration
- Pluggable Architecture: Easy to add new providers
2. Adapter Pattern
- Storage Adapters: Uniform interface for different storage systems
- Technology Abstraction: Hide provider-specific implementation details
- Consistent API: Same operations across all storage providers
- Error Handling: Consistent error handling across providers
3. Strategy Pattern
- Transformation Strategies: Different algorithms for data processing
- Runtime Selection: Choose transformation strategy based on data type
- Extensible Design: Easy to add new transformation strategies
- Pipeline Processing: Chain multiple transformations together
4. Façade Pattern
- Simplified Interface: Hide complex subsystem interactions
- Service Orchestration: Coordinate multiple operations
- Cross-Cutting Concerns: Handle logging, validation, error handling
- Business-Focused API: Operations expressed in business terms
DDD Implementation Benefits
1. Application Services
- Orchestrate domain operations without containing business logic
- Handle cross-cutting concerns like file storage and data transformation
- Coordinate between multiple aggregates and external systems
- Maintain transaction boundaries and consistency
2. Technology Independence
- Domain layer remains unaware of specific storage or processing technologies
- Easy to switch between different providers based on requirements
- Support for hybrid scenarios (different providers for different use cases)
- Testability through abstraction and mocking
3. Cross-Cutting Concerns
- File validation and security handled at service layer
- Data transformation pipelines support business rule implementation
- Monitoring and logging integrated into service operations
- Error handling and retry policies implemented consistently
4. Integration Patterns
- Support for event-driven architectures through async operations
- Integration with domain events for file processing workflows
- Support for bulk operations and batch processing scenarios
- Caching and performance optimization at service layer
Onion Architecture Benefits
1. Dependency Inversion
- Application layer defines service contracts
- Infrastructure layer implements concrete services
- Domain layer is protected from external technology concerns
- Easy to mock services for testing
2. Separation of Concerns
- File storage separated from business logic
- Data transformation isolated from domain rules
- External integrations handled at appropriate layer
- Clear boundaries between layers
3. Testability
- Service abstractions enable comprehensive unit testing
- Integration tests can use different providers (in-memory, local)
- Domain logic can be tested independently of external services
- Easy to simulate various failure scenarios
4. Flexibility
- Support for multiple cloud providers simultaneously
- Runtime configuration of storage strategies
- Easy migration between different storage solutions
- Support for multi-tenant scenarios with different storage per tenant
Service Categories
1. File Storage Services
- Abstract Operations: Save, retrieve, list, delete, check existence
- Metadata Management: File size, content type, modification dates
- Access Control: Public URLs, expiration times, permissions
- Validation: File size limits, extension restrictions, security checks
- Token Processing: Extract and resolve tokens in templates
- Format Conversion: Currency, date-time, boolean transformations
- Pipeline Processing: Chainable transformation operations
- Validation: Type-safe transformations with error handling
3. Cross-Cutting Services
- Configuration Management: Provider selection and options
- Logging and Monitoring: Comprehensive operation tracking
- Error Handling: Consistent error responses and recovery
- Performance Optimization: Caching, connection pooling, retry policies
Integration Patterns
1. Domain Event Integration
public class DocumentProcessingService
{
public async Task ProcessDocumentAsync(DocumentUploadedEvent evt)
{
// Save document using blob service
var location = await _blobService.SaveAsync(evt.DocumentData);
// Transform document data
var transformedData = await _transformationService.ProcessAsync(evt.Metadata);
// Update domain entity
var document = await _documentRepository.GetByIdAsync(evt.DocumentId);
document.SetProcessingComplete(location, transformedData);
}
}
2. Multi-Provider Configuration
public void ConfigureServices(IServiceCollection services)
{
// Configure multiple storage providers
services.Configure<BlobServiceOptions>("AWS", options => {
options.Provider = "S3";
options.ConnectionString = awsConfig;
});
services.Configure<BlobServiceOptions>("Azure", options => {
options.Provider = "AzureBlob";
options.ConnectionString = azureConfig;
});
// Register provider factory
services.AddSingleton<IBlobServiceFactory, BlobServiceFactory>();
}
3. Pipeline Processing
public class DataProcessingPipeline
{
public async Task<ProcessedData> ProcessAsync(RawData input)
{
return await _transformationService
.ExtractTokens(input)
.ValidateTokens()
.ResolveTokens()
.FormatOutput()
.ExecuteAsync();
}
}
- Async Operations: All service operations support cancellation tokens
- Streaming Support: Large file processing with streaming APIs
- Bulk Operations: Efficient batch processing capabilities
- Connection Pooling: Optimized connections to external services
- Caching Integration: Support for distributed caching patterns
- Retry Policies: Resilient operations with configurable retry logic
Security Features
- File Validation: Comprehensive file type and size validation
- Access Control: Support for temporary URLs and expiration
- Encryption: Support for encryption at rest and in transit
- Audit Logging: Comprehensive audit trails for compliance
- Input Sanitization: Protection against malicious file uploads