8. Cross-cutting Concepts

8.1 Domain Model and Business Logic

Domain-Driven Design Implementation

BookWorm follows Domain-Driven Design principles with clear domain boundaries and ubiquitous language throughout the system.

Domain Boundaries

Ubiquitous Language

Domain Term	Definition	Context
Book	A published work available for purchase	Catalog Domain
Order	A customer's request to purchase items	Ordering Domain
Basket	Temporary collection of items for purchase	Shopping Domain
Conversation	A chat session between participants	Communication Domain

8.2 Security Architecture

Authentication and Authorization

Security Policies

Security Aspect	Implementation	Standards
Authentication	OAuth 2.0 / OIDC with Keycloak	RFC 6749, RFC 6750
Authorization	Role-based access control (RBAC)	Custom policy framework
Data Encryption	TLS 1.3 in transit, AES-256 at rest	FIPS 140-2 compliance
API Security	JWT tokens, rate limiting, input validation	OWASP guidelines
Secrets Management	Azure Key Vault integration	Zero-trust principles

8.3 Performance and Scalability

Caching Strategy

Caching Policies

Cache Type	TTL	Use Case	Invalidation Strategy
Browser Cache	1 hour	Static assets, images	Version-based
CDN Cache	24 hours	Public content	Manual purge
API Response Cache	5-15 minutes	Catalog data, search results	Time-based + tag-based
Application Cache	30 minutes	User sessions, temporary data	Event-driven
Database Query Cache	Variable	Expensive queries	Data change triggers

Performance Optimizations

Optimization	Implementation	Benefit
Async Operations	Task-based programming	Non-blocking I/O operations
Connection Pooling	EF Core connection pooling	Reduced connection overhead
Pagination	Cursor-based pagination	Efficient large dataset handling
Compression	Gzip/Brotli response compression	Reduced bandwidth usage
Lazy Loading	On-demand data loading	Faster initial response times

8.4 Error Handling and Resilience

Error Handling Strategy

1. Centralized Exception Handling: Implement a global exception handler to catch unhandled exceptions and return standardized error responses.
2. Validation: Use data annotations and FluentValidation for request validation, returning 400 Bad Request responses for invalid input.
3. Logging: Log errors with sufficient context (e.g., user ID, request ID) to facilitate troubleshooting.
4. User-Friendly Messages: Avoid exposing internal error details to users; provide generic error messages instead.

Resilience Patterns

Pattern	Implementation	Use Case
Circuit Breaker	Polly library	External service failures
Retry Policies	Exponential backoff	Transient failures
Timeout Policies	Configurable timeouts	Long-running operations
Bulkhead Isolation	Separate thread pools	Fault isolation
Fallback Mechanisms	Graceful degradation	Service unavailability

8.5 Logging and Monitoring

Structured Logging

 builder.Logging.AddOpenTelemetry(logging =>
{
    logging.IncludeFormattedMessage = true;
    logging.IncludeScopes = true;
});

Log Correlation

Monitoring Metrics

Metric Category	Key Metrics	Alerting Thresholds
Performance	Response time, throughput, error rate	> 2s response, > 5% error rate
Infrastructure	CPU, memory, disk usage	> 80% utilization
Business	Orders/hour, revenue, conversion rate	-20% from baseline
Security	Failed logins, suspicious activity	> 10 failed attempts/minute

8.6 Observability with OpenTelemetry

OpenTelemetry Integration

8.7 Data Consistency and Transactions

Transaction Patterns

Pattern	Use Case	Implementation
ACID Transactions	Single service operations	Entity Framework transactions
Saga Pattern	Multi-service workflows	Orchestrated/Choreographed sagas
Eventual Consistency	Cross-domain updates	Event-driven synchronization
Optimistic Concurrency	Conflict resolution	Version-based conflict detection

API Standards

Aspect	Standard	Example
HTTP Methods	REST semantics	GET, POST, PUT, DELETE
Status Codes	HTTP standards	200, 201, 400, 404, 500
Resource Naming	Plural nouns	/books, /orders, /users
Error Format	RFC 7807	Problem Details for HTTP APIs
Date/Time	ISO 8601	2024-12-31T23:59:59Z