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Monolithic Application Architecture

This document outlines Bayat's standards and best practices for designing, developing, and maintaining monolithic applications.

Table of Contents

Overview

A monolithic architecture is a traditional unified model where the application is built as a single, indivisible unit. This document provides guidelines for effectively implementing monolithic applications at Bayat, recognizing that while microservices are often preferred for new large-scale projects, monolithic architectures remain valuable for many use cases.

When to Use Monolithic Architecture

Consider a monolithic approach when:

  • Small to medium-sized applications with limited complexity
  • Startups and MVPs where speed to market is critical
  • Single-team applications managed by a small development team
  • Limited expected growth in features or scale
  • Constrained resources for infrastructure management
  • Applications with significant cross-cutting concerns requiring tight coupling
  • Batch processing systems with sequential workflows
  • Simple CRUD applications with straightforward business logic

Architectural Principles

Key Principles

  • Simplicity: Keep the design as simple as possible
  • Cohesion: Group related functionality together
  • Low Coupling: Minimize dependencies between modules
  • Separation of Concerns: Divide the application into distinct features with minimal overlap
  • DRY (Don't Repeat Yourself): Avoid code duplication
  • SOLID Principles: Apply all SOLID principles throughout the codebase
  • Defense in Depth: Implement security at multiple layers
  • Fail Fast: Detect and handle errors as early as possible

Architecture Layers

Implement a clear layered architecture with well-defined responsibilities:

  1. Presentation Layer:

    • User interface components
    • API controllers
    • View models and DTOs

  2. Business Logic Layer:

    • Services
    • Domain entities
    • Business rules
    • Workflow orchestration

  3. Data Access Layer:

    • Repositories
    • Data mappers
    • ORM configuration
    • Query services

  4. Cross-Cutting Concerns:

    • Logging
    • Authentication
    • Authorization
    • Caching
    • Exception handling

Modular Design

Module Organization

  • Vertical Slicing: Organize by business capability/domain rather than technical layers
  • Bounded Context: Define clear boundaries between different business domains
  • Interface-Based Design: Define clear interfaces between modules
  • Dependency Management: Use dependency injection to manage component dependencies
  • Service Locator Anti-Pattern: Avoid service locator pattern in favor of DI

Module Communication

  • Well-Defined APIs: Modules should communicate through well-defined internal APIs
  • Event-Driven Communication: Consider using internal events for cross-module communication
  • Command Query Responsibility Segregation (CQRS): Separate read and write operations when beneficial
  • Mediator Pattern: Use mediator for cross-cutting operations

Code Organization

Project Structure

  • Feature-Based Organization: Group code by feature/domain, not by type
  • Consistent Naming Conventions: Follow language-specific conventions from our standards
  • Consistent File Organization: Standardize file and directory structures
  • Solution Organization: Organize Visual Studio solutions or equivalent by domain boundaries
  • Shared Code Management: Carefully manage shared libraries and utilities

Coding Standards

  • Follow Language-Specific Guidelines: Adhere to our language-specific coding standards
  • Documentation: Document public APIs, complex business logic, and design decisions
  • Code Style: Use consistent code formatting and style guides
  • Static Analysis: Implement static code analysis tools
  • Refactoring: Regularly refactor to maintain code quality

Database Design

Schema Design

  • Normalized Design: Follow normalization principles (typically 3NF) unless performance demands otherwise
  • Performance-Driven Denormalization: Document and justify any denormalization
  • Consistent Naming: Use consistent naming conventions for database objects
  • Versioning Strategy: Implement database migration/versioning strategy
  • Indexes: Design appropriate indexes based on query patterns

Data Access

  • ORM Usage: Prefer ORM tools for standard CRUD operations
  • Stored Procedures: Use stored procedures for complex data operations when appropriate
  • Query Performance: Optimize queries for performance
  • Connection Management: Implement proper connection pooling and management
  • Transactions: Use transactions appropriately to maintain data integrity

Scalability

Vertical Scaling

  • Resource Planning: Plan for CPU, memory, and disk requirements
  • Load Testing: Regularly load test to identify bottlenecks
  • Database Scaling: Implement database scaling strategies (read replicas, sharding when necessary)
  • Caching Strategy: Implement multi-level caching where appropriate

Horizontal Scaling

Despite monolithic architecture, design for horizontal scalability where possible:

  • Statelessness: Design application to be stateless where possible
  • Session Management: Use external session stores
  • File Storage: Use external file storage systems
  • Load Balancing: Design to work behind load balancers
  • Database Connection Management: Properly manage database connections for multiple instances

Performance Optimization

Application Performance

  • Profiling: Regularly profile the application to identify bottlenecks
  • Caching Strategy: Implement appropriate caching at multiple levels
    • Memory caching for frequently accessed data
    • Distributed caching for multi-instance deployments
    • Output caching for rendered content
  • Asynchronous Processing: Use async/await patterns for I/O-bound operations
  • Resource Pooling: Implement connection pooling and object pooling
  • Lazy Loading: Load resources only when needed

Front-end Performance

  • Minification: Minify and bundle static resources
  • Compression: Enable HTTP compression
  • CDN Integration: Use CDNs for static content delivery
  • Optimized Images: Optimize image size and format
  • Lazy Loading: Implement lazy loading for UI components

Testing

Testing Strategy

  • Unit Testing: Comprehensive unit tests for all business logic
  • Integration Testing: Test component interactions
  • UI/E2E Testing: Test complete user flows
  • Load Testing: Regular load testing to identify performance issues
  • Security Testing: Regular security assessments

Testing Best Practices

  • Test Pyramid: Follow the test pyramid approach (more unit tests, fewer E2E tests)
  • Test Independence: Tests should be independent and repeatable
  • Continuous Testing: Integrate automated tests in CI/CD pipeline
  • Test Coverage: Monitor and maintain high test coverage
  • Test Data Management: Implement proper test data management

Deployment

Deployment Process

  • CI/CD Pipeline: Implement automated build and deployment pipeline
  • Environment Parity: Ensure development, staging, and production environments are similar
  • Blue-Green Deployment: Consider blue-green deployment for zero-downtime updates
  • Rollback Strategy: Implement easy rollback mechanisms
  • Configuration Management: Externalize configuration from code

Build Optimization

  • Build Process: Optimize build process for speed
  • Artifact Management: Properly version and store build artifacts
  • Dependency Management: Carefully manage external dependencies

Monitoring and Maintenance

Observability

  • Logging: Implement structured logging across the application
  • Metrics Collection: Collect performance and business metrics
  • Distributed Tracing: Implement request tracing
  • Health Checks: Implement health check endpoints
  • Dashboards: Create monitoring dashboards for key metrics

Operational Considerations

  • Backup Strategy: Implement comprehensive backup procedures
  • Disaster Recovery: Document and test disaster recovery procedures
  • Incident Response: Establish clear incident response processes
  • Documentation: Maintain up-to-date operational documentation
  • Runbooks: Create operational runbooks for common tasks

Migration Strategies

Incremental Modernization

For existing monoliths that need modernization:

  • Strangler Pattern: Gradually replace monolith components
  • Anti-Corruption Layer: Use adapter layers to isolate legacy code
  • Parallel Development: Run old and new systems in parallel during transition
  • Feature Flags: Use feature flags to control migration
  • Data Migration Strategy: Carefully plan and execute data migration

Monolith to Microservices

When planning a transition to microservices:

  • Domain Analysis: Identify bounded contexts for service boundaries
  • Dependency Mapping: Map internal dependencies before decomposition
  • Incremental Extraction: Extract services one at a time
  • Shared Database Transition: Carefully manage transition away from shared database
  • API Gateway Introduction: Consider API gateway for managing client transitions

Anti-patterns to Avoid

  • Ball of Mud: Unstructured code without clear architecture
  • God Classes: Overly large classes with too many responsibilities
  • Spaghetti Code: Tangled, hard-to-maintain code
  • Feature Creep: Continuous addition of features without refactoring
  • Database as Integration Point: Using the database as the primary integration mechanism
  • Hardcoded Dependencies: Directly instantiating dependencies instead of injection
  • No Separation of Concerns: Mixing presentation, business, and data access logic
  • Dual-Write Problem: Writing to multiple data stores without transactional guarantees
  • Lack of Monitoring: Insufficient observability into application behavior

References