Architecture is about making decisions that make future changes easier, not harder. I've worked on codebases where adding a feature took days because of poor architecture, and I've worked on systems where changes were straightforward because the architecture supported them.
Separation of Concerns: The Foundation
Every module, class, or function should have one reason to change. This principle—the Single Responsibility Principle—sounds simple but is violated constantly.
I've refactored classes that handled database queries, business logic, and HTML rendering. When requirements changed, we had to modify code in multiple places. Separating these concerns made changes isolated and predictable.
In Laravel, I structure applications with clear layers:
- Controllers: Handle HTTP requests, validate input, call services
- Services: Contain business logic, orchestrate domain operations
- Repositories: Abstract data access, provide clean interfaces
- Models: Represent domain entities, handle data relationships
This structure makes testing easier and changes more predictable. When business logic changes, I modify services. When database structure changes, I modify repositories. Each change is isolated.
SOLID Principles: Not Just Theory
SOLID principles aren't academic exercises—they solve real problems:
Single Responsibility Principle
Each class should have one reason to change. I've seen classes that handled user authentication, email sending, and logging. When email requirements changed, we risked breaking authentication. Separating these into distinct classes eliminated that risk.
Open/Closed Principle
Classes should be open for extension but closed for modification. I use interfaces and dependency injection to achieve this.
For example, payment processing. Instead of modifying a PaymentProcessor class for each new payment method, I create a PaymentGateway interface. New payment methods implement the interface without modifying existing code.
Liskov Substitution Principle
Subtypes must be substitutable for their base types. I've seen inheritance hierarchies where child classes couldn't replace parent classes without breaking functionality.
I prefer composition over inheritance. Instead of extending classes, I compose them. This avoids fragile base class problems and makes code more flexible.
Interface Segregation Principle
Clients shouldn't depend on interfaces they don't use. I've seen interfaces with 20 methods when classes only needed 3.
I create focused interfaces. A UserRepository might have methods for user operations, but I don't force it to implement methods for product operations. Smaller, focused interfaces are easier to implement and test.
Dependency Inversion Principle
Depend on abstractions, not concretions. High-level modules shouldn't depend on low-level modules—both should depend on abstractions.
Laravel's service container makes dependency injection straightforward. I inject interfaces, not concrete classes. This makes testing easier and allows swapping implementations without changing dependent code.
Design Patterns: When to Use Them
Design patterns solve common problems, but using them unnecessarily adds complexity. I use patterns when they solve actual problems:
Repository Pattern
I use repositories to abstract data access. This makes testing easier (mock repositories instead of databases) and allows switching data sources without changing business logic.
For one project, we started with MySQL but needed to add Elasticsearch for search. The repository pattern allowed adding Elasticsearch repositories without changing service code.
Factory Pattern
I use factories when object creation is complex or needs to vary. Laravel's model factories are perfect for creating test data, but I also create custom factories for complex object graphs.
Strategy Pattern
When algorithms need to vary, I use the strategy pattern. Payment processing, shipping calculations, and discount calculations are good candidates.
I've implemented pricing strategies where different customer types get different pricing algorithms. Adding a new customer type means creating a new strategy class—no changes to existing code.
API Design: Contracts Matter
APIs are contracts between services. Breaking contracts breaks systems. I design APIs with versioning and backward compatibility in mind.
For REST APIs, I follow these principles:
- Use HTTP methods correctly (GET for reads, POST for creates, PUT for updates, DELETE for deletes)
- Return consistent response formats
- Use proper HTTP status codes
- Version APIs (v1, v2 in URLs or headers)
- Document everything
I've maintained APIs for years. Good API design makes evolution possible without breaking clients.
Database Design: Structure Matters
Database structure impacts everything. Poor schema design leads to slow queries, data inconsistencies, and difficult migrations.
I follow these principles:
- Normalize appropriately: Normalize to reduce redundancy, but denormalize when queries require it
- Index strategically: Index foreign keys, frequently queried columns, and columns used in WHERE clauses
- Use appropriate data types: Don't use VARCHAR for everything—use appropriate types for performance
- Plan for growth: Consider partitioning, archiving, and scaling strategies
I've redesigned databases that were causing performance problems. Proper indexing and normalization can improve query performance by orders of magnitude.
Error Handling: Fail Gracefully
Systems fail. Good architecture handles failures gracefully. I implement:
- Proper exception handling (catch specific exceptions, handle appropriately)
- Logging (log errors with context for debugging)
- User-friendly error messages (don't expose technical details to users)
- Retry logic for transient failures
- Circuit breakers for external service calls
I've seen systems crash because a single external API call failed. Proper error handling prevents cascading failures.
Testing: Architecture Enables Testing
Good architecture makes testing possible. I design for testability:
- Dependency injection (allows mocking dependencies)
- Small, focused classes (easier to test)
- Pure functions when possible (no side effects, easier to test)
- Clear interfaces (easier to mock)
I write unit tests for business logic, integration tests for API endpoints, and end-to-end tests for critical user flows. Good architecture makes all of this possible.
Documentation: Architecture Decisions
I document architecture decisions. Not everything—just the important decisions and why they were made.
When I return to code months later, or when new team members join, documentation explains the "why" behind the architecture. This prevents reverting good decisions or repeating mistakes.
What I've Learned
After years of building and maintaining systems:
- Architecture decisions compound. Good decisions make future work easier; bad decisions make it harder.
- Simplicity beats complexity. The simplest architecture that solves the problem is usually best.
- Change is inevitable. Design for change, not for perfection.
- Principles matter more than patterns. Understand why patterns exist, not just what they are.
- Testing reveals architecture problems. If code is hard to test, the architecture needs improvement.
Good architecture isn't about using the latest patterns or technologies—it's about making code maintainable, testable, and evolvable. Focus on that, and the rest follows.