System Architecture

System architecture defines the high-level structure of software systems, including components, their relationships, and principles guiding their design and evolution.

What is System Architecture?

System architecture is the conceptual model that defines the structure, behavior, and views of a system. It serves as the blueprint for both system development and maintenance.

Architectural Patterns

Monolithic Architecture

┌─────────────────────────────┐
│      Monolithic App         │
├─────────────────────────────┤
│ ┌─────┐ ┌─────┐ ┌─────┐    │
│ │ UI  │ │Logic│ │Data │    │
│ └─────┘ └─────┘ └─────┘    │
└─────────────────────────────┘

Characteristics:

Single deployable unit
Shared database
Tight coupling
Simple deployment

Pros:

Easy development and testing
Simple deployment
No network latency
Strong consistency

Cons:

Difficult to scale components
Technology lock-in
Single point of failure
Hard to maintain as it grows

When to Use:

Small applications
Simple business logic
Limited team size
Rapid prototyping

Microservices Architecture

┌──────┐  ┌──────┐  ┌──────┐
│Service│  │Service│  │Service│
│  A    │  │  B    │  │  C    │
└───┬──┘  └───┬──┘  └───┬──┘
    │          │          │
    └──────────┼──────────┘
               │
        ┌──────┴──────┐
        │ API Gateway │
        └──────┬──────┘
               │
        ┌──────┴──────┐
        │    Client   │
        └─────────────┘

Characteristics:

Independent services
Own databases
Loose coupling
API communication

Pros:

Independent scaling
Technology diversity
Fault isolation
Team autonomy

Cons:

Network complexity
Distributed transactions
Operational overhead
Testing complexity

When to Use:

Large applications
Multiple teams
Different scalability needs
Technology diversity

Layered Architecture

┌─────────────────┐
│ Presentation    │  ← UI/Controllers
├─────────────────┤
│ Business Logic  │  ← Services/Domain
├─────────────────┤
│ Data Access     │  ← Repositories
├─────────────────┤
│ Database        │  ← Storage
└─────────────────┘

Characteristics:

Organized in horizontal layers
Each layer communicates with adjacent layers
Separation of concerns

Benefits:

Clear separation of concerns
Testability
Maintainability
Reusability

Architectural Quality Attributes

Performance

Response Time: Time to process a request
Throughput: Number of requests per second
Latency: Delay in communication
Resource Utilization: CPU, memory, network usage

Scalability

# Vertical Scaling (Scale Up)
def scale_vertically():
    # Add more CPU, RAM, storage
    increase_server_resources()

# Horizontal Scaling (Scale Out)
def scale_horizontally():
    # Add more servers
    add_more_servers()
    load_balance_across_servers()

Availability

Uptime: System is operational
Fault Tolerance: System continues despite failures
Redundancy: Backup components

Security

Authentication: Verify identity
Authorization: Control access
Encryption: Protect data
Audit Logging: Track activities

Maintainability

Modularity: Independent components
Documentation: Clear architecture docs
Testing: Comprehensive test coverage
Code Quality: Clean, readable code

Design Principles

Separation of Concerns

# Bad: Mixed responsibilities
class UserHandler:
    def save_user(self, user):
        # Validation
        if not user.email:
            raise ValueError("Email required")
        
        # Database operations
        db.execute("INSERT INTO users...")
        
        # Email sending
        email_service.send_welcome(user.email)

# Good: Separated concerns
class UserValidator:
    def validate(self, user):
        if not user.email:
            raise ValueError("Email required")

class UserRepository:
    def save(self, user):
        db.execute("INSERT INTO users...")

class EmailService:
    def send_welcome(self, email):
        # Send email logic

Single Responsibility Principle

Each component should have one reason to change.

Don't Repeat Yourself (DRY)

Avoid code duplication through abstraction.

Interface Segregation

Clients shouldn't depend on interfaces they don't use.

Dependency Inversion

Depend on abstractions, not concretions.

Architectural Decision Making

Trade-off Analysis

Consider:

Performance vs. Complexity
Consistency vs. Availability
Security vs. Usability
Cost vs. Features

Decision Framework

Identify Requirements: Functional and non-functional
Evaluate Options: Multiple architectural approaches
Analyze Trade-offs: Pros and cons of each option
Make Decision: Choose based on requirements
Document: Record rationale and assumptions

Documentation

Document:

Architectural decisions
Rationale behind choices
Assumptions and constraints
Evolution over time

Common Architectural Patterns

Repository Pattern

class UserRepository:
    def __init__(self, db_connection):
        self.db = db_connection
    
    def find_by_id(self, user_id):
        query = "SELECT * FROM users WHERE id = ?"
        return self.db.execute(query, user_id)
    
    def save(self, user):
        query = "INSERT INTO users (name, email) VALUES (?, ?)"
        self.db.execute(query, user.name, user.email)

Factory Pattern

class DatabaseFactory:
    @staticmethod
    def create_database(db_type):
        if db_type == "mysql":
            return MySQLDatabase()
        elif db_type == "postgresql":
            return PostgreSQLDatabase()
        else:
            raise ValueError(f"Unsupported database type: {db_type}")

Observer Pattern

class EventManager:
    def __init__(self):
        self.listeners = {}
    
    def subscribe(self, event_type, listener):
        if event_type not in self.listeners:
            self.listeners[event_type] = []
        self.listeners[event_type].append(listener)
    
    def publish(self, event):
        event_type = event.type
        if event_type in self.listeners:
            for listener in self.listeners[event_type]:
                listener.handle(event)

Architectural Evolution

Monolith to Microservices

Identify Bounded Contexts: Natural business boundaries
Extract Services: Move functionality to services
Implement APIs: Communication between services
Migrate Data: Separate databases
Decommission: Remove old monolith code

Strangler Fig Pattern

Gradually replace legacy systems with new implementations:

Build new functionality alongside existing system
Redirect traffic to new system
Decommission old components
Repeat until fully migrated

Best Practices

Start Simple: Begin with monolith, evolve as needed
Measure Everything: Collect metrics and logs
Design for Failure: Assume components will fail
Automate Everything: Deployment, testing, monitoring
Review Regularly: Architecture should evolve with requirements
Document Decisions: Record architectural choices and rationale
Consider Team Structure: Conway's Law - organization influences architecture

Common Pitfalls

Over-engineering: Adding unnecessary complexity
Premature Optimization: Optimizing before measuring
Ignoring Non-functional Requirements: Focusing only on features
Lack of Monitoring: No visibility into system behavior
Technology Lock-in: Difficult to change technologies later

Good system architecture balances competing concerns while providing a foundation for growth and maintenance. It should be simple enough to understand but flexible enough to evolve.

System Architecture

What is System Architecture?

Architectural Patterns

Monolithic Architecture

Microservices Architecture

Layered Architecture

Architectural Quality Attributes

Performance

Scalability

Availability

Security

Maintainability

Design Principles

Separation of Concerns

Single Responsibility Principle

Don't Repeat Yourself (DRY)

Interface Segregation

Dependency Inversion

Architectural Decision Making

Trade-off Analysis

Decision Framework

Documentation

Common Architectural Patterns

Repository Pattern

Factory Pattern

Observer Pattern

Architectural Evolution

Monolith to Microservices

Strangler Fig Pattern

Best Practices

Common Pitfalls

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System Architecture

Design Patterns

Development

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