Cloud Architecture Patterns for Scalable Applications

In today's cloud-native world, choosing the right architecture patterns is crucial for building applications that can scale effectively. Let's explore some essential patterns and their implementations.

Microservices Architecture

Breaking down applications into smaller, independent services:

// User Service
interface UserService {
  getUserById(id: string): Promise<User>;
  createUser(user: UserInput): Promise<User>;
  updateUser(id: string, data: Partial<User>): Promise<User>;
}

// Authentication Service
interface AuthService {
  login(credentials: Credentials): Promise<TokenResponse>;
  validateToken(token: string): Promise<boolean>;
  refreshToken(token: string): Promise<TokenResponse>;
}

Event-Driven Architecture

Using events for loose coupling between services:

// Event Publisher
class OrderEventPublisher {
  async publishOrderCreated(order: Order) {
    await eventBus.publish('order.created', {
      orderId: order.id,
      userId: order.userId,
      timestamp: new Date().toISOString()
    });
  }
}

// Event Subscriber
class NotificationService {
  @Subscribe('order.created')
  async handleOrderCreated(event: OrderCreatedEvent) {
    await this.sendOrderConfirmation(event.orderId);
  }
}

CQRS Pattern

Separating read and write operations:

// Command
interface CreateOrderCommand {
  userId: string;
  products: Array<{ id: string; quantity: number }>;
}

// Query
interface GetOrderQuery {
  orderId: string;
  includeDetails?: boolean;
}

// Handlers
class OrderCommandHandler {
  async execute(cmd: CreateOrderCommand) {
    // Write to primary database
  }
}

class OrderQueryHandler {
  async execute(query: GetOrderQuery) {
    // Read from replica/cache
  }
}

Circuit Breaker Pattern

Preventing cascading failures:

class CircuitBreaker {
  private failures = 0;
  private lastFailure: Date | null = null;
  private readonly threshold = 5;
  private readonly resetTimeout = 60000; // 1 minute

  async execute<T>(fn: () => Promise<T>): Promise<T> {
    if (this.isOpen()) {
      throw new Error('Circuit is open');
    }

    try {
      const result = await fn();
      this.reset();
      return result;
    } catch (error) {
      this.recordFailure();
      throw error;
    }
  }

  private isOpen(): boolean {
    if (this.failures >= this.threshold) {
      if (this.lastFailure && Date.now() - this.lastFailure.getTime() > this.resetTimeout) {
        this.reset();
        return false;
      }
      return true;
    }
    return false;
  }

  private recordFailure() {
    this.failures++;
    this.lastFailure = new Date();
  }

  private reset() {
    this.failures = 0;
    this.lastFailure = null;
  }
}

Cache-Aside Pattern

Improving read performance:

class CacheAsideService {
  constructor(
    private readonly cache: Cache,
    private readonly db: Database
  ) {}

  async getData(key: string): Promise<Data> {
    // Try cache first
    const cached = await this.cache.get(key);
    if (cached) {
      return cached;
    }

    // Cache miss - get from database
    const data = await this.db.get(key);
    
    // Store in cache for next time
    await this.cache.set(key, data, { ttl: 3600 });
    
    return data;
  }
}

Best Practices

1. Design for Failure

   • Implement proper error handling
   • Use circuit breakers
   • Design with redundancy in mind

2. Monitor Everything

   • Track key metrics
   • Set up proper logging
   • Implement tracing

3. Scale Smart

   • Use auto-scaling
   • Implement proper caching
   • Optimize database queries

4. Security First

   • Implement proper authentication
   • Use encryption at rest and in transit
   • Regular security audits

Next Steps

1. Review your current architecture
2. Identify improvement areas
3. Plan gradual implementation
4. Monitor and adjust