API Gateway/Backend for Frontend

Overview

The API Gateway pattern creates a centralized service layer that acts as a single entry point for client applications while coordinating access to multiple backend services. This pattern provides unified API interfaces, handles cross-cutting concerns, and simplifies client integration.

Use this pattern when building:

Multi-client applications (web, mobile, third-party integrations)
Microservice architectures requiring unified interfaces
Systems needing centralized authentication and rate limiting
Applications requiring response aggregation and transformation
APIs requiring monitoring and analytics across multiple services

Architecture Diagram

flowchart TB
    Client1[Web Client]
    Client2[Mobile App]
    Client3[Third Party]
    Gateway[API Gateway Service]
    Client1 --> Gateway
    Client2 --> Gateway
    Client3 --> Gateway

    subgraph GatewayProcessing ["Gateway Processing"]
        Gateway --> Auth["Authentication<br/>SQL Database/KV Cache"]
        Gateway --> Rate["Rate Limiting<br/>Observer"]
        Gateway --> Route[Request Routing]
        Gateway --> Cache["Response Cache<br/>KV Cache"]
    end

    subgraph Backend ["Backend Services"]
        Route --> Service1[User Service]
        Route --> Service2[Order Service]
        Route --> Service3[Payment Service]
        Route --> ServiceN[Other Services]
    end

    subgraph CrossCutting ["Cross-Cutting Concerns"]
        Observer[Observer] --> Metrics[Metrics Collection]
        Observer --> Logs["Request/Response Logs"]
        Observer --> Alerts[Rate Limit Alerts]

        SqlDb[SQL Database] --> UserAuth[User Authentication]
        SqlDb --> APIKeys[API Key Management]

        KvCache[KV Cache] --> SessionCache[Session Cache]
        KvCache --> ResponseCache[Response Cache]
    end

    Gateway --> AggregatedResponse[Aggregated Response]
    AggregatedResponse --> Client1
    AggregatedResponse --> Client2
    AggregatedResponse --> Client3

Components

Service - Central orchestration component handling routing, transformation, and aggregation
KV Cache - High-performance caching for sessions, responses, and rate limiting counters
Observer - Monitoring, rate limiting, and performance tracking across the gateway
SQL Database - Persistent storage for authentication, API keys, and configuration data

Logical Flow

Request Reception - Client applications send requests to gateway Service as single entry point
Authentication & Authorization - Service validates requests using SQL Database or cached tokens in KV Cache
Rate Limiting - Observer enforces rate limiting policies based on client identity and API keys
Route Resolution - Service analyzes request paths and headers to determine required backend services
Cache Check - Service checks KV Cache for cached responses before making backend calls
Backend Orchestration - Service coordinates calls to backend services with circuit breaker patterns
Response Aggregation - Service combines and transforms responses from multiple backend services
Caching & Response - Processed responses stored in KV Cache and returned to clients with proper formatting

Implementation

Deploy Gateway Service - Configure main Service with routing rules, authentication middleware, and transformation logic
Configure Authentication - Set up SQL Database with user tables and API key management
Implement Caching - Configure KV Cache with appropriate TTL policies for responses and sessions
Set Up Monitoring - Deploy Observer with metrics collection, rate limiting rules, and alerting
Production Setup - Add SSL termination, load balancing, backup authentication, and service discovery integration

application "api_gateway" {

  service "gateway" {
  }

  kv_cache "cache_store" {
  }

  kv_cache "session_store" {
  }

  sql_database "auth_db" {
  }

  observer "gateway_monitor" {
  }

}

application "enterprise_api_gateway" {

  service "gateway" {
  }

  service "admin_gateway" {
  }

  kv_cache "response_cache" {
  }

  kv_cache "session_cache" {
  }

  kv_cache "config_cache" {
  }

  sql_database "auth_database" {
  }

  sql_database "audit_database" {
  }

  observer "gateway_observer" {
  }

}

Best Practices

Implement multiple authentication methods - Support API keys, JWT tokens, and OAuth for different client types
Use secure token storage - Cache authentication tokens securely with appropriate expiration policies
Validate all inputs - Implement complete request validation and sanitization at gateway level
Monitor security events - Track authentication failures and suspicious access patterns
Cache strategically - Cache frequently accessed, static data while avoiding user-specific information
Implement cache invalidation - Design cache keys and invalidation strategies for data consistency
Use appropriate TTLs - Set cache expiration based on data volatility and business requirements
Implement circuit breakers - Prevent cascading failures by isolating failing backend services
Use connection pooling - Maintain persistent connections to reduce connection overhead
Optimize request routing - Design routing logic to minimize latency and distribute load effectively
Provide meaningful error responses - Transform backend errors into consistent, client-friendly messages
Implement retry logic - Use exponential backoff for transient failures while avoiding retry storms