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API Gateway Pattern

Overview​

The API Gateway pattern provides a single entry point for client requests to a microservices architecture. It acts as a reverse proxy, routing requests to appropriate backend services while handling cross-cutting concerns like authentication, rate limiting, and monitoring.

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Architecture Diagram​

Components​

API Gateway​

Responsibility: Central entry point for all client requests

Key Features:

  • Request routing and load balancing
  • Protocol translation (HTTP/REST to gRPC)
  • Request/response transformation
  • API composition and aggregation

Technology: Kong, AWS API Gateway, or Zuul

Authentication & Authorization​

Responsibility: Verify client identity and permissions

Implementation:

  • JWT token validation
  • OAuth 2.0 / OpenID Connect integration
  • Role-based access control (RBAC)
  • API key management

Rate Limiting & Throttling​

Responsibility: Protect backend services from overload

Strategies:

  • Per-client rate limiting
  • Global rate limiting
  • Burst capacity handling
  • Circuit breaker patterns

Monitoring & Observability​

Responsibility: Track API usage and performance

Metrics:

  • Request/response times
  • Error rates and status codes
  • Throughput and concurrent requests
  • Client usage patterns

Implementation Guide​

Step 1: Gateway Setup​

# kong-gateway.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: kong-gateway
spec:
  replicas: 3
  selector:
    matchLabels:
      app: kong-gateway
  template:
    metadata:
      labels:
        app: kong-gateway
    spec:
      containers:
      - name: kong
        image: kong:3.0
        ports:
        - containerPort: 8000
        - containerPort: 8001
        env:
        - name: KONG_DATABASE
          value: "off"
        - name: KONG_DECLARATIVE_CONFIG
          value: "/kong/declarative/kong.yml"

Step 2: Service Configuration​

# kong-config.yml
_format_version: "3.0"

services:
  - name: user-service
    url: http://user-service:8080
    routes:
      - name: user-routes
        paths:
          - /api/users
        methods:
          - GET
          - POST
          - PUT
          - DELETE

  - name: order-service
    url: http://order-service:8080
    routes:
      - name: order-routes
        paths:
          - /api/orders
        methods:
          - GET
          - POST

plugins:
  - name: jwt
    config:
      secret_is_base64: false
      key_claim_name: iss
      
  - name: rate-limiting
    config:
      minute: 100
      hour: 1000
      policy: local

Step 3: Authentication Setup​

// JWT validation middleware
const jwt = require('jsonwebtoken');

function validateJWT(req, res, next) {
  const token = req.headers.authorization?.replace('Bearer ', '');
  
  if (!token) {
    return res.status(401).json({ error: 'No token provided' });
  }
  
  try {
    const decoded = jwt.verify(token, process.env.JWT_SECRET);
    req.user = decoded;
    next();
  } catch (error) {
    return res.status(401).json({ error: 'Invalid token' });
  }
}

module.exports = { validateJWT };

Step 4: Rate Limiting Configuration​

-- Kong rate limiting plugin configuration
local rate_limiting = {
  minute = 100,
  hour = 1000,
  day = 10000,
  month = 100000,
  year = 1000000,
  policy = "redis",
  redis_host = "redis-cluster",
  redis_port = 6379,
  fault_tolerant = true,
  hide_client_headers = false
}

return rate_limiting

Configuration Examples​

Environment-Specific Settings​

Development​

gateway:
  replicas: 1
  resources:
    requests:
      memory: "256Mi"
      cpu: "250m"
  rate_limiting:
    minute: 1000
    hour: 10000

Production​

gateway:
  replicas: 5
  resources:
    requests:
      memory: "1Gi"
      cpu: "500m"
  rate_limiting:
    minute: 100
    hour: 1000
  circuit_breaker:
    failure_threshold: 5
    timeout: 30s

Testing Strategy​

Unit Tests​

  • Route configuration validation
  • Authentication middleware testing
  • Rate limiting logic verification

Integration Tests​

  • End-to-end request flow testing
  • Service discovery and routing
  • Error handling and fallback scenarios

Load Tests​

  • Performance under expected load
  • Rate limiting effectiveness
  • Circuit breaker behavior

Security Tests​

  • Authentication bypass attempts
  • Authorization boundary testing
  • Input validation and sanitization

Monitoring & Observability​

Key Metrics​

# Prometheus metrics configuration
metrics:
  - name: gateway_requests_total
    type: counter
    labels: [method, route, status_code]
    
  - name: gateway_request_duration_seconds
    type: histogram
    labels: [method, route]
    
  - name: gateway_active_connections
    type: gauge
    
  - name: gateway_rate_limit_exceeded_total
    type: counter
    labels: [client_id, route]

Alerting Rules​

groups:
  - name: api-gateway
    rules:
      - alert: HighErrorRate
        expr: rate(gateway_requests_total{status_code=~"5.."}[5m]) > 0.1
        for: 2m
        labels:
          severity: warning
        annotations:
          summary: "High error rate detected"
          
      - alert: GatewayDown
        expr: up{job="api-gateway"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "API Gateway is down"

Best Practices​

Do's​

  • Keep it lightweight: Gateway should focus on routing and cross-cutting concerns
  • Implement circuit breakers: Protect against cascading failures
  • Use connection pooling: Optimize backend connections
  • Monitor everything: Track all requests, errors, and performance metrics
  • Version your APIs: Support multiple API versions through the gateway

Don'ts​

  • Don't add business logic: Keep business logic in services, not the gateway
  • Don't create a single point of failure: Deploy multiple gateway instances
  • Don't ignore security: Always validate and sanitize inputs
  • Don't forget rate limiting: Protect your services from abuse
  • Don't skip monitoring: Observability is critical for troubleshooting

Scaling Considerations​

Horizontal Scaling​

  • Deploy multiple gateway instances behind a load balancer
  • Use session affinity for stateful connections
  • Implement health checks for automatic failover

Performance Optimization​

  • Enable response caching for read-heavy operations
  • Use connection pooling to backend services
  • Implement request/response compression
  • Optimize routing rules for common patterns

Security Considerations​

Authentication​

  • Implement strong authentication mechanisms (JWT, OAuth)
  • Use short-lived tokens with refresh capabilities
  • Validate all tokens on every request

Authorization​

  • Implement fine-grained access controls
  • Use role-based or attribute-based access control
  • Audit all authorization decisions

Input Validation​

  • Validate all incoming requests
  • Sanitize user inputs to prevent injection attacks
  • Implement request size limits
  • Backend for Frontend (BFF) (Coming Soon)
  • Service Mesh Architecture (Coming Soon)
  • Circuit Breaker Pattern
  • Rate Limiting Strategies (Coming Soon)

References​

Last Updated: 2024-01-15
Maintainer: Platform Architecture Team
Status: Production Ready