API Gateway Patterns: Kong, AWS API Gateway, and When to Use Each

Introduction

API gateways have become the backbone of modern microservices architecture. They act as the single entry point for all client requests, handling everything from routing and authentication to rate limiting and load balancing.

Here, we'll compare two popular API gateway solutions: Kong (open-source and self-hosted) and AWS API Gateway (fully managed).

Understanding API Gateway Patterns

Edge Gateway Pattern: A single entry point at the network edge that handles all external traffic.

Backend for Frontend (BFF) Pattern: Separate gateways optimized for different client types.

Sidecar Pattern: A gateway deployed alongside each service in service mesh architectures.

Kong: The Open-Source Powerhouse

Kong is built on NGINX and offers both open-source and enterprise versions.

# kong.yaml - Declarative configuration
_format_version: "3.0"

services:
  - name: user-service
    url: http://user-api:3000
    routes:
      - name: user-routes
        paths:
          - /api/users
    plugins:
      - name: rate-limiting
        config:
          minute: 100
      - name: key-auth

AWS API Gateway

AWS API Gateway is fully managed and integrates deeply with AWS services.

resource "aws_api_gateway_rest_api" "main" {
  name        = "production-api"
  description = "Production API Gateway"
}

resource "aws_api_gateway_method" "get_users" {
  rest_api_id   = aws_api_gateway_rest_api.main.id
  resource_id   = aws_api_gateway_resource.users.id
  http_method   = "GET"
  authorization = "COGNITO_USER_POOLS"
}

Decision Framework

Choose Kong When:

• Multi-cloud or hybrid deployments
• Advanced customization needs
• Cost optimization at scale
• Avoiding vendor lock-in

Choose AWS API Gateway When:

• AWS-native architecture
• Minimal operational overhead
• Rapid prototyping
• Deep AWS integration needed

Conclusion

Both Kong and AWS API Gateway are excellent choices. Kong excels in flexibility and multi-cloud scenarios, while AWS API Gateway shines in AWS-native architectures.

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Originally published at instadevops.com