API Gateway Patterns#

An API gateway sits between clients and your backend services. It handles cross-cutting concerns – authentication, rate limiting, request transformation, routing – so your services do not have to. Choosing the right gateway and configuring it correctly is one of the first decisions in any microservices architecture.

Gateway Responsibilities#

Before selecting a gateway, clarify which responsibilities it should own:

• Routing – directing requests to the correct backend service based on path, headers, or method.
• Authentication and authorization – validating tokens, API keys, or certificates before requests reach backends.
• Rate limiting – protecting backends from traffic spikes and enforcing usage quotas.
• Request/response transformation – modifying headers, rewriting paths, converting between formats.
• Load balancing – distributing traffic across service instances.
• Observability – emitting metrics, logs, and traces for every request that passes through.
• TLS termination – handling HTTPS so backends can speak plain HTTP internally.

No gateway does everything equally well. The right choice depends on which of these responsibilities matter most in your environment.

AWS Lambda and Serverless Function Patterns#

Lambda runs your code without you provisioning or managing servers. You upload a function, configure a trigger, and AWS handles scaling, patching, and availability. The execution model is simple: an event arrives, Lambda invokes your handler, your handler returns a response. Everything in between – concurrency, retries, scaling from zero to thousands of instances – is managed for you.

That simplicity hides real complexity. Cold starts, timeout limits, memory-to-CPU coupling, VPC attachment latency, and event source mapping behavior all require deliberate design. This article covers the patterns that matter in practice.

Rate Limiting Implementation Patterns#

Rate limiting controls how many requests a client can make within a time period. It protects services from overload, ensures fair usage across clients, prevents abuse, and provides a mechanism for graceful degradation under load. Every production API needs rate limiting at some layer.

Algorithm Comparison#

Fixed Window#

The simplest algorithm. Divide time into fixed windows (e.g., 1-minute intervals) and count requests per window. When the count exceeds the limit, reject requests until the next window starts.