Api on Commentary of Takao

Best Practices for Designing REST API Endpoints

Fri, 25 Apr 2025 00:00:00 +0900

Introduction

In modern web development, API consistency plays a critical role in developer productivity.

Inconsistent endpoints (URLs), improper HTTP methods, and wrapping all errors in 200 OK status codes lead to confusion, bugs, and wasted development cycles.

This article reviews the best practices for designing scalable, self-documenting REST APIs that are easy to understand and integrate.

1. Principle 1: Resource-Oriented URLs (Use Nouns)

The core principle of REST is that URIs represent resources (nouns), while the HTTP methods (verbs) represent the actions performed on those resources.

GraphQL vs REST in 2024: Making the Right Choice

Tue, 03 Dec 2024 00:00:00 +0900

Introduction

The debate between GraphQL and REST has matured significantly by 2024. Both approaches have evolved, adopted features from each other, and found their niches. The question is no longer which is universally superior, but which fits your specific project context. This article provides a balanced comparison to help teams make informed API architecture decisions.

State of REST in 2024

REST remains the dominant API paradigm, powering the majority of web APIs. Its strengths lie in maturity, simplicity, and universal HTTP caching. The OpenAPI 3.1 specification brought JSON Schema compatibility, improving interoperability. Tooling like Swagger UI, Redoc, and Postman collections provide excellent documentation and testing capabilities.

API Rate Limiting Strategies: Protecting Your Services

Tue, 07 May 2024 00:00:00 +0900

Rate limiting is a critical component of any production API. It protects backend services from abuse, ensures fair resource allocation, maintains performance under load, and mitigates denial-of-service attacks. This article examines the major rate limiting algorithms, their trade-offs, and best practices for designing robust systems.

Token Bucket Algorithm

The token bucket is one of the most widely used rate limiting algorithms. A bucket holds tokens that refill at a steady rate, and each request consumes one token. If the bucket is empty, the request is denied. This approach allows bursts up to the bucket capacity while smoothing traffic over time.