You're reading from RESTful API Design Patterns and Best Practices Master REST API design with real-world patterns, lifecycle management, and OpenAPI practices

Product type Paperback

Published in Oct 2025

Publisher Packt

ISBN-13 9781835885284

Length 406 pages

Edition 1st Edition

Languages

JavaScript

Tools

.NET

Concepts

REST API

Authors (2):

Andrzej Jarzyna

Samir Amzani

View More author details

Table of Contents (20) Chapters

Preface

1. The Apprentice’s Study – Preparing for the Craft

2. The “Why” of API Development FREE CHAPTER

3. API as a Product: Designing APIs with a Product Mindset

4. Understanding Application and API Lifecycles

5. Applying Domain-Driven Design to APIs

6. The Wizard’s Grimoire – Mastering the Fundamentals of REST

7. Comparing and Choosing the Right API Style

8. REST Design Constraints and Maturity Models

9. Constructing an API Design Domain Model

10. Designing and Managing Effective API Contracts

11. The Archmage’s Circle – Forging and Evolving API Contracts

12. Understanding the OpenAPI Specification

13. OpenAPI as a Contract: Best Practices and Implementation

14. Using JSON Schema to Define Your Object Models

15. Don’t Hate Your Hypermedia: Creating APIs for Humans and AIs

16. API Change Management: Strategies for Versioning and Evolution

17. Unlock Your Book’s Exclusive Benefits

How to unlock these benefits in three easy steps

18. Other Books You May Enjoy

19. Index

API bundling

While monetization models determine how an API generates revenue, API bundles and plans organize the API’s structure and accessibility by grouping related APIs and defining usage limits, features, and terms for different customer segments. Like any product, APIs need to be thoughtfully packaged for developers through an API portal, where bundles and plans help streamline access, clarify value, and meet a range of customer needs.For instance, a company might create distinct bundles for analytics, machine learning, and data storage APIs, each with tailored pricing models. The analytics bundle could use a tiered model for steady, predictable revenue, while the machine learning bundle might adopt a pay-as-you-go model to accommodate high-intensity computational usage. This bundling approach enables more flexible and targeted pricing strategies, maximizing value for both the provider and the consumer.