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This chapter is from the book

This chapter is from the book

Principles of Web API Design: Delivering Value with APIs and MicroservicesPrinciples of Web API Design: Delivering Value with APIs and Microservices

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This chapter is from the book

This chapter is from the book

Principles of Web API Design: Delivering Value with APIs and MicroservicesPrinciples of Web API Design: Delivering Value with APIs and Microservices

Learn More Buy

Resource-Based API Design

A resource is a digital representation of a concept, often an entity or collection of entities that may change over time. It consists of a unique name or identifier that can reference documents, images, collections of other resources, or a digital representation of anything in the real world such as a person or thing. Resources may even represent business processes and workflows.

Resource-based APIs focus on interactions across a network, independent of how they are stored in a database or manifested as objects. They offer different operations, or affordances, as possible interactions with a specific resource. In addition, resources support multiple representations that allow a Web app, mobile app, and reporting tool to interact with the resource using different media formats such as JSON or XML.

Resources Are Not Data Models

It is important to recognize that resources are not the same thing as a data model that resides with a database. The data model, often reflected as a schema design in a database, is optimized for the read and write interactions necessary to support the required I/O performance and reporting needs of a solution.

While data may be part of an API, the data model should not be used as the basis of API design. Data models meet a specific set of requirements, including read and write performance, optimized data storage, and optimized query support. Data models are optimized for the internal details of an application.

Like the choice of programming languages and frameworks, the choice of database types and vendors changes over time. APIs designed to directly map to a data or object model expose these internal implementation details to API consumers. The result is a more fragile API that must introduce significant design changes when the data model changes.

Web API design seeks to achieve a different set of goals, including delivering outcomes and experiences, optimized network access, and programming language independence. Because APIs involve integration between systems, they should remain stable over a long period of time, whereas data models may change to accommodate new or changing data access requirements.

While APIs may have an impact on the data model, an API design should evolve independently from the latest database trends.

WHAT HAPPENS WHEN TEAMS EXPOSE A DATA MODEL AS AN API?

Constant code changes: Database schema changes will result in a constantly changing API, as the API must keep in lockstep with the underlying database. This change to the data model forces consumers into a complex conformist relationship in which they must rewrite their API integration code every time the underlying data model changes. This hindrance may be overcome by an anticorruption layer that isolates a unit of code from these changes. However, the constant flux of the API creates a high cost of development as downstream developers maintain the anticorruption layer.

Create network chattiness: Exposing link tables as separate API endpoints causes API “chattiness,” as the consumer is forced to make multiple API calls, one for each table. It is similar to how an n+1 query problem degrades database performance. While an n+1 problem can be a performance bottleneck for databases, API chattiness has a devastating impact on API performance.

Data inconsistencies: Not only does performance suffer from network chattiness, but the n+1 problem also results in data inconsistencies. Clients are forced to make multiple API calls and stitch the results together into a single unified view. This may result in incomplete or corrupted data due to inconsistent reads, perhaps across transactional boundaries, that occur from multiple API requests necessary to obtain necessary data.

Confuse API details: Columns optimized for query performance, such as CHAR(1) column that uses character codes to indicate status, become meaningless to API consumers without additional clarification.

Expose sensitive data: Tools that build APIs that mirror a data model expose all columns with a table using SELECT * FROM [table name]. This also exposes data that API consumers should never see, such as personally identifiable information (PII). It may also expose data that helps hackers compromise systems through a better understanding of the internal details of the API.

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