What is API testing?

API tests check for data and formatting accuracy, error handling, authentication and authorization compliance, compatibility issues, load issues and more. Development teams can choose to run these tests manually or use software to automate testing and maximize process efficiency. Regardless of the approach, comprehensive API testing requires a range of testing methods to help ensure the optimal performance and security of APIs and applications.

Modern applications typically have three layers: a data layer, a service (or application) layer and a presentation layer. The service layer holds the application’s business logic (and core functionality of the API), which dictates how APIs communicate with other app components and functions.

Historically, developers would implement API-layer testing at the end of the software development lifecycle. However, today many businesses are adopting API-first development strategies, where development teams build applications as a network of services delivered through APIs.

Maintaining optimized APIs is critical to an API-first approach, so developers often choose to incorporate API testing practices earlier in the lifecycle. This proactive approach—known as "shifting left"—helps teams find and fix issues earlier, prevent costly errors and project delays, and optimize the entire development process.

It’s worth noting, however, that API testing might continue even after deployment. Post-production testing (or shift-right testing) offers businesses a complementary testing approach that, when used alongside shift-left strategies, can integrate a continuous feedback loop into DevOps and CI/CD pipelines.

Beyond helping create more stable and reliable APIs, API testing offers businesses significant advantages. It helps improve the quality of enterprise software applications, minimize development costs, accelerate software delivery and more.

APIs are everywhere. They are the connective tissue for a range of systems and processes, and enterprises and individual users alike expect a lot from them. API testing makes sure they work as they should. Let’s unpack that a bit.

APIs (including SOAP, GraphQL and REST APIs) connect applications, web services, systems and databases across the digital world. They enable companies to integrate databases, connect core legacy systems with modern platforms, and connect deployments in different environments. They also enable organizations to offer services to external developers and partners and facilitate more connected user experiences.

Individual users encounter APIs all the time, perhaps unknowingly. When users enter a city into a weather app to look up current conditions, the app calls a weather API to get real-time weather data. Similarly, when a user clicks “get directions” in a navigation app, the app’s backend calls a directions API, which retrieves the step-by-step directions and sends them back to the user.

What’s more, today’s users expect to interact with reliable, ultra-responsive applications. User bounce rates increase 32% when load times increase from one second to three seconds.¹ And 40% of users abandon site if they take longer than three seconds to load.² The emphasis on APIs has led many organizations to adopt an API-first approach, where APIs are considered primary building blocks of an application (and receive commensurate attention).

API-level problems can lead to performance issues (such as increased latency) for users and expose enterprise data to cyberattacks, both of which hurt a business’s bottom line. To avoid these issues, applications and API-first networks require secure, high-performing APIs. And continuous testing is essential for building and maintaining such APIs.

API testing verifies that APIs provide the expected results, and that they do so consistently in response to varying inputs and scenarios. It enables teams to address problems at the server level before they reach the user interface and create larger issues.

API tests help teams safely simulate scenarios that would be risky or impractical to perform at the interface level (probing for security vulnerabilities, for instance). And in microservice architectures, where each microservice generally manages its own data store and exposes functions through APIs, APIs testing helps ensure that microservices are interacting effectively and securely.

Getting a complete, accurate view of API health requires IT teams to conduct a range of tests, including:

Functional testing—which includes unit, regression and integration testing—helps ensure that an API provides the correct responses and data formats for a particular request. It involves sending specific requests to API endpoints and checking that the expected status codes, response bodies and data structures are returned.

Functional tests broadly aim to validate functionality across different test scenarios, including both normal and edge cases, error handling and business rule compliance.

Unit testing is a software testing technique where individual units or components of an application (such as functions, methods or classes) are tested separately to make sure they work as intended. For APIs that means sending a single request to a single API endpoint to get a single response or series of responses.  

Unit API tests attempt to confirm that each part of the codebase behaves correctly so that developers can detect bugs early and create more dependable API code.

Performance testing evaluates an API’s speed, responsiveness and throughput in different situations, including how it handles traffic spikes and numerous simultaneous API calls. Teams can conduct a range of performance tests (load tests, stress tests and endurance tests, among others) to spot traffic bottlenecks and ensure low latency, especially when APIs are part of larger, dynamic systems.

For example, IT personnel may want to check how quickly and reliably a shopping cart API on an e-commerce site will respond during a major online shopping event, such as a holiday sale.

Security testing helps ensure that APIs protect sensitive data and prevent unauthorized access. It includes identifying endpoint vulnerabilities such as cross-site scripting, SQL injection and weaknesses in authentication or authorization protocols. Security tests can also identify unencrypted data transfers, use of weak passwords and insecure network architecture.

Authentication tests, for example, can verify the effectiveness of API authentication mechanisms (such as API keys, JSON Web Tokens (JWT), OAuth access tokens and traditional username-password pairs). And API penetration tests—also called API pentests—can help teams find security vulnerabilities by simulating real-world cyberattacks and assessing the API’s response.

Integration testing evaluates how different components or modules of a system work together, typically after APIs are unit tested. It requires teams to test an API’s inputs and outputs to verify the interactions and interfaces between modules.

Integration tests help reveal problematic data exchanges, communication protocols and external system dependencies that can create interface issues and undermine the overall performance of an application. Teams can use an incremental approach (where API components are integrated and tested gradually), “big bang” approaches (where all components are integrated at once and the entire system is tested together), or other testing methods.

Integration testing is sometimes overlooked in API development, but it’s a critical process for maintaining application health, especially when an app depends on external APIs.

Stress testing and load testing have similar objectives: determining the capacity of an API.

Stress testing pushes APIs beyond their normal operational limits to determine their breaking point. It simulates situations—such as constrained resources and extreme loads—to identify bottlenecks, scalability issues and the maximum capacity an API can handle before issues occur.

Load testing measures how APIs perform under varying levels of concurrent requests or user activity. It helps development teams understand how APIs respond to different traffic loads, so they can effectively manage API traffic and minimize response times and error rates.  

Documentation testing helps ensure that APIs are clearly documented, and that the documentation accurately describes their functionality. It also validates API feature integration and verifies that APIs behave as specified in the documentation.

Documentation testers can confirm that an API returns the expected data, that its parameters are correctly defined and that data formats align with current documentation.

Interoperability testing verifies that an API can effectively connect and communicate with different operating systems, frameworks, hardware environments and programming languages. An API should, by definition, be interoperable.

API interoperability tests help ensure that APIs adhere to industry standards, protocols and data formats so that they have broad compatibility with various client applications and services. They also confirm that APIs can support standard data formats (such as JavaScript Object Notation (JSON), XML, Protocol Buffers), communication protocols (such as HTTP, WebSockets, gRPC), character encodings, localization and authentication mechanisms.

Contract tests capture the interactions between two systems or modules (two microservices, for instance) to assess the compatibility and effectiveness of their communication. They verify that API interactions adhere to predefined contracts and that the contracts remain consistent across deployments, which makes them especially useful for testing APIs in microservice architectures.

Using contract testing, developers can prevent microservice and third-party API integration issues and simplify communication between front end developers and backend engineers.

API fuzz testing, or API fuzzing, assesses the security and stability of an application’s APIs. It involves sending a range of malformed or unexpected inputs to an API to find vulnerabilities, such as input validation errors, buffer overflows, injection flaws and other security issues.

Fuzzing can make an API behave unpredictably and reveal flaws in how it processes inputs and request sequences. This exercise helps IT teams uncover security issues that might be used to compromise the application.

End-to-end testing evaluates the complete integration and functionality of an API within its broader system or application. It simulates real-world scenarios to help developers understand how APIs interact with system components, databases and external services.

The end-to-end testing process typically includes setting up a comprehensive test environment, verifying authentication and authorization, preparing relevant test data, sending data requests with various parameter configurations, and validating the API’s response to ensure data consistency.

The best testing methods for API-driven environments depend on the nature of the APIs and their complexity. For simple APIs that mostly handle basic “create, read, update, delete” operations, manual testing might be sufficient. Manual testing is a relatively straightforward process that involves sending API requests and checking the responses against expectations.

With manual API testing, it’s important to create a test plan and decide which scenarios and criteria to test. Teams can then prepare the necessary input parameters, send data requests, and observe API responses for any errors or unexpected results.

If the API is more complex or requires extensive data manipulation, API test automation using open-source and third-party tools can help streamline the testing process. Automated testing is especially beneficial for larger projects, heavily regulated environments and for handling sensitive data, because it’s more efficient and scalable than manual testing.

API testing and API monitoring aim to ensure that APIs function optimally and that applications can communicate effectively with other apps and services. However, they focus on different parts of the application lifecycle.

Whereas API testing is a proactive approach that focuses on detecting performance, security and reliability issues during development, monitoring prioritizes detecting issues after deployment. API monitoring tools also track and visualize API telemetry over time, enabling teams to analyze historical data and identify performance trends for the API’s entire post-release lifespan.

Because both monitoring and testing practices help ensure that APIs and applications are optimized for end users, businesses need both to maintain a healthy API ecosystem.

The widespread adoption of API-first software development, cloud-native SaaS applications and accelerated CI/CD pipelines means that APIs are now omnipresent across the digital landscape. It also means that APIs are evolving faster than ever. Therefore, businesses looking to stay ahead of the curve must consider adopting innovative API testing tools and practices.

Examples of emerging testing trends include:

Implementing rigorous API testing practices can:

• Fortify APIs and applications. API testing helps developers to build, deliver and maintain stable, reliable applications.

• Improve mean time to repair (MTTR). API testing helps DevOps teams identify and address API problems early in the software lifecycle and before they impact users.

• Fast-track feedback. API testing tools interact directly with application logic, so validation happens quickly, and developers get feedback faster.

• Strengthen API security. API testing helps teams find vulnerabilities (weak authentication protocols, for instance) and fill security gaps before bad actors can exploit them.

• Accelerate software development cycles. API testing tools accelerate feedback cycles, enabling faster software iteration, simpler debugging and continuous improvement. These features help businesses enhance CI/CD pipelines and sustain agile development practices.

• Simplify test maintenance. Because APIs don’t change frequently (unlike user interfaces, which change based on when and how users access them), API tests don’t need frequent updates or maintenance to remain effective.

• Expand test coverage. Testing applications at the API layer provide broader test coverage than UI tests, which can miss backend application issues.