What is API testing? A complete guide

APIs orchestrate behind-the-scenes work for every application on the internet today. To build foolproof APIs that are resilient, highly performant, and function well at scale, you need to test them rigorously.

This guide walks you through what API testing is, how it works, types of API tests you can perform, and how to integrate it well with modern software delivery pipelines.

What is API testing?

API stands for application programming interface. APIs handle communication between the client, the application’s own server and database, or third-party services that interact with the application.

API testing is a type of testing that involves sending requests and evaluating responses to APIs. It validates the behavior, performance, reliability, and security of these APIs.

API testing is a type of testing that involves sending requests and evaluating responses to APIs.

API testing vs unit testing vs UI testing

Unit testing tests isolated functions or methods. UI testing tests an application’s interactions with screens and browsers. API testing, on the other hand, tests the business logic that is implemented in the backend.

All three types of testing differ in scope, speed, stability, dependency, coverage, and maintenance as shown below:

Why is API testing important in an API-first world?

“People have realized you can test a whole lot of the business functionality through the API level.”— Lisa Crispin (Agile testing author and coach)

Modern software applications are API driven. Interactions between the UI or client, database, server, and other services happen via these APIs regardless of the overall application architecture.

From authentication and authorization to data validation, business logic enforcement, and integrations, APIs contribute significantly to performance-sensitive workflows.

These impact user experience and business metrics. A broken API cannot be compensated for by a polished UI or even the most sought-after user experience.

Today, the majority of internet traffic is driven by APIs. Fault isolation is extremely simplified at the API level.

Teams can significantly reduce production incidents by conducting standardized API testing. Thus, API testing helps teams catch issues and defects in the APIs at source before they reach the end users.

What is the relationship between API testing and API monitoring?

API testing and API monitoring are complementary processes.

API testing validates API behaviour according to set specifications and benchmarks. It happens before APIs are actually released or the software is shipped to production.

API monitoring, on the other hand, is a continuous process where teams monitor their APIs to see if they’re functioning correctly, experiencing any downtime, etc., in real-time.

Teams that invest in robust API testing will see fewer production incidents. This reduces the effort and time spent on monitoring APIs. API testing is not a one-off replacement for API monitoring; rather, the former complements the latter.

For instance, if you notice, via monitoring, unusual traffic spikes in APIs causing them to slow down, you can incorporate stress and load testing of your APIs.

API testing is not a one-off replacement for API monitoring; rather, the former complements the latter.

Architectures and principles of APIs

There are different API principles and architectures. The most common ones are REST, SOAP, and GraphQL. Let’s take a deeper look at one of them: REST architecture.

REST architecture

REST stands for representational state transfer. It’s the most popular API architecture, in which a URL takes certain parameters as input.

This URL is then queried by the client using standard HTTP methods. Finally, the URL communicates with the backend server and returns the correct response to the client.

HTTP methods

The following are the most common HTTP method types used when building REST APIs:

Status codes

HTTP status codes are the first signals in API testing. While testing APIs, teams should ensure the right API is returning the right status code.

How does API testing work?

Implementing API testing systematically across hundreds of endpoints requires careful planning. The following process will demystify how to implement API testing.

1. Set up your test environment

Create a test environment as close to your production environment as possible. You want to simulate a real production environment and carry out your API testing without breaking things for your users.

Deploy the application with all its dependencies (databases, external services, messaging systems) in an isolated test environment.

2. Define test cases from specifications

Clearly define test cases for the APIs. Each test case defines expected inputs and outputs.

For example, imagine that you’re writing test cases for a payment transfer API. Common types of test cases would include the following:

Happy path

Happy path test case confirms that baseline logic works well. For example, when a user sends $5 from account A to account B, a valid transfer should happen between two active accounts.

Edge case

The edge case probes some real-world limits of valid behaviour. For example, if the user transfers the exact balance amount to an account, the account balance should reduce to 0.

Invalid input

The invalid input checks that the API rejects bad data with a clean error. For example, if the user attempts to transfer $100 when their account has only $90, API should reject such a request.

The boundary condition tests both sides of a rule—one that should pass and one that should fail.

Boundary condition

The boundary condition tests both sides of a rule—one that should pass and one that should fail. Let’s say your API imposes a $1,000 cap per transaction. A request for even $1,001 should be rejected, whereas a request for $1,000 should go through.

3. Author tests and assert responses

You’ll want to write tests that send HTTP requests using different methods, such as GET, PUT, POST, etc., with well-defined headers, query parameters, and request bodies. Validate that the API:

• Returns the correct status code. If a resource did not exist, the API should return a 404. If the API returns a valid response, a 200 status code should be returned.
• Returns a valid JSON content in the response with all fields well defined.
• Has each field in the JSON response in its correct type. A flag like “is_payment_valid” should only be a boolean value of either true or false. Similarly, usernames returned should be in string form.
• Doesn’t take an unusual time to respond.
• Returns error messages for erroneous requests of the form 3XX, 4XX, and 5XX that are intuitive to understand and made available to the user.

4. Automate testing with CI/CD

Integrate your API test suite into your build pipeline to implement test automation. This will increase testing efficiency while standardising the entire testing process. Every time you commit to the repository, your API tests will run automatically.

5. Report and triage results

Lastly, capture the test results, response times, and failure logs and route these to the developer and engineering teams so that these defects can be taken into account and tracked over time. This ensures more robust API development in the next release cycle.

What are the different types of API testing?

Modern systems require a multi-dimensional testing approach that addresses correctness, security, performance, and reliability. The following types of API testing can be used to evaluate various metrics and benchmarks for a robust API:

Use case: Standardizing API testing across 3500 applications at scale — Fiserv + Tricentis

Let’s take a look at an example use case for standardizing API testing.

Problem

Fiserv, a global leader in financial technology, manages a portfolio of over 3,500 applications, serving clients across banking, payments, and financial services.

Their quality engineering teams faced fragmented tooling, inconsistent testing practices, and a growing backlog of manual test cycles, slowing their delivery and increasing the risk of production incidents.

Solution

Fiserv utilised the Tricentis platform, including Tricentis Tosca, for end-to-end automation testing encompassing API testing workflows. They used qTest for enterprise test management and Tricentis Data Integrity for downstream data validation.

Outcome

Fiserv reduced its incidents by 65% and achieved consistent, auditable test coverage across thousands of applications, accelerating release cycles and reducing operational risk while meeting all its compliance requirements. (Read the full case study here.)

What is an example of API testing?

Let’s circle back to the earlier example of a payment transfer API. This API allows clients to initiate a money transfer.

This is what the API definition might look like:

API Endpoint URL: /v1/transfers

API Method Type: POST

A complete set of API tests would cover the following:

Happy path

A valid transfer should return a:

• 201 status code.
• Valid transaction ID present in the response that is not null.
• Timestamp of a valid ISO 8601 string.
• The amount in response that matches the one sent in the request.

Insufficient funds

If the transfer amount exceeds the balance, the API should return a:

• 422 status code stating unprocessable entities.
• Error message saying “insufficient funds.”
• No transaction ID in the response.
• Unchanged account balance after the API call.

Invalid account

If a transfer is made to or from a non-existent account, the API should return a:

• 404 status code indicating resource not found.
• Non-debited source account.

Unauthorized request

Missing or invalid authentication tokens should return a 401 status code indicating an unauthorized request or transaction. No transaction should be created here, and no data should be returned in the API response.

Negative amount

A negative or zero amount should return a 400 (bad requests) with a validation message. No changes should be made to the database; no transaction should actually occur.

Schema validation

The response body should conform to the documented contract, where all required fields should be present with the correct data types.

• Account number should be a number, not a string.
• Timestamp should be parsed as a valid ISO 8601.
• Currency should be exactly three characters.

Performance

For performance, API testing should validate:

• P95 latency under 300ms baseline.
• Graceful degradation at 500 concurrent users.
• Stable error rate below 1%.
• No 5XX responses during ramp-up.
• No duplicate transactions.

Benefits of API Testing

Implementing and following structured API testing enables the teams to utilise its benefits as shown below:

1. API tests are language agnostic

An API communicates over standard protocols like HTTP, gRPC, and GraphQL. The tests can be written in any language and run on any platform, regardless of the language the API itself has been written in.

A Java-based REST API can be tested using Python scripts. Being language agnostic gives teams flexibility in executing these tests.

API testing allows QA teams and developers to test them before they’re integrated with the frontend, speeding up the testing process and making it more efficient.

2. API tests are independent of UI

Backend APIs are usually built even before the interfaces are programmed. API testing allows QA teams and developers to test them before they’re integrated with the frontend, speeding up the testing process and making it more efficient.

3. API tests are faster and more stable

UI tests can be notorious and brittle. For example, if a button moves or a label on an input field changes, new tests need to be written.

Since APIs communicate with the service later, API tests are much more stable and less likely to change when client-side changes happen. This leads to lower maintenance overhead and higher confidence in test results for the teams.

4. API tests speed up releases

Because of their speed and versatility, API tests fit well in agile and modern DevOps culture, with short feedback loops leading to faster release cycles.

API testing best practices

Executing individual API tests is just a starting point. Building a robust, maintainable, and scalable API testing system is what separates high-performing quality engineering teams from the rest.

The following best practices can help you make the most of API testing:

1. Start with a risk-based test strategy where you prioritize API testing coverage for high-traffic paths and security-sensitive endpoints (e.g., authentication, financial layers, etc.).
2. Use OpenAPI/Swagger specifications to define and enforce API contracts early that validate common and standardised API behavior.
3. Narrow down the scope of test coverage, beginning with smoke tests and gradually including regression suites, edge cases, negative tests, etc.
4. Automate API testing and integrate it well with your existing CI/CD pipeline for fast feedback and automated test execution, making API testing more efficient and standardized
5. Use data-driven testing to run the same test logic against a variety of input combinations to increase coverage without increasing manual efforts for writing such tests.
6. Use service virtualization or mocking to simulate third-party behaviour that keeps your test suite fast and reliable.
7. Track test coverage and quality metrics by measuring endpoint coverage, test pass rates, mean time to detect regressions, etc. Treat these as engineering KPIs when developing and testing APIs.

While API testing has its benefits, many teams often struggle to implement effective API testing at scale.

Challenges and pitfalls in API testing

While API testing has its benefits, many teams often struggle to implement effective API testing at scale. Understanding some common challenges can improve your chances of building a durable testing strategy:

 

How agentic AI enhances API testing

Traditional API testing automations still require humans to author, maintain, and evolve every test case. Agentic AIs are autonomous systems that plan, execute, and iterate on multi-step processes without human intervention.

An agentic testing system can analyze API specifications and infer likely failures. It can generate a comprehensive test suite, execute it, and evaluate the results while also recommending remediation steps without human intervention.

Agentic API testing shifts the human role of writing and maintaining individual tests to defining quality goals and reviewing AI-generated test results. This can save teams considerable time, effort, and engineering resources to scale their product and business.

Platforms such as Tricentis Tosca enable agentic API test automation directly into your engineering workflow, letting your teams dramatically expand API test coverage without a proportional increase in test authoring effort.

This post was written by Siddhant Varma. Siddhant is a full stack JavaScript developer with expertise in frontend engineering. He’s worked with scaling multiple startups in India and has experience building products in the ed-tech and healthcare industries. Siddhant has a passion for teaching and a knack for writing. He’s also taught programming to many graduates, helping them become better future developers.