Common Problems Faced with API Testing with Postman and Modern Alternatives

API testing is one of the most integral parts of the SDLC that helps in ensuring these application services or microservices work as intended. Postman has become the de facto method for API testing due to a user-friendly interface to create, test, and automate API requests. However, despite a relatively comprehensive set of features, some limitations and challenges have become associated with Postman that hamper the productivity of software engineers, QA testers, and SDETs.

This blog is written by Jeremy Rivera at KushoAI. We're building the fastest way to test your APIs. It's completely free and you can sign up here.

Common Issues When API Testing with Postman

1. Insufficient Collaborative Capabilities

Where Postman provides some of the core collaboration features such as shared workspaces, it is limited in several ways. Collaboration can be a crux for larger teams in distributed environments. Most often, it is required to keep the version control of API tests.

Meanwhile, the problem of insufficient fine-grained access control and versioning, especially within free-tier plans, puts severe demands on test-case management among larger teams.

Implications: Teams may encounter difficulties in upholding consistency throughout testing environments, which could result in variations in test outcomes.

2. Performance Limitations with Large Collections

Postman collections serve as an effective means of structuring various API tests; however, as these collections expand, performance-related challenges also arise. The management of extensive collections may lead to prolonged execution durations, heightened memory usage, and sporadic system freezes.

Performance is said to degrade when Postman operates with large collections of API tests or sizeable datasets

Impact: The execution of big test suites is very time-consuming and counterproductive for performance testing or inclusion in a CI/CD pipeline.

3. Poor CI/CD Integration

Setting up Postman through Newman in CI/CD pipelines, although possible, often falls short of the depth of integration that a developer would want for continuous testing. This will seem somewhat clunky compared to a native testing framework.

Issue: Complex setup and limited flexibility with CI/CD tools like Jenkins, GitLab, and others.

Consequences: Teams looking to implement seamless continuous integration and deployment may find it challenging to integrate Postman into an automated workflow.

4. Claims and Test Script Development

So far, Postman is using JavaScript to build test scripts and assertions-a powerful feature, but there are certainly limitations on debugging and how complex tests can be. Large or complex test scenarios become far more difficult to manage through the Postman scripts when these go beyond basic request and response checks.

Problem: Lack of availability of advanced debugging and test management instruments.

Implications: Testers may find it challenging to design and debug complex conditions. This increases the likelihood of missing defects related to exceptional cases.

5. Poor support for assessment of load and stress

While Postman is highly appropriate for functional API testing, it is definitely not suitable for load or performance testing at all. It does not support significant traffic or intricate scenarios, and hence will have reduced effectiveness in reviewing API behavior under stress.

Problem: Inability to successfully emulate high-traffic load testing scenarios.

Outcomes: Teams relying on Postman to perform performance testing will not catch critical scalability issues that, when the application sees real traffic conditions, bottlenecks will occur in production.

Alternatives to Postman for API Testing

Although Postman is a powerful tool, there are many modern alternatives which address some of the limitations of the application. Here are a few options for your needs in specific areas of your testing strategy.

1. Insomnia

Insomnia is a professional API testing tool with a clean, minimalistic interface. It may be less feature-heavy compared to Postman, but it is lightweight, fast, and fits a single developer's needs perfectly, who is seeking speed and intuitiveness.

Strengths: Simple, fast, and supports GraphQL out of the box.

Ideal for: Small teams or freelance software developers focused on simplicity and speed of API testing.

2. Swagger and OpenAPI Tools

Swagger, put together with other OpenAPI tools, provides complete design, documentation, and testing for APIs. In Swagger, testing capabilities are completely integrated into its API documentation tools, making it an ideal tool for teams following the API-first approach to development.

Strong points: Best-in-class documentation integration, with automatic test generation from OpenAPI specs.

Best For: Teams prioritizing API documentation and auto-generated tests for OpenAPI or Swagger-compliant APIs.

3. Katalon Studio

Katalon Studio is a multi-purpose testing platform that provides substantial sets of features for API, web application, and mobile testing. Strong automation frameworks come with integrated API testing in their core, making this tool an attractive option in teams operating with complicated workflows.

Strong points: high level of automation, support for API testing, and well-integrated with popular CI/CD tools. Best For: The teams looking for an all-in-one solution to automate functional, UI, and API tests.

4. Karate

Karate is an open-source API testing framework that enables testers to write tests in a simplified Gherkin-like language. This would make it more available to those with no technical background. Karate also enables end-to-end API testing and brings about good integrations into CI/CD pipelines. Strengths: A simple DSL for writing tests; it supports both REST and SOAP, and also integrates with CI/CD pipelines. Best For: Teams needing simplicity, bold statements, and pain-free continuous integration and continuous deployment. 5. Gatling Gatling is a performance and stress-testing tool for APIs. Basically, it offers developers and testers the chance to simulate high volumes of traffic and understand why certain parts of the application bottleneck. While it won't function well for functional testing, it shines where Postman does not: load testing. Strengths: Excellent for load and stress testing, with detailed performance reports. Best For: Performance testing-focused teams working with APIs under very high loads.

Postman remains one of the most used and easy-to-use tools for API testing, but it does have some limitations. For larger teams, projects that require complex assertions, or projects focused on load and performance testing, other tools like Insomnia, Swagger, Katalon, Karate, and Gatling offer richer and more specialized capabilities. The type of tool to use would, therefore, need consideration of specific needs that your team and project might have. Be it deeper CI/CD integration, better collaborative features, or advanced performance testing; there exists an alternative to fit your testing strategy. Teams can optimize API testing processes for higher quality software delivered faster and more efficiently by exploring some of these options.

This blog is written by Jeremy Rivera at KushoAI. We're building an AI agent that tests your APIs for you. Bring in API information and watch KushoAI turn it into fully functional and exhaustive test suites in minutes.