Exploring API Performance Testing with Postman
23/12/2024
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Hello, tech enthusiasts and creative developers! I’m Vu, the author of SupremeTech’s performance testing series. In the article “The Ultimate Guide to JMeter Performance Testing Tool,” we explored JMeter’s strengths and critical role in performance testing. Today, I’m introducing an exciting and straightforward way to do API performance testing using Postman.
API performance testing with Postman lets you reuse the collections you already have to simulate many virtual users calling your API at the same time, then measure response time, error rate and throughput. It is a quick way to check how your API behaves under load before release, without setting up a separate load-testing tool. In this guide, I will walk through the five steps to run a test, how to make the simulation more realistic and what to watch out for so your results stay reliable.
What is Postman?
Postman is a robust API (Application Programming Interface) platform that empowers developers to quickly design, test, document, and interact with APIs. It is a widely used tool for testing APIs, which is valuable in software development, primarily web or mobile app development.
Why Use Postman for API Testing?
Postman is favored by software developers, testers, and API specialists because of its many advantages:
- User-Friendly Interface: Postman’s intuitive design makes it easy to use.
- Supports Diverse HTTP Methods: It handles requests such as GET, POST, PUT, DELETE, PATCH, OPTIONS, and more.
- Flexible Configuration: Easily manage API request headers, parameters, and body settings.
- Test Automation with Scripts: Write JavaScript code within the Tests tab to automate API response validation.
- Integration with CI/CD: Postman’s CLI tool, Newman, seamlessly integrates with CI/CD pipelines, enabling automated API testing in development workflows.
- API Documentation and Sharing: Create and share API documentation with team members or clients effortlessly.
Read more:
Performance API Testing on Postman
As of mid-2024, Postman introduced a new feature allowing users to perform API performance testing quickly and conveniently. With just a few simple steps, you can evaluate your API’s performance under high load and ensure its strength.
Step 1: Select the Collection for Performance Testing
- Open Postman and navigate to the Collections tab on the left sidebar.
- Choose the Collection or Folder you want to test.
Step 2: Launch the Collection Runner
- After selecting your desired Collection or Folder, click Run Collection to open the Collection Runner window.
- In the Runner, select the APIs you want to include in the performance test.
- Switch to the Performance tab and choose a simulation method:
- Fixed: Simulates a fixed number of users.
- Ramp Up: Starts with a few users and gradually increases.
- Spike: Introduces a sudden surge in traffic followed by a reduction.
- Peak: Increases traffic to a high level and sustains it for a period.
Step 3: Adjust Virtual Users and Test Duration
- Configure the Virtual Users and Test Duration settings to simulate the desired load.
- Start with smaller values, then gradually increase them to gain a clear understanding of your API’s performance under varying conditions.
Step 4: Run the Test
- Click Run to start the performance test.
- During the test, Postman will send API requests and provide real-time data on:
- Response Time: The API’s duration to respond to a request.
- Error Rate: The percentage of failed requests.
- Throughput: The number of API requests the system can handle per second.
Step 5: Analyze the Report
Once the test is complete, Postman generates a detailed report, including:
- Response Time: Tracks the duration it takes for APIs to process requests.
- Error Rate: Highlights any issues encountered during testing.
- Throughput: Measures the system’s capacity to process requests under load.
Use these metrics to evaluate whether your API performs efficiently under heavy traffic. These insights will guide you in optimizing your API for better performance.
Leverage Customization for Realistic User Simulation
Postman allows you to customize request data for each virtual user. You can upload a CSV or JSON file with unique datasets if you want different data for each user. This feature enables a more accurate simulation of real-world user behavior.
After each test run, Postman provides an easy-to-understand report highlighting the areas for improvement. You can track performance changes and compare test results to identify weaknesses and refine your API.
Tips for More Reliable API Performance Tests in Postman
A performance test is only useful if its results reflect your API rather than the limits of the test setup. These practices help keep your results trustworthy.
Watch the resources of the machine running the test
When you run a test locally, Postman sends all requests from the computer running it. The number of virtual users you can simulate therefore depends on that machine’s available resources and on the collection you use, and pre-request or post-response scripts reduce the number of virtual users Postman can simulate. If the machine is overloaded, slow results may come from your laptop rather than your API.
Start small, then scale up
Postman recommends beginning with a small test of 10 to 20 virtual users and observing system resource usage. Increase the load step by step and compare runs, so you can see where response time or error rate starts to change.
Choose where to run the test
Besides the desktop app, Postman can run performance tests through the Postman CLI, which fits CI/CD pipelines, or in Postman’s cloud infrastructure for larger loads. Cloud runs are available on paid Postman plans.
Test in an environment that matches production
Run tests against a staging environment that is as close to production as possible, and agree on test windows with the teams that own the API and its dependencies. Load tests against shared or production systems can affect real users and other services.
Performance Testing and Regression Testing: Why Your API Needs Both
Performance testing answers one question: how fast and stable is the API under load? It does not confirm whether the API still returns the right data after a developer changes the code. That is the job of regression testing, which repeats functional checks before every release to catch features that have broken unexpectedly.
As release cycles get shorter, repeating these checks by hand quickly becomes a bottleneck. SupremeTech’s AI-powered regression testing service converts manual test cases into automated checks for APIs, web journeys and batch jobs in one framework. AI drafts the automated tests, experienced engineers review and approve each one, and approved tests run automatically when code changes, with reports that include recordings and execution records for faster investigation.
Test and Optimize Your API with Postman
With Postman’s new performance testing feature, API optimization has never been easier. It helps you quickly identify and address potential issues to ensure your system is always ready to handle user demands effectively and reliably.
For more details and step-by-step guidance, check out the following resources on the Postman website:
- Overview
- Run a performance test
- View performance test metrics
- Debug performance test errors
- Inject data into virtual users
Start your API performance optimization journey with Postman and prepare your system to meet every demand seamlessly.
Read more:
If your team also spends too much time repeating API and functional checks before each release, explore SupremeTech’s AI-powered regression testing solution or contact our team to discuss your testing workflow.
Frequently Asked Questions
Yes. Postman has a built-in performance testing feature that uses the requests in a collection or folder to simulate many virtual users calling your API in parallel. You can run it from the Postman desktop app, through the Postman CLI in a CI/CD pipeline, or in Postman’s cloud on paid plans.
For local runs, there is no fixed number. It depends on the resources of the machine running the test and on how heavy your collection is, and scripts in requests reduce the number of users you can simulate. Start with 10 to 20 virtual users, check CPU and memory usage, then scale up. For larger loads, Postman’s cloud runs distribute the test across multiple machines.
Focus on three core metrics. Response time shows how long the API takes to answer requests. Error rate shows the percentage of failed requests. Throughput shows how many requests the API handles per second. Compare these across runs with different loads to find the point where performance starts to degrade.
Use Postman when you want a quick performance check that reuses your existing API collections with little setup. A dedicated tool such as JMeter is usually a better fit for complex scenarios, very large distributed loads or protocols beyond HTTP APIs. Many teams start with Postman for early feedback and move to a dedicated tool for full-scale load testing.
Yes. The Postman CLI can trigger performance tests from your CI/CD pipeline, so you can check API performance as part of your regular build or release process. Make sure the runner machine has enough resources for the load you configure, or the results may reflect the runner’s limits instead of your API.
No. Performance testing measures speed and stability under load, while regression testing checks that existing features still behave correctly after code changes. A release can pass a performance test and still return wrong data. Teams usually automate both, for example by pairing Postman performance tests with an automated regression suite such as SupremeTech’s AI-powered regression testing service.
