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I was highly satisfied working with PFLB. They're a fantastic one-stop shop for software performance, with everything you need—their platform and skilled engineers. I've used them three times to load test the College Board software before big updates, and it all went smoothly. Plus, I love that they store all the testing data, so we can track performance capacity over time.
It was a pleasure working with PFLB, and I'd recommend them for performance testing. They quickly got up to speed with our complex software architecture and were super productive in setting up our load test environment in the cloud. They were really dedicated to improving our product with their strong expertise in performance optimization.
PFLB was willing to work with a very small solopreneur without an enormous investment in capital. Their prices were reasonable and provided me with notable improvements to my php performance.
PFLB did benchmarking tests on our database storage engine under standard and uncommon conditions, using specialized tools. Their analysis gave us valuable insights and recommendations to boost our product's performance. I highly recommend PFLB to anyone looking for an expert performance testing company.
We smoothly moved over 30 JMeter projects to PFLB, and it's been a total game changer. It's given our team of 50+ remote performance engineers the ability to handle large-scale load tests every day with real ease.
PFLB's testing team helped us successfully complete the FDA regulations with a great test coverage for the computer system validation (CSV) process at Illumina. I highly recommend Yuri Kovalov and his team—they're top-notch professionals in performance and load testing.
PFLB has been Tinder's load testing provider for over 5 years, and it is a true pleasure working with them. They managed the entire performance engineering process for our app releases, helping us fix tons of performance issues. I highly recommend PFLB as a reliable vendor.
5.0
Use real user data for precise load profiles.
Clear and actionable test reports.
Easy migration of existing test scenarios.
Simply drag and drop your JMX files into the PFLB cloud platform and start your tests immediately.
Yes, you can simulate user traffic from up to 18 different geo-locations to ensure realistic JMeter cloud testing.
Our platform supports JavaScript, BeanShell, JMEX, Groovy, and the No Code Script Builder.
JMeter Cloud Performance Testing starts with downloading and setting up JMeter on your system. You then create test plans to simulate traffic to your web application, allowing you to measure response times and throughput to assess the performance under various conditions. JMeter is widely used in banking performance testing services.
To use JMeter for API testing, start by setting up JMeter on your system. Create a new test plan and add HTTP Request samplers to define the API endpoints you want to test. Configure the request parameters, headers, and body content as needed for your API. Run the test to simulate traffic and analyze the responses to assess the API’s performance and reliability under different conditions.
To perform spike testing in JMeter, first set up your basic test plan with the necessary HTTP requests. Then, use the Synchronizing Timer to control and synchronize multiple threads, allowing them to hit the server at the exact same moment. Configure the number of threads to simulate the sudden increase in load (spike). Execute the test to observe how the system handles sudden surges in traffic and analyze the results to assess performance stability during peak loads. This method is particularly useful for e-learning software performance testing , where traffic can spike during key events like online exams or course launches.
JMeter is not designed for direct UI testing as it doesn’t interact with web pages like a browser. For UI interactions like clicks, tools like Selenium are better suited, but you can use JMeter to test the performance of web UI components by targeting the underlying HTTP requests.
To perform stress testing in JMeter, set up your test plan with the necessary HTTP requests. Gradually increase the number of threads (users) and the load duration to find the point at which your application's performance degrades or fails. This helps identify the application's capacity limits and ensures it can handle high traffic before becoming unstable.
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