JMeter Cloud Load Testing Tool
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Elevate Performance Testing with Powerful Cloud-Based JMeter
Experience a World-Class Test Design Process
Unlock High Volume Geo-Distributed Load Testing Infrastructure
Effortlessly import a JMX file into PFLB, configure load generator locations, and subject your application to hundreds of thousands of requests per second.
Manage test duration and user ramp-up, and run tests manually or seamlessly integrate them into your preferred CI pipeline.
Unlock High Volume Geo-Distributed Load Testing Infrastructure
Discover Load Testing Results with Grafana Dashboards
PFLB Client’s Review
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.
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 to optimize software performance.
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.
Benefits of JMeter Cloud Load Testing
Cloud-Based Execution
Scalable Testing
Comprehensive Scripting Options
AI-Powered Insights
Why Choose PFLB’s JMeter Cloud Based Load Testing?
User-Friendly
All-Inclusive JMeter Toolset
PFLB offers everything you need to run JMeter in the cloud. Easily upload and execute JMX files for advanced load testing scenarios. Enjoy the flexibility to tailor tests to your specific requirement.
AI-Powered Performance Insights
Expert Support
Our team of performance engineers, with over two decades of experience, offers expert guidance throughout. Our performance testing services ensure practical insights and solutions exactly when needed.
Integrations with Your Favourite Tools
- Google Analytics
Use real user data for precise load profiles.
- Grafana
Clear and actionable test reports.
- Postman, Insomnia, JMeter
Easy migration of existing test scenarios.
FAQs
01How do I upload my JMX files?
02Can I simulate traffic from multiple locations?
Yes, you can simulate user traffic from up to 18 different geo-locations to ensure realistic JMeter cloud testing.
03What scripting languages are supported?
04How JMeter is used for performance testing
05How to use JMeter for API testing?
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.