Compare Loadero vs. NeoLoad

Loadero is an innovative SaaS platform designed for conducting comprehensive end-to-end testing of web applications in the cloud. By harnessing the power of Selenium for browser automation, it effectively emulates real user interactions with the application under test. Users can customize various parameters, including browser versions, geographic locations, network conditions, and even media inputs to replicate webcam and microphone usage. This flexibility enables the effective load testing of a variety of web applications, particularly those that incorporate WebRTC technology for video communication and conferencing. The platform can simulate thousands of users in a single test scenario, providing a robust environment for performance assessment. Upon the conclusion of each test, Loadero automatically runs pre-established assertions to verify results. Tests can be initiated from any of Loadero's 12 global physical locations, ensuring thorough performance evaluations across diverse geographic areas. If your organization regularly conducts tests for multiple clients, consider opting for a monthly subscription to benefit from reduced costs per participant. Additionally, should you exhaust the compute units included in your plan, there's always the option to purchase additional units as needed. This adaptability makes Loadero an essential tool for teams striving to maintain high-quality web applications.

Software for continuous performance testing to automate API load and application testing. For complex applications, you can design code-free performance tests. Script performance tests in automated pipelines for API test. You can design, maintain, and run performance tests in code. Then analyze the results within continuous integration pipelines with pre-packaged plugins for CI/CD tools or the NeoLoad API. You can quickly create test scripts for large, complex applications with a graphical user interface. This allows you to skip the tedious task of manually coding new or updated tests. SLAs can be defined based on the built-in monitoring metrics. To determine the app's performance, put pressure on it and compare SLAs with server-level statistics. Automate pass/fail triggers using SLAs. Contributes to root cause analysis. Automatic test script updates make it easier to update test scripts. For easy maintenance, update only the affected part of the test and re-use any remaining.