Compare MOZARK vs. NeoLoad

Evaluating app performance through distributed testing is essential for understanding the effects of cutting-edge technologies such as 5G, edge computing, and content delivery networks (CDNs), which are vital for enhancing user satisfaction. Our platform is specifically designed to offer a distributed digital measurement framework for both wireless and wireline networks, including cloud services and CDNs. Inadequately performing applications can result in significant declines in user engagement and revenue, highlighting the importance of pre-launch testing and ongoing, experience-centric monitoring. Our solution enables automated functional testing and user experience evaluations that are non-intrusive, facilitating the release of flawless applications and an improved experience within the app. As enterprises transition to cloud-based Software as a Service (SaaS) applications and embrace remote work, they face new challenges in maintaining smooth connectivity and optimal app performance for their workforce. Moreover, our platform allows for synthetic monitoring of app performance across various locations without requiring any SDK integration or modifications to existing code, ensuring comprehensive oversight of user experience across diverse environments.

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.