Compare Gauntlt vs. NeoLoad

Gauntlt offers integrations with various security tools, enabling security, development, and operations teams to work together effectively in creating robust software. It is designed to enhance testing and foster communication among different teams, allowing for the creation of practical tests that can be incorporated into deployment and testing workflows. The attacks in Gauntlt are composed in a straightforward language that is easy to understand. It seamlessly integrates with your organization's existing testing tools and processes. Included with Gauntlt are security tool adapters that streamline the integration process. It utilizes standard error and standard output from Unix to communicate status updates. There are two primary methods for getting started with Gauntlt: you can either install it via the gem method, which requires you to download and configure the security tools (but rest assured, Gauntlt provides guidance throughout this process), or opt for the Gauntlt Starter Kit, a Vagrant script that automatically sets up the necessary tools for you. Traditionally, security testing occurs according to the auditors' timelines, and the resulting outputs often lack actionable insights, highlighting the need for more efficient solutions in security testing protocols. By using Gauntlt, teams can shift towards a more proactive and integrated approach to security testing, ultimately improving the overall security posture of their software projects.

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.