GENGHIS3 Beta
Beyond Limits, Beyond Bugs: Elevate Your Software's Performance with Our Testing Expertise.Load test and analyze your application to identify performance bottlenecks and optimize performance.
Harness GENGHIS3 Beta Features to Test Your Applications Under Stress
Unwavering Precision in Traffic Orchestration
GENGHIS3 Beta adheres to a meticulously crafted schedule, executing each request with unwavering precision, delivering a controlled and consistent testing environment.
Seamless Traffic Dynamics for Realistic Testing
Simulating the lifecycle of real-world traffic, incorporating the gradual buildup, peak periods, and eventual decline to provide a realistic performance evaluation.
Unveiling Hidden Performance Patterns with Super-High Granularity
Circllhist histogram excels in capturing the intricate details of latency measurements, providing a highly granular view of system performance.
A Versatile Toolset for Comprehensive Performance Testing
GENGHIS3 Beta seamlessly exchanges data with other instances via NATS messages, ensuring seamless collaboration and synchronization during load testing.
Define Traffic with Precision: Leveraging Postman Collections
Postman collections - a beloved tool among developers, to streamline your performance testing efforts.
Performance Testing Made Easy
Software Developer
Quick feedback with short tests: GENGHIS3 Beta provides a quick feedback loop for developers, enabling them to verify their implementation with short tests. This makes it easy to identify and resolve performance bottlenecks early on.
Easy to compare with circllhist: The steady timeline execution of GENGHIS3 Beta allows developers to easily compare test results with circllhist, a widely used performance testing tool. This facilitates the identification of performance trends and patterns.
Incident Replication
Simulate complex traffic: GENGHIS3 Beta's traffic control via NATS messages enables developers to easily replicate the most complex traffic that caused an issue. This allows them to thoroughly investigate the root cause of the incident and implement preventive measures.
Simple scripting and configuration: GENGHIS3 Beta's simple scripting and configuration options make it easy to replicate incidents and observe the target system under various conditions. This helps developers gain a deeper understanding of the system's behavior and its response to different scenarios.
Verifying Subsystem Performance
Feed generator and load generator modes: GENGHIS3 Beta's feed generator and load generator modes provide a comprehensive solution for verifying subsystem performance. The feed generator generates subsequent data in the business logic, mimicking real-world user interactions, and sends the results to the load generator via NATS.
Remote deployment and data control: The feed generator can be deployed on a remote host, offloading the load generator and allowing for centralized control of the data feed. This enables developers to focus on the load generator and its performance testing capabilities.
Flexible data feed: The amount of data fed to the load generator can be adjusted based on the specific test requirements. Additionally, the load generator can handle various data formats, including CSV files and NATS messages.
Postman Collection as Single Source of Truth
Agile collaboration: GENGHIS3 Beta integrates with Postman collections, the de-facto standard for documenting API requests. This facilitates seamless collaboration between developers and performance testers, ensuring that everyone is working with the same set of information.
Simplified test creation: By using Postman collections as the single source of truth, test creation becomes much simpler. Developers can easily generate load tests from their Postman collections, saving time and effort.
Improved test execution: With Postman collections integrated, test execution is more accurate and consistent. The load generator accurately reflects the requests defined in the Postman collections, ensuring that the test results reflect the expected behavior of the system.