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Description

Appvance IQ (AIQ), delivers transformative productivity gains and lower costs for both test creation and execution. It offers both AI-driven (fully automated tests) and 3rd-generation codeless scripting for test creation. These scripts are then executed using data-driven functional and performance, app-pen, and API testing -- both for web and mobile apps. AIQ's self healing technology allows you to cover all code with only 10% of the effort required by traditional testing systems. AIQ detects important bugs automatically and with minimal effort. No programming, scripting, logs, or recording are required. AIQ can be easily integrated with your existing DevOps tools, processes, and tools.

Description

A test execution is defined by a combination of a testing tool, a repository of tests, and specific arguments or parameters. You can utilize the out-of-the-box workflows provided by Testkube for various testing tools or create a personalized workflow tailored to your needs. It's possible to group related or unrelated test execution workflows into comprehensive suites for better organization. Additionally, you can establish a searchable repository filled with test executions that are ready to run. Proactive triggers allow you to initiate test executions in response to CI/CD events, on a manual basis, or according to a predefined schedule. Furthermore, you can set up your system to respond to Kubernetes infrastructure events, like deployments, to automatically launch test executions. With Kubernetes’s inherent scalability, you have the option to increase the number of concurrent test executions to meet demand. You can also take advantage of advanced scaling options to enhance load tests, allowing you to expand from a single execution to as many as 1,000. By parallelizing functional tests, you can significantly reduce the time required for completion. All logs and artifacts generated during the execution of test tools are stored in a centralized repository, making them easily accessible. Moreover, the system includes features for quickly identifying errors by highlighting keywords associated with failures in the logs. In addition, utilizing various filtering options can enhance your ability to sift through logs efficiently, ensuring a smoother debugging process.