December’25 Updates: JMeter Workflows in HyperExecute, New Additions in KaneAI and More

HyperExecute Workflows for JMeter Projects

HyperExecute now supports Workflows for JMeter projects, allowing teams to orchestrate, automate, and manage performance testing more efficiently within CI/CD pipelines.

Workflows in HyperExecute help teams simulate real-world CI/CD practices, giving them a framework to manage complex performance testing scenarios without constant manual intervention.

It reduces the need for repetitive manual setups while giving teams better visibility into test execution. You can define sequences of JMeter tests, track execution results, and ensure repeatable performance analysis across different environments.

Chrome for Testing in HyperExecute

HyperExecute now includes support for Chrome for Testing, providing predictable browser versions that align with corresponding ChromeDriver releases.

With Chrome for Testing, you can target specific versions to prevent flaky failures caused by mismatched browser-driver combinations. This improves the reliability of automated tests, reduces debugging time, and maintains consistency across all stages of the testing pipeline.

Generate Playwright Lighthouse Reports in HyperExecute

HyperExecute now supports generating Lighthouse reports directly from Playwright workflows. This enables teams to monitor key aspects of web performance, accessibility, SEO, and best practices without leaving their testing environment.

Integrating Lighthouse reporting directly into Playwright tests provides immediate feedback and actionable insights without additional manual steps or separate tools. You can assess performance metrics, identify accessibility issues, and track SEO improvements automatically during test runs.

To get started, check out this documentation on Lighthouse Playwright reports in HyperExecute.

Latest Features in TestMu KaneAI

The updates below focus on everyday gaps teams hit while building and running tests in KaneAI. The changes improve how mobile tests behave, how configurations are managed, and how test flows are controlled.

Below are the key features and enhancements across KaneAI:

• GPS Support in KaneAI for Mobile Authoring: With the KaneAI GPS feature for mobile authoring, you can simulate real-world locations to validate location-based user flows in mobile tests. This feature is particularly useful for apps that rely on geolocation for functionality or personalization.
• Accessibility Support for KaneAI Mobile Authoring: We now support accessibility testing for mobile authoring. You can now validate accessibility labels, roles, and assistive behaviors within mobile test flows. This helps ensure that your applications are inclusive and meet accessibility standards.
• Module Bulk Update & Module Delete (Behind Feature Flag): With bulk module update in KaneAI, you can now update multiple modules at once and safely remove unused ones. This functionality is being gradually rolled out behind a feature flag to ensure controlled adoption.
• GCP Spanner Support in KaneAI Database: You can now connect Google Cloud Spanner as a data source for data-driven test validations. This expands the range of data integrations in KaneAI.
• Sequential Execution in KaneAI Test Runs: KaneAI now allows defining the exact order in which test cases are executed. This is especially useful for dependency-driven testing and flow-based scenarios.

Bonus: In TestMu AI Test Manager, you can now manage and edit shared test configurations in KaneAI across projects from a single central location. This ensures consistent settings across all runs, reducing errors and simplifying maintenance.

Wrapping Up!

The December updates extend browser support, improve performance testing workflows, enhance mobile testing capabilities, and simplify configuration management.

Teams can now orchestrate JMeter executions, run stable Chrome tests, generate Lighthouse performance reports, and manage KaneAI projects more efficiently.

These improvements reduce manual effort, improve reliability, and provide better insights into test results, allowing teams to focus on delivering quality applications without disrupting existing workflows.