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AI-Native Test Observability For Smarter Reporting

Test observability enables analysis of system behavior and performance during testing, helping to detect, diagnose and improve issues.

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Best Egg

"We figured out a more efficient way to monitor system health and resolve failures earlier in lower environments."

Tenny , Engineering Operations Lead

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The Need for AI-Native Test Observability

Test observability is crucial for swiftly identifying and resolving issues during testing, improving software quality, and making data-driven decisions to enhance overall system reliability.

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Features of AI-Native Test Observability

App Profiling dashboard provides metrics to identify bottlenecks and optimize performance.

App Profiling Insights

Export Reports

  • Export widget data to CSV for further analysis in spreadsheets.
  • Save widget data as a PDF for clean, shareable reports.
  • Export data for future reference and easy access to historical insights.

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Customize Usage Reports

  • Analyze trends by selecting custom date ranges to spot usage increase or drops.
  • Adjust time windows to analyze past performance in detail.

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What is Test Observability and Test Intelligence?

Test observability focuses on the ability to continuously monitor and assess the performance of a system during testing. It collects data from various sources, such as logs, metrics, and traces, to provide insights into how the system behaves. This approach helps identify issues and failures in real time, enabling teams to make informed decisions and optimize testing efforts to improve overall system reliability and performance.

Test Intelligence, however, builds on observability by incorporating AI and machine learning to transform raw test data into actionable insights. It automates the identification of root causes, categorizes failures, and predicts potential issues before they occur, allowing teams to address issues. With features like smart test prioritization, automated alerts, and noise reduction, Test Intelligence streamlines the debugging process, accelerates resolution times, and enhances the overall testing strategy.

Ensure QA Efficiency with AI Native Test Insights

AI Native Test Intelligence

AI Native Test Intelligence

Uses AI to analyze test data, identify issues, and optimize test execution.

AI Native Test Analytics

AI Native Test Analytics

Uses centralized data to measure, track, and improve software testing processes.

Dashlane

50%

reduction in test execution time

“HyperExecute is a highly reliable test execution platform and has excellent customer support.”

Sagar Uday Kumar

Sr. Engineering Manager

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Frequently asked questions