Dashboard
QA

QA Dashboard

A single view for test stability and failure patterns. It highlights failed and flaky tests, recent trends, and high-impact issues so QA teams can act quickly.

In QA view. Choose an Environment (for example, Production, Development) and a Period (7, 14, or 30 days). The dashboard refreshes to show metrics for that scope.

KPI Tiles

kpi tile

1. Test Case Executions

Number of tests run in the selected period. Helps QA and managers gauge coverage and CI activity.

2. Passed Test Case

Count of tests that passed. Helps managers read stability and QA confirm that recent fixes hold.

3. Failed Test Case

Count of tests that failed. Direct queue for QA triage and for developers to pick up fixes.

4. Average Time Duration

Average time per test run. Helps developers spot slow suites and managers track pipeline efficiency.

Most Flaky Tests

Most flaky test

Tests that pass and fail across runs. Helps QA prioritize stabilization and developers target fragile areas.

AI Insights

The QA Dashboard includes two AI-driven panels that explain failures and highlight patterns for the selected period, environment, and branches.

AI Insights

Test Failure Categories

An AI summary that categorizes failures by type and shows counts with the recent change. It separates real defects from test or environment noise so you can route work to the right owner.

  • Actual Bug
    A repeatable product defect; the same assertion or stack trace fails across runs. Fix the code and verify on a clean run.

  • UI Change
    The interface changed, and the test no longer matches (locator/text/timeout). Update selectors and assertions to the new UI.

  • Flaky Tests
    Intermittent failure from timing, order, shared state, network, or data setup. Stabilize with explicit waits, isolated state, and reliable data/mocks.

  • Miscellaneous
    Environment or pipeline problems, such as secrets, CI timeouts, or permissions. Correct the configuration/infra and re-run.

AI Insight Summaries

This panel calls out notable patterns and opportunities based on recent history.

1. Critical issues

Failures with the highest impact on release readiness. Guides managers on risk and QA on urgent triage.

2. Trend analysis

Patterns that are rising or repeating over time. Helps QA verify regressions and developers confirm that fixes stick.

3. Optimization opportunities

Tests or areas where speed or stability can improve. Helps developers reduce runtime and QA cut noise.

Cross-Environment Performance

cross environments

1. Pass rate

Percentage of passing tests per environment. Helps teams spot environment-specific problems.

2. Executions

The number of total tests executed in each environment. Helps assess coverage and workload by environment.

3. Flaky rate

Share of flaky tests per environment. Helps QA and developers find unstable setups.

4. Average Execution Time

Average execution time per environment. Helps detect slow environments and plan optimization.

OverviewDeveloper