This chart shows daily runs, split by Passed tests (green) and Failed tests (red). Hover over a date to see exact counts. Use it to spot spikes, compare days, and correlate changes with deployments or data updates.
Measures the percentage of executions with inconsistent results for the same code (pass in one run, fail in another) and tracks problematic tests. This is a noise indicator.A list of Flaky Tests on the right shows the name, spec file, and execution date.
High flakiness means wasted triage and unreliable signals.
Track the curve after fixes to confirm deflakes are effective.
Measures the percentage of test executions that are failing for the first time compared to previous runs.A list of the New Failures on the right shows the name, spec file, and execution date for every newly failed test.Use it to detect regressions early:
Spikes indicate recent changes that may have introduced defects or test failures.
A flat or declining line indicates improved stability for newly added or recently touched areas.
This chart analyzes your test-retry behavior over the selected time period, environment, and branch. A rising trend suggests your tests are becoming unstable or “flaky.”It shows three daily metrics:
Total Retries: The number of times tests were re-run.
Total Runs: The total number of test suites executed.
Retried Test Cases: The number of unique tests that needed a retry.