Analytics

The Analytics page aggregates runs across a date range so you can see trends rather than individual outcomes. It answers the questions a single run cannot: is our pass rate drifting, which test is eating the most time, and which one fails just often enough to be annoying.

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1. 1Change the window: 7, 30, or 90 days.
2. 2Totals for the window, with pass rate and average duration.
3. 3Runs over time. A red band shows the day a failure appeared.
4. 4Flakiest tests. This is the most useful list on the page: fix these or delete them.
5. 5Most active tests, which is usually where your monthly allowance is going.

What it shows

• A summary of total, passed, and failed runs, with the overall pass rate and average duration.
• A daily timeseries so you can see when a change in pass rate began.
• Slowest tests, ranked by average duration.
• Flakiest tests, the ones that alternate between passing and failing rather than staying broken.
• Busiest tests, ranked by how many runs they consume.

Filtering by environment

If your workspace uses environments, an environment filter narrows every figure on the page to All environments, No environment, or one environment. Flakiness is worked out per test per environment, so a test that is stable on Production but flaky on Staging appears in the flakiest list with its Staging label.

Reading the flakiest list

This is the most useful list on the page, because a flaky test is worse than a broken one. A test that always fails gets fixed. A test that fails one run in six trains everybody to ignore red, which eventually means ignoring a real failure. Anything appearing here is worth either fixing properly or removing.

Watching the busiest list

If you are running out of monthly runs sooner than expected, the busiest list usually explains why. It is common to find one test on a five-minute schedule quietly consuming most of the allowance for a journey that would be fine checked hourly.