GitHub delivery evidence
Build and verify the change with supported GitHub context.
Ingest results from any runner, track each test as a stable identity across runs, and let three independent flakiness signals tell a real failure from a flaky one.
One connected loop, held on the stage this capability serves. The other stages stay as context so you can see what feeds in and what comes next.
Build and verify the change.
Build and verify the change with supported GitHub context.
Inspect delivery workflow activity in the connected release workspace.
Investigate test outcomes and flakiness evidence across runs.
Keep supported API contracts inspectable alongside release evidence.
Compare public cloud compute pricing as planning evidence.
Watch one test flap between pass and fail while everything around it stays green. That non-determinism is exactly what the three flakiness signals catch.
latest run · per test
history → latestEvery suite's duration fills to scale as the run is measured, and the slowest one is flagged so the bottleneck is obvious.
suite duration
4m 12sRerun, alternation, and windowed instability each catch a different shape of flake, so a test that only passes on retry and one that flips between runs are both caught.
A test that failed today but passed yesterday opens one entry per test-day with a resolve lifecycle, so new breakage is separated from old noise.
An honest limit
Test intelligence is reporting, not a test runner. Raw per-test rows are kept for 7 days while daily and monthly aggregates persist, and there is no quarantine, CI gating, or code-coverage ingestion here.
Ingest results from your supported CI.