Measure Your Tests:

Wrap your existing code with measurement collectors to track arbitrary custom metrics.

def example(): Unit = {
  using collectors { new CpuUsageCollector } measure { yourServiceCall() }

Track Historical Test Performance:

All measurements are writtent to a SQL database for further analysis. Plot your performance over time to review historical trends.

Detect Anomalies:

Ships with ML-based anomaly detection, so you always know when your tests aren’t executing as expected.

Conduct Statistical Significance Testing:

Unconvinced that your alternative method implementation is truly faster? Measure both and let the p-value decide!