Statistical
Log Pattern Mix
Updated Oct 24, 2026 · today
Raises warnings when a service’s mix of known log patterns departs from its learned baseline.
Example alert
Exact wording varies — the detector generates titles from the anomaly it finds. This is representative of what an alert looks like when it fires.
Availability
Runs on these tiers:
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Open alerts in the sandbox →Related detectors
- Volume Anomaly
Detects spikes, drops, and flatlines in log volume vs daily and weekly baselines per service.
- Silence Detection
Catches services that stop logging when they normally log every N seconds. The most dangerous failure mode: no errors, just absence.
- Outlier Detection
Multi-dimensional outliers in log feature space. Catches subtle anomalies that single-axis thresholds miss.
- Numeric Field Anomaly
Discovers the numeric fields your logs carry — payment amounts, cache hit rates, queue depths, inference scores — and flags when one drifts from its baseline.
- Post-Change Regression
Checks whether a deploy, config change or scale event actually made things worse, by comparing the window after the change against the matched window before it — per service.