Industry-average MTTD is 4+ hours, the team finds out from a customer or the CEO before they find out from monitoring.
Most outages do not start as a metric crossing a threshold, they start as a subtle change in pattern: a slow uptick in p99, a slight rise in queue depth, a deploy that nudged error rate up by 0.2%. Static thresholds miss those because they're set high enough to avoid noise. By the time the metric crosses the threshold, the incident has been live for an hour, the support inbox has 80 tickets, and the CEO has Slacked engineering.
Nova's predictive engine watches every signal and flags pattern deviations before they cross thresholds, with deploy and topology context applied automatically.
Nova builds a baseline per service and per signal from 30 days of history. Anomaly scores update every few seconds and the timeline surfaces the moment a service starts drifting.
A 5x spike during a known deploy is not the same as a 5x spike at 3am. Nova correlates anomalies with active deploys, maintenance windows, and traffic patterns to suppress expected behavior.
Nova runs scripted user-journeys from external locations every 1-5 minutes, so even during low-traffic windows when RUM has no signal, you have a steady detection pulse.
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