Catching Anomalies Before They Become Incidents
Proactive anomaly detection replaced a threshold-alert setup that mostly told the team about problems after customers already felt them.
- Client
- E-Commerce Platform (Peak-Season Traffic Spikes)
- Digital Worker
- Application Support Digital Engineer
Fewer false-positive alerts
Faster time-to-detect for real issues
Of anomalies caught before customer impact
From the problem to the result.
The challenge
Alerting was threshold-based and noisy, so real anomalies were buried in false positives and usually surfaced only after customers reported issues.
What Nevarix did
Nevarix introduced behavior-based anomaly detection across the application's health signals, with automated ticket creation and routing the moment a genuine deviation appears.
The outcome
The team now catches degradation before it becomes an outage, and alert fatigue dropped enough that real signals actually get attention.
Application Support Digital Engineer
Watches system health signals and surfaces anomalies before they become incidents.
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