Unidata watches every float your systems emit. Our adaptive statistics flag outliers in real time—no manual configuration, no competing data types, just precision on continuous measurements.
Active Anomalies
Monitored Systems
Detection Accuracy
Response Time
Unidata combines statistical analysis, machine learning, and pattern detection to identify outliers with precision
Standard deviation-based outlier detection
Identify statistical outliers beyond 3-4 standard deviations. Adapts dynamically to changing data patterns.
Time-series pattern recognition
Separate time series into components to identify anomalous deviations from seasonal patterns.
Data gap and corruption identification
Detect data gaps, transmission failures, and unexpected null patterns in metric streams.
Real-time anomalies identified by Unidata systems
| Metric | Source | Detection Method | Severity | Timestamp | Status |
|---|---|---|---|---|---|
| CPU Utilization Server Cluster | US-East-1 Server Group | Z-Score (4.2σ) | Critical | 2 minutes ago 12:04:23 UTC | Investigating |
| Network Latency Gateway Cluster | Network Edge Router-08 | Rolling Trend Alert | High | 12 minutes ago 11:54:47 UTC | Alert Sent |
| Read IOPS Storage System | SAN Storage Array-42 | Seasonal Deviation | Medium | 38 minutes ago 11:28:12 UTC | Resolved |
| Memory Usage Kubernetes Cluster | Container k8s-node-17 | Missing Data Pattern | Low | 1 hour ago 11:14:08 UTC | Resolved |
Seamlessly connect Unidata with your existing infrastructure and monitoring tools.
Integrations content coming soon...
Configure and manage alert notifications for detected anomalies.
Alerts content coming soon...
Ready to implement autonomous anomaly detection? Contact our team to learn more about Unidata.