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About LogicMonitorProactive observability
LogicMonitor’s Anomaly Detection uses machine learning to identify when resource behavior deviates from expected patterns—so you can catch early warning signs, prevent incidents, and troubleshoot smarter.
Why Anomaly Detection
Anomaly Detection learns how your systems typically behave, then flags deviations from those patterns—helping your teams get ahead of outages, misconfigurations, and performance degradations.
Identify unexpected behavior across metrics without writing rules or thresholds—just enable and go.
What you can do with Anomaly Detection
Anomaly Detection helps your teams stay ahead of issues by automatically modeling what’s normal—and flagging what’s not—across all your monitored metrics.
LogicMonitor continuously analyzes your metric history to understand baseline performance, detect trends, and account for seasonality.
When current behavior falls outside the expected range, Anomaly Detection flags it—helping you catch early signs of trouble.
Predict trends with forward-looking models that help teams plan capacity, avoid bottlenecks, and optimize resource usage.
View anomaly bands and actual performance on the same graph—making it easy to spot when and where things drifted.
Anomaly Detection is part of LogicMonitor’s core platform experience—no extra tools, scripts, or configuration needed.
