Introducing anomaly detection in Datadog

Anomaly detection has been added to Datadog to provide deeper context for dynamic metrics like application throughput, web requests, and user logins. The feature analyzes a metric's historical behavior to distinguish between normal and abnormal trends. It accounts for seasonality and can separate the trend component from the seasonal component of a timeseries. Anomaly detection is available in Datadog and complements outlier detection, which identifies unexpected differences in behavior among multiple entities reporting the same metric.

No tracked trend matches for this post yet.

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