Why did the bands of my anomaly detector in CloudWatch change suddenly?

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CloudWatch applies statistical and machine learning algorithms when you enable anomaly detection for a metric. These algorithms analyze the metric, detect normal baselines, and then surface anomalies with no user intervention. The algorithms generate an anomaly detection model. The model generates a range of expected values that represent normal metric behavior.

After you create a model, CloudWatch anomaly detection continually evaluates the model and makes adjustments. It does this to make sure that its analysis is as accurate as possible. If another anomaly detection model that is trained with the most recent data performs better than the current model, then CloudWatch anomaly detection switches to the new model. This can cause the anomaly detection bands to shift.

Related information

Using CloudWatch anomaly detection