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Metric data point reference

To view information about a specific data point, rest the cursor over that point in the chart. The table to the right shows the following. See also Customize anomaly detection for individual metrics.

Note

Moogsoft Cloud stores all timestamps in UTC format. The dates and times displayed in the UI are based on your browser's local time.

Field

Description

Time

The local time when the data point was captured.

Severity

Severity, if the data point is an anomaly.

Confidence

The level of confidence that the data point is an anomaly, from 0 (low confidence) to 1 (high confidence).  A low confidence value might indicate a relatively small sample size. It might also indicate that the data distribution is less normalized and more scattered, with more variations from the statistical average that represents "normal" behavior for that metric.

High Threshold

The high threshold for normal performance at the time the data point was captured.

Low Threshold

The low threshold for normal performance at the time the data point was captured.

Median

The median value in effect when the data point was captured.

Detector

The anomaly detector in use when the data point was captured.

Deviations

The number of standard deviations above or below the mean at which the detector determines that a data point is an anomaly.

Vector

The detector considers anomalies based on whether a data point is

  • Above threshold (too high) only

  • Below threshold (too low) only

  • Above or below threshold (too high or too low)

Hold For

The detector setting in effect when the data point was captured. You can configure this setting when you set up the detector.

Hold For specifies the number of anomalous data points to observe before generating an anomaly event. For example: if Hold For = 1 when a metric generates an anomalous data point, the detector waits for one more anomalous data point before it generates an event.

Stateful

The detector setting in effect when the data point was captured. You can configure this setting when you set up the detector.

When Stateful is True, generate an anomaly only when the metric changes state: when it enters an anomalous state, when its value changes significantly while in an anomalous state, or when it returns to a normal state. When False, generate an anomaly for every anomalous data point.

Window

The detector setting in effect when the data point was captured. You can configure this setting when you set up the detector.

Window specifies the number of data points sent to Moogsoft Cloud and displayed before and after each anomaly.