Metric data point reference
Use metric charts to view information about metric data at specific points in time. The following tables show the information that you can view.
Metric chart information
The information in this table appears to the right of the chart for any data point you hover over.
Field | Description |
|---|---|
Time | The local time when the data point was captured. |
Severity | Severity, if the data point is an anomaly. |
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. |
Metric Policy | The policy which evaluated the metric when the data point was captured. |
Raw Datum information
To view detailed information about a specific data point in the chart, click the graphed line.
The Raw Datum dialog appears. It includes information about the source and tags, which can vary depending on the metric. It also includes an "engine" section which displays values for the following:
Field | Description |
|---|---|
highThreshold | The high threshold for normal performance at the time the data point was captured. |
lowThreshold | The low threshold for normal performance at the time the data point was captured. |
vector | The detector considers anomalies based on whether a data point is
|
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. |
DETECTOR_CLASS | This value may be either CThresholdDetector (threshold detector) or CAdaptiveDetector (adaptive detector). |
holdfor | The Hold For 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. |
Note
Moogsoft Cloud discards duplicate metrics which contain identical values and arrive in the same batch. Moogsoft adds the time to metrics without timestamps, but because this process happens quickly, metrics in the same batch are often stamped with the same time.
Metrics are considered duplicates when they contain the same values for:
timestamp
fqm
source
key
name
When multiple identical metrics exist, only the first metric is accepted and the rest are discarded. To avoid this scenario, you can either modify the metric data so that it it is sent with unique timestamps, or add differentiating values to the fqm, source, key, or name fields.