Multi-metric gauge chart

Create a multi-metric gauge chart to display a ratio of the good state and the bad state of devices, users, or events.

Data shape

<kpi for good state>, <kpi for bad state>

NQL structure

Refer to the Live Dashboards NQL examples documentation for query examples of multiple-metric gauge widgets.

The NQL structure depends on the variable state comparison you set for the multi-metric gauge—good values versus bad values.

For example, the NQL structure below returns the ratio of devices or users with bad events against objects without bad events.

<devices|users>
| include <event table>
| compute temp_bad_number = <device|user>.count()
| summarize 
   <good_label> = count() - temp_bad_number.sum(), 
   <bad_label> = temp_bad_number.sum()

The image below displays a gauge using the NQL structure referenced above. The legend labels for good and bad values, come from their corresponding variable names in the NQL query.

The variable names are formatted with the following heuristic:

Underscores are replaced with spaces.
The first character of the variable is changed to upper-case.

Configuring visualization fields specific to multi-metric gauges

Refer to the Managing Live Dashboards documentation to learn how to fill in the remaining configuration fields that are not specific to this widget.

After selecting the Multi metric gauge chart option from the Chart type dropdown in the Add widget/Edit a widget pop-up:

Use the Label (optional) field to create the visible name of the main gauge.
- The text can contain special characters. There is a 50-character limit on the Label field.
- See the image in the NQL structure to understand how to define the legend labels for the good and bad values in the query.
Enter a Widget description (optional) to explain, for example, how the metric should be interpreted, calculated, or any subtleties to the metric.
- The widget description appears by hovering over the info icon next to the multi-metric gauge widget in the dashboard.

RELATED TOPIC

Last updated 1 month ago

NQL structure

Refer to the Live Dashboards NQL examples documentation for query examples of multiple-metric gauge widgets.

The NQL structure depends on the variable state comparison you set for the multi-metric gauge—good values versus bad values.

For example, the NQL structure below returns the ratio of devices or users with bad events against objects without bad events.

<devices|users>
| include <event table>
| compute temp_bad_number = <device|user>.count()
| summarize 
   <good_label> = count() - temp_bad_number.sum(), 
   <bad_label> = temp_bad_number.sum()

The image below displays a gauge using the NQL structure referenced above. The legend labels for good and bad values, come from their corresponding variable names in the NQL query.

The variable names are formatted with the following heuristic:

Underscores are replaced with spaces.

The first character of the variable is changed to upper-case.

Configuring visualization fields specific to multi-metric gauges

Refer to the Managing Live Dashboards documentation to learn how to fill in the remaining configuration fields that are not specific to this widget.

After selecting the Multi metric gauge chart option from the Chart type dropdown in the Add widget/Edit a widget pop-up:

Use the Label (optional) field to create the visible name of the main gauge.

The text can contain special characters. There is a 50-character limit on the Label field.
See the image in the NQL structure to understand how to define the legend labels for the good and bad values in the query.

Enter a Widget description (optional) to explain, for example, how the metric should be interpreted, calculated, or any subtleties to the metric.

The widget description appears by hovering over the info icon next to the multi-metric gauge widget in the dashboard.