Create and Manage Variables

Overview

A variable is like a placeholder for a value used in queries. Once set up in Custom Dashboards, your dashboard panel's queries will update to show data for that value.

Variables make dashboards more interactive and dynamic. Instead of putting specific names for servers, applications, or sensors in your queries, you can use variables instead. Once set up, you can easily switch between different data views. This means that if you have very complex, high-cardinality metrics, you can add variables to zoom in on specific values you care about, across widgets for all data types and regardless of the variable source type.

Variable types

Choose from any of the following variable types:

Variable type	Description
Static-value variable	Manually define a fixed list of variable values, such as a number or a string of numbers separated by a comma. For example, if you have country names that never change, you might want to create them as a static-value variable rather than a data source variable.
Query variable	Variable values are retrieved from a data source query using logs, metrics, or spans. For example, a query variable can generate a list of server names, sensor IDs, or data centers, dynamically updating the values by fetching options via a data source query. Query variables prove beneficial when managing multiple data source instances, especially across diverse environments.

Getting started

Navigate to Dashboards > Custom Dashboards.

In a new or existing dashboard, click the Manage Variable icon { } in the upper left-hand corner of your dashboard. Then click + Variable.

General options

Define the following fields for all variable types:

Variable type

Select a variable type.

Variable name

Text entered in this field determines how the variable name will appear in your query, e.g, {{ podvalues }}. No capitals or spaces are allowed.

Display name

[Optional] Text entered in this field will appear in the top bar selection as part of the drop-down, e.g., "My Pods".

Selection options

Once you have defined your variable, you may choose from these selection options:

• Multi-value: Allows multiple selection of values within a specific variable. Note that some queries do not support multiple values, such as {{ variablename }}. Choose this option only if your query supports multiple values.

• Include all: You may enable this option when the multi-value option is enabled. The query will select all available and future values for a specific timeframe, regardless of your specific selection.

When both options are selected, all variable options are selected by default, and one or more may be deselected. Opting out of both options will allow you to select one variable value at a time.

Create a static-value variable

Create a logs-based query variable

Create a spans-based query variable

Create a metrics-based query variable

Metric names

Metric labels

Metric label values

Manage variables

Easily view and manage the variables from the Custom Dashboards upper toolbar.

Edit or delete

To edit or delete a variable:

Reorder variables

Variables support drag-and-drop reordering, allowing you to organize them in a logical and meaningful order-especially helpful after adding new variables.

To reorder one or more variables:

Query with template variables

You can use template variables in Lucene, PromQL, or DataPrime queries to build reusable dashboards. This eliminates the need to input the same data points into each widget, and instead allows you to filter all the widgets on your dashboard simultaneously with one variable.

To edit the query, select the widget and navigate to the query builder at the bottom of the screen.

Lucene

In a Lucene query, a template variable is referenced with {{ variable_name }} syntax.

Example:

 product_id:{{ pid }} 

In this example, the pid is the variable name, which must match the name you defined in the dashboard.

PromQL

In a PromQL query, a template variable is referenced with ${variable_name} syntax.

Example:

sum(kube_pod_owner{pod=~${pod}})

In this example, {pod=~${pod}} is a label selector that filters the kube_pod_owner metric for the specific pod whose name matches the name selected in the ${pod} template variable. The ${pod} is dynamically replaced with the selected pod when the query runs.

DataPrime

In a DataPrime query, a template variable is accessed with $p.<variable_name> syntax.

Example:

source logs 
| filter $l.applicationname.inArray($p.application) 
| groupby $l.applicationname as Application
, $m.timestamp / 10m as timestamp agg count() as count

In this example, the DataPrime query groups log activity into 10 minute intervals and filters them by the selected application dashboard variable, using a parameter that dynamically updates based on the variable you select. This allows you to compare log volume across one or more applications.

Learn more about query parameters.

Global variables

Coralogix provides predefined, system-managed variables that automatically adapt to the scope of your dashboard context. These variables can be included directly in your widget queries and update dynamically when the global dashboard context changes, such as when you adjust the dashboard time range using the time picker.

PromQL predefined variables

Use these variables in metrics-based widgets.

Variable	Description	Example
${__range}	This variable represents the duration of the dashboard time range. It is rendered as an interval string supported by PromQL. e.g., If one selects a time range from 13.00 to 14.30, then ${__range} will be rendered as 90m.	30m, 1d
${__range_s}	Rendered as the number of seconds in the selected time frame.	60s, 180s
${__range_ms}	Rendered as the number of milliseconds in the selected time frame.	60ms, 180ms
${__interval}	A dynamic interval based on the selected time range. Used to group time series data efficiently in visualizations. Behavior depends on the widget type. In widgets that support time bucket configuration (such as line charts and vertical bar charts by time), the ${__interval} variable resolves to the value set in the widget's configuration. In other widgets, it defaults to the selected time range divided by 96.	5m, 1h, 1d
${__interval_s}	The ${__interval} value in seconds, rendered as a number. Useful for functions that require interval math in seconds.	60s, 1200s
${__interval_ms}	The ${__interval} value expressed in milliseconds as a number. Useful for calculations or functions requiring millisecond precision.	60000ms, 1200000ms
${__rate_interval}	A dynamic range for PromQL rate() queries. It resolves to the larger of ${__interval} + 15s or 60s, ensuring both adequate overlap and enough data points for accurate calculations.	60s, 2m
${__rate_interval_s}	The ${__rate_interval} value in seconds, rendered as a number.	60s, 120s
${__rate_interval_ms}	The ${__rate_interval} value expressed in milliseconds as a number. Enables precise math and comparisons.	6000000ms, 1200000ms

Example:

avg_over_time(k8s_node_cpu_time_total[${__range}])

This query calculates the average CPU time accumulated across all nodes over the time range selected in the dashboard. The ${__range} variable dynamically reflects the current time picker selection, so the aggregation always matches the visible timeframe.

DataPrime predefined variables

Take advantage of predefined global dashboard variables in your widgets querying with DataPrime.

Variable	Description	Example
$p.timeRange.startTime	The start of the dashboard time range, based on the current time picker setting. Use this to align query results with the visible time scope.	1d, 5m, 60s
$p.timeRange.endTime	The end of the dashboard time range, based on the current time picker setting. Use this to align query results with the visible time scope.	1d, 5m, 60s
$p.timeRange.suggestedInterval	The suggested interval variable allows you to include queries that automatically adjust the widget's query and visualization according to the current dashboard time range by dividing it into 96 uniform time buckets. This ensures the query and visualization remain appropriately scaled as users change the time picker.	1d, 5m, 60s

Example:

source logs | groupby $m.timestamp / $p.timeRange.suggestedInterval 
as timestamp agg count() as count

This example dynamically groups log data by time without hardcoding an interval, ensuring the widget adapts gracefully across different time ranges. Use $p.timeRange.suggestedInterval instead of manually selected a time interval, which can result in charts that are too broad or too granular when the time range is adjusted.

Additional resources

8.11 Coralogix Academy - Custom Dashboard Variables

Custom Dashboard Variables