Rate

Docs > Dashboards > Functions > Rate

Per second

Function	Description	Example
`per_second()`	Graph the rate at which the metric is changing per second.	`per_second(<METRIC_NAME>{*})`

Per minute

Function	Description	Example
`per_minute()`	Graph the rate at which the metric is changing per minute.	`per_minute(<METRIC_NAME>{*})`

Per hour

Function	Description	Example
`per_hour()`	Graph the rate at which the metric is changing per hour.	`per_hour(<METRIC_NAME>{*})`

Time difference

Function	Description	Example
`dt()`	Graph the time difference in seconds between submitted points.	`dt(<METRIC_NAME>{*})`

The dt() function returns only one timeseries regardless of how many groups are involved. Within that one timeseries, it considers the time difference of all the submitted points across the various groups.

Value difference

Function	Description	Example
`diff()`	Graph the delta of the metric.	`diff(<METRIC_NAME>{*})`

Calculates the difference between each interval on a per interval basis. For example, a metric submits data points with a 15 second interval, the diff() modifier would show it over 15 second rate. Note: The calculation is done after applying time aggregation and before space aggregation takes place.

Monotonic difference

Function	Description	Example
`monotonic_diff()`	Graph the delta of the metric like `diff()` but only if the delta is positive.	`monotonic_diff(<METRIC_NAME>{*})`

Derivative

Function	Description	Example
`derivative()`	Graph the derivative (diff/dt) of the metric.	`derivative(<METRIC_NAME>{*})`

Throughput

Function	Description	Example
`throughput()`	Converts a timeseries into a rate per second, by dividing each value by the number of seconds in the time bucket to produce the per-second value.	`throughput(<METRIC_NAME>{*})`

Other functions

Consult the other available functions:

Algorithmic: Implement Anomaly or Outlier detection on your metric.

Arithmetic: Perform Arithmetic operation on your metric.

Count: Count non zero or non null value of your metric.

Exclusion: Exclude certain values of your metric.

Interpolation: Fill or set default values for your metric.

Rank: Select only a subset of metrics.

Regression: Apply some machine learning function to your metric.

Rollup: Control the number of raw points used in your metric.

Smoothing: Smooth your metric variations.

Timeshift: Shift your metric data point along the timeline.

Further Reading

Additional helpful documentation, links, and articles:

Alert on no change in valueDOCUMENTATION