Functions for metrics

Kloudfuse has a large number of functions for examining the metric data types of counter, gauge, and histogram.

Algorithms

Anomalies

Overlay a band on the metric, showing the expected behavior of a series based on past values.

Outliers

Highlight outliers series.

Forecast

Forecast future values based on past values.

Aggregation

Average

Average value for a specific metric across aggregated or grouped data points.

Minimum

Smallest or lowest value observed among the aggregated data points.

Maximum

Largest or highest value observed among the aggregated data points.

Sum

Sum of values observed among the aggregated data points.

Count

Count of values observed among the aggregated data points.

Standard variance

Standard variance of values observed among the aggregated data points.

Standard deviation

Standard deviation of values observed among the aggregated data points.

Quantile

Specific value or point in a dataset that divides the data into ordered subsets with equal probabilities.

Arithmetic

Absolute value

Absolute value of the metric.

Exponential

Calculates the exponential function for all elements of the time series.

Floor

Rounds down the sample values of all elements in the time series to the nearest integer.

Histogram quantile

Calculates the φ-quantile (0 ≤ φ ≤ 1) from the buckets of the histogram.

Log 2

Calculates Log 2, the binary logarithm, of the metric; log2.

Log 10

Calculates Log 10, decimal or common logarithm, of the metric; log10.

Scalar

Determines the sample value of a single-element input time series v, scalar(v instant-vector), and converts it to a scalar value.,

ln

Calculates the natural logarithm, of all values in a time series; loge.

Round

Rounds the sample values of all elements in the time series to the nearest integer.

SGN

Returns a vector with all sample values in the time series converted to their sign, + or -.

Square root

Calculates the square root of all values in the time series, \$\sqrt(value)\$.

Ceil

Rounds up the sample values of all elements in the time series to the nearest integer.

Timestamp

Returns the timestamp of each value in the time series in epoch format, or the number of seconds after January 1, 1970 UTC.

Count

Count non zero

Computes the count of all non-zero values.

Count not null

Computes the count of all non-null values.

Absent

Returns an empty vector if the time series has any elements, or a 1-element vector with value 1 if the time series has no elements.

Absent over time

Returns an empty vector if the range time series has any elements, or a 1-element vector with value 1 if the range time series has no elements.

Changes

Returns the count of instances when the time series value changed within the specified time range, as an instant vector.

Resets

Returns the number of counter resets, resets(v range-vector), within the specified time range, for each input time series, as an instant vector.

Time

Day of week

Returns the day of the week for each element in the time series, in UTC. Valid values range from 0 to 6, where 0 is Sunday, 1 is Monday, and so on.

Day of month

Returns the day of the month for each element in the time series, in UTC. Valid values range from 1 to 31.

Day of year

Returns the day of the year for each element in the time series, in UTC. Valid values range from 1 to 365 for non-leap years, and from 1 to 366 for leap years.

Days in month

Returns the number of days in the month for element in the time series, in UTC. Valid values range from 28 to 31.

Hour

Returns the hour of the day for each element in the time series, in UTC. Valid values range from 0 to 23.

Minute

Returns the minute of the hour for each element of the times series, in UTC. Valid values range from 0 to 59.

Month

Returns the month of the year for each element of the time series, in UTC. Valid values range from 1 to 12.

Year

Returns the year for each element of the time series, in UTC.

Rate

Diff

Graphs the delta of the metric, \$Delta\$.

Derivative

Graphs the time derivative of the metric, \$\frac{Delta}{dt}\$.

Monotonic diff

Graphs the delta (\$Delta\$) of the metric, but only if it is positive.

Irate

Calculates the per-second instant rate of increase of the time series in the range vector, based on the last two data points. Automatically adjusts for breaks in monotonicity, like counter resets due to target restarts.

Per hour

Graphs the rate of metric change per hour.

Per minute

Graphs the rate of metric change per minute.

Per second

Graphs the rate of metric change per second.

Increase

Calculates the increase in the time series across the range vector.

Exclusion

Clamp max

Lowers all metric values greater than the threshold to that threshold value.

Clamp min

Raises all metric values lower than the threshold to that threshold value.

Cutoff max

Removes all metric values greater than the threshold value.

Cutoff min

Removes all metric values less than the threshold value.

Clamp

Clamps the values of all elements in the time series to min and max. This lowers values greater than and max to and max, and raises values lower than and min to and min.

Rank

Top K

Graphs the top K elements.

Sort

Sorts the time series by sample value, in ascending order.

Sort desc

Sorts the time series by sample value, in descending order.

Rollup

Average over time

Calculates the average value of all points in the specified interval.

Min over time

Calculates the minimum value of all points in the specified interval.

Max over time

Calculates the maximum value of all points in the specified interval.

Sum over time

Calculates the sum of all values in the specified interval.

Count over time

Counts of all values in the specified interval.

Quantile over time

Calculates the φ-quantile (0 ≤ φ ≤ 1) of values in the specified interval.

Deviation over time

Calculates the population standard deviation of values in the specified interval.

Variance over time

Calculates the variance of values in the specified interval.

Last over time

Returns the most recent point value in the specified interval.

Regression

Predict linear

Predicts the value of time series t seconds from now using simple linear regression.

Smoothing

Holt Winters

Produces a smoothed value for time series based on the range in the time series, accounting for seasonal adjustments. Implements the Holt-Winters method of exponentially-weighted averages as smoothing factors.

Trigonometric

Acos

Calculates the arccosine of all elements in the time series.

Acosh

Calculates the inverse hyperbolic cosine of all elements in the time series.

Asin

Calculates the arcsine of all elements in the time series.

Asinh

Calculates the inverse hyperbolic sine of all elements in the time series.

Atan

Calculates the arctangent of all elements in the time series.

Atanh

Calculates the inverse hyperbolic tangent of all elements in the time series.

Cos

Calculates the cosine of all elements in the time series.

Cosh

Calculates the hyperbolic cosine of all elements in the time series.

Sin

Calculates the sine of all elements in the time series.

Sinh

Calculates the hyperbolic sine of all elements in the time series.

Tan

Calculates the tangent of all elements in the time series.

Tanh

Calculates the hyperbolic tangent of all elements in the time series.