Package version
Distribution cumulative measurement. The count and sum cannot decrease, if resets then the start_time should also be reset.
Floating point cumulative measurement. The value cannot decrease, if resets then the start_time should also be reset. Recorded values are always >= 0.
Integer cumulative measurement. The value cannot decrease, if resets then the start_time should also be reset.
Distribution gauge measurement. The count and sum can go both up and down. Recorded values are always >= 0. Used in scenarios like a snapshot of time the current items in a queue have spent there.
Floating point gauge. The value can go both up and down.
Integer gauge. The value can go both up and down.
Some frameworks implemented Histograms as a summary of observations (usually things like request durations and response sizes). While it also provides a total count of observations and a sum of all observed values, it calculates configurable percentiles over a sliding time window. This is not recommended, since it cannot be aggregated.
Do not use this default value.
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The kind of metric. It describes how the data is reported.
A gauge is an instantaneous measurement of a value.
A cumulative measurement is a value accumulated over a time interval. In a time series, cumulative measurements should have the same start time, increasing values and increasing end times, until an event resets the cumulative value to zero and sets a new start time for the following points.