Metric types

    A counter is a cumulative metric that represents a single monotonically increasing counter whose value can only increase or be reset to zero on restart. For example, you can use a counter to represent the number of requests served, tasks completed, or errors.

    Do not use a counter to expose a value that can decrease. For example, do not use a counter for the number of currently running processes; instead use a gauge.

    Client library usage documentation for counters:

    A gauge is a metric that represents a single numerical value that can arbitrarily go up and down.

    Client library usage documentation for gauges:

    A histogram samples observations (usually things like request durations or response sizes) and counts them in configurable buckets. It also provides a sum of all observed values.

    A histogram with a base metric name of exposes multiple time series during a scrape:

    • cumulative counters for the observation buckets, exposed as <basename>_bucket{le="<upper inclusive bound>"}
    • the total sum of all observed values, exposed as <basename>_sum
    • the count of events that have been observed, exposed as (identical to <basename>_bucket{le="+Inf"} above)

    Use the histogram_quantile() function to calculate quantiles from histograms or even aggregations of histograms. A histogram is also suitable to calculate an . When operating on buckets, remember that the histogram is cumulative. See for details of histogram usage and differences to summaries.

    Similar to a histogram, a summary samples 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 quantiles over a sliding time window.

    A summary with a base metric name of exposes multiple time series during a scrape:

    • streaming φ-quantiles (0 ≤ φ ≤ 1) of observed events, exposed as <basename>{quantile="<φ>"}
    • the total sum of all observed values, exposed as <basename>_sum
    • the count of events that have been observed, exposed as

    See histograms and summaries for detailed explanations of φ-quantiles, summary usage, and differences to .

    Client library usage documentation for summaries: