Metrics (Statistical Collector / Performance data)

This page is about metrics in Monitoring.

A monitoring/performance metrics is a:

• timestamped
• numerical value

Monitoring Metrics are also known as:

• Statistical Collector
• Perfcounter (generally on Windows)
• Performance metrics
• Performance data

They are known as statistical data collectors because they gather data and compute statistics. They are used to collect, evaluate and report results, e.g.

• mean residence times of customers
• or the average utilisation of a server.

An aggregated metrics is

• calculated from time serie data.
• a statistic(s) (See also the page Counter - Statistics (for Engineers on operational data))

They are event metrics.

• Timer, a Timer measures both the count of timed events and the total time of all events timed.
• Counter is used to record occurrences of events like the number of customer arrivals. Representing a counter without rate aggregation over some time window is rarely useful, as the representation is a function of both the rapidity with which the counter is incremented and the longevity of the service.
• Gauge, - a single metric (gauge values are not rates)
• Distribution
• histogram - An histogram ranks the measured values into predefined classes.
• Regressions: A Regression perform a regressional analysis of two different collected value series (x and y). It reports the number of observations, mean (for x and y), regression and correlation coefficients, standard deviations and interception.

Time serie:

• Tallies. A tally record the mean and standard deviation of a (time) series of values. Example: Computing the average time customers spent on a system
• Accumulates: An Accumulate record the mean and standard deviation of a time series of values against different time interval. Example: System load

See also: Prometheus Metrics Type

• Statistical Data Collectors (desmoj.core.statistic package)