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138 lines
5.4 KiB
Markdown
138 lines
5.4 KiB
Markdown
# Introduction
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Prometheus is in the business of doing several things:
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* exposing metrics,
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* collecting metrics,
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* performing computational rules upon them and generating synthetic series,
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* triggering events based upon rule conditions, and
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* metric series archival and deletion.
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The focus of this guide is oriented exclusively toward exposing metrics with
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an eye toward computational rules and event handling in the Prometheus core.
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After reading this guide, you will understand the following:
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* what types of Prometheus metrics are available and how they work,
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* how you should embed these metrics in your applications,
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* what metadata you attach to them, and
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* what to instrument.
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# Metric Types
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Prometheus offers three core metric types:
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* counters,
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* gauges, and
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* summaries.
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Each is tailored toward a different purpose, so it is important to use the
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right one for the right job.
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## Counter
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A _Counter_ tracks addition or subtraction of values from itself. It is used
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to represent state that you control and is not external.
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The following are good examples or applications of counters:
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* pedometers: devices that track the number of steps you take,
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* tickers: devices that measure the number of times an event has occurred,
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* censuses: processes to count to number of individuals of a population, and
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* _your_ bank account ledger: the sum of all transactions conducted on your
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liquid assets.
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The key thing to note about _Counters_ is that they are best used when you are
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directly receiving the events that mutate their values and mutating the
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underlying values that represent their individual state.
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A good example is of an elevator that tracks how many times it has been used in
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its duty cycle. Each time someone hits the button to dispatch it, the elevator
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can update its tally; and this is a tally it keeps!
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See also the [counter Javadoc](https://github.com/prometheus/client_java/blob/master/client/src/main/java/io/prometheus/client/metrics/Counter.java)
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in Prometheus' Java client library for further documentation and concrete code
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examples.
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## Gauges
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A _Gauge_ reports instantaneous values based on external state. This is
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primarily state that you do not control directly but rather that you depend on
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or can inspect.
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The following are good examples or applications of gauges:
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* thermometer,
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* barometer,
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* altimeter, and
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* total system resource utilization.
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Unlike a _Counter_, you don't have direct access to the events that brought the
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_Gauge_ to its value today. This is a white-box and black-box distinction.
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See also the [gauge Javadoc](https://github.com/prometheus/client_java/blob/master/client/src/main/java/io/prometheus/client/metrics/Gauge.java)
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in Prometheus' Java client library for further documentation and concrete code
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examples.
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## Which to use: Counter or Gauge?
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Knowing whether to use a _Counter_ or a _Gauge_ can be tough. Let's perform a
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practical thought exercise. Below is an image of an automobile's instrument
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dashboard:
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What do you see in this photo? Take a minute to make a list. (Don't worry;
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I'll wait for you.)
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From left to right and top to bottom, there are the following instruments:
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* Tachometer: it measures the revolutions per minute of the engine;
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* Clock: it measures the time;
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* Thermometer: it measures the temperature outside the vehicle;
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* Odometer: they measure the total miles the vehicle has traveled as well as
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how far it has traveled on its last trip;
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* Fuel Gauge: it measures how much fuel is in the tank;
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* Speedometer: it measures how fast we are going.
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Great! Look at this list and now think about the definitions above for
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_Counter_ and _Gauge_. Can you identify what instruments are what? (Again,
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I'll wait for you.)
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* Tachometer: Counter. Tricky. The vehicle's sensors observe how quickly
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the flywheel rotates and update the instrument's value on frequent
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intervals by counting revolutions.
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* Clock: Gauge. It is an external value, and we cannot watch the clock's
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internal events.
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* Thermometer: Gauge. It measures an external value, and there is no way to
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track thermodynamic events that influence the outside temperature.
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* Odometer: Counter. It measures distances by the number of times the
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wheels have turned, which itself is based on an event.
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* Fuel Gauge: Gauge. Who would have guessed? It uses a floating ballast and
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a rheostat and is not event-based.
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* Speedmeter: Counter. Tricky. It measures wheel rotation (events) over
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time.
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## Summaries
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_Summary_ is a unique metric type, and one you have probably not used before.
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It samples events over sliding windows of time and provides instantaneous
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insight into their distributions, frequencies, and sums.
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Practically speaking, a summary collects event values and reports the
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following information:
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* streaming quantile values of the entire observed population,
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* the total sum of all observed values, and
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* the count of events that have been observed.
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This is quite convenient, for if you are interested in tracking latencies of an
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operation in real time, you get three types of information reported for free
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with one metric.
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See also the [summary Javadoc](https://github.com/prometheus/client_java/blob/master/client/src/main/java/io/prometheus/client/metrics/Summary.java)
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in Prometheus' Java client library for further documentation and concrete code
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examples.
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# Acknowledgements
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Robert Bray: Vehicle Instrument Panel
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