182 lines
8.2 KiB
Go
182 lines
8.2 KiB
Go
// Copyright 2014 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// Package prometheus provides metrics primitives to instrument code for
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// monitoring. It also offers a registry for metrics. Sub-packages allow to
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// expose the registered metrics via HTTP (package promhttp) or push them to a
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// Pushgateway (package push).
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//
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// All exported functions and methods are safe to be used concurrently unless
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//specified otherwise.
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//
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// A Basic Example
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//
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// As a starting point, a very basic usage example:
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//
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// package main
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//
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// import (
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// "net/http"
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//
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// "github.com/prometheus/client_golang/prometheus"
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// "github.com/prometheus/client_golang/prometheus/promhttp"
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// )
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//
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// var (
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// cpuTemp = prometheus.NewGauge(prometheus.GaugeOpts{
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// Name: "cpu_temperature_celsius",
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// Help: "Current temperature of the CPU.",
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// })
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// hdFailures = prometheus.NewCounterVec(
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// prometheus.CounterOpts{
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// Name: "hd_errors_total",
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// Help: "Number of hard-disk errors.",
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// },
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// []string{"device"},
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// )
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// )
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//
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// func init() {
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// // Metrics have to be registered to be exposed:
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// prometheus.MustRegister(cpuTemp)
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// prometheus.MustRegister(hdFailures)
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// }
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//
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// func main() {
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// cpuTemp.Set(65.3)
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// hdFailures.With(prometheus.Labels{"device":"/dev/sda"}).Inc()
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//
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// // The Handler function provides a default handler to expose metrics
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// // via an HTTP server. "/metrics" is the usual endpoint for that.
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// http.Handle("/metrics", promhttp.Handler())
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// http.ListenAndServe(":8080", nil)
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// }
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//
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//
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// This is a complete program that exports two metrics, a Gauge and a Counter,
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// the latter with a label attached to turn it into a (one-dimensional) vector.
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//
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// Metrics
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//
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// The number of exported identifiers in this package might appear a bit
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// overwhelming. Hovever, in addition to the basic plumbing shown in the example
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// above, you only need to understand the different metric types and their
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// vector versions for basic usage.
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//
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// Above, you have already touched the Counter and the Gauge. There are two more
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// advanced metric types: the Summary and Histogram. A more thorough description
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// of those four metric types can be found in the Prometheus docs:
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// https://prometheus.io/docs/concepts/metric_types/
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//
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// A fifth "type" of metric is Untyped. It behaves like a Gauge, but signals the
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// Prometheus server not to assume anything about its type.
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//
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// In addition to the fundamental metric types Gauge, Counter, Summary,
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// Histogram, and Untyped, a very important part of the Prometheus data model is
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// the partitioning of samples along dimensions called labels, which results in
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// metric vectors. The fundamental types are GaugeVec, CounterVec, SummaryVec,
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// HistogramVec, and UntypedVec.
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//
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// While only the fundamental metric types implement the Metric interface, both
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// the metrics and their vector versions implement the Collector interface. A
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// Collector manages the collection of a number of Metrics, but for convenience,
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// a Metric can also “collect itself”. Note that Gauge, Counter, Summary,
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// Histogram, and Untyped are interfaces themselves while GaugeVec, CounterVec,
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// SummaryVec, HistogramVec, and UntypedVec are not.
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//
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// To create instances of Metrics and their vector versions, you need a suitable
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// …Opts struct, i.e. GaugeOpts, CounterOpts, SummaryOpts,
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// HistogramOpts, or UntypedOpts.
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//
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// Custom Collectors and constant Metrics
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//
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// While you could create your own implementations of Metric, most likely you
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// will only ever implement the Collector interface on your own. At a first
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// glance, a custom Collector seems handy to bundle Metrics for common
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// registration (with the prime example of the different metric vectors above,
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// which bundle all the metrics of the same name but with different labels).
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//
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// There is a more involved use case, too: If you already have metrics
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// available, created outside of the Prometheus context, you don't need the
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// interface of the various Metric types. You essentially want to mirror the
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// existing numbers into Prometheus Metrics during collection. An own
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// implementation of the Collector interface is perfect for that. You can create
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// Metric instances “on the fly” using NewConstMetric, NewConstHistogram, and
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// NewConstSummary (and their respective Must… versions). That will happen in
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// the Collect method. The Describe method has to return separate Desc
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// instances, representative of the “throw-away” metrics to be created
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// later. NewDesc comes in handy to create those Desc instances.
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//
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// The Collector example illustrates the use case. You can also look at the
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// source code of the processCollector (mirroring process metrics), the
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// goCollector (mirroring Go metrics), or the expvarCollector (mirroring expvar
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// metrics) as examples that are used in this package itself.
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//
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// If you just need to call a function to get a single float value to collect as
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// a metric, GaugeFunc, CounterFunc, or UntypedFunc might be interesting
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// shortcuts.
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//
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// Advanced Uses of the Registry
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//
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// While MustRegister is the by far most common way of registering a Collector,
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// sometimes you might want to handle the errors the registration might
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// cause. As suggested by the name, MustRegister panics if an error occurs. With
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// the Register function, the error is returned and can be handled.
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//
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// An error is returned if the registered Collector is incompatible or
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// inconsistent with already registered metrics. The registry aims for
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// consistency of the collected metrics according to the Prometheus data
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// model. Inconsistencies are ideally detected at registration time, not at
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// collect time. The former will usually be detected at start-up time of a
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// program, while the latter will only happen at scrape time, possibly not even
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// on the first scrape if the inconsistency only becomes relevant later. That is
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// the main reason why a Collector and a Metric have to describe themselves to
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// the registry.
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//
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// So far, everything we did operated on the so-called default registry, as it
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// can be found in the global DefaultRegistry variable. With NewRegistry, you
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// can create a custom registry, or you can even implement the Registerer or
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// Gatherer interfaces yourself. The methods Register and Unregister work in
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// the same way on a custom registry as the global functions Register and
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// Unregister on the default registry.
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//
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// There are a number of uses for custom registries: You can use registries
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// with special properties, see NewPedanticRegistry. You can avoid global state,
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// as it is imposed by the DefaultRegistry. You can use multiple registries at
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// the same time to expose different metrics in different ways. You can use
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// separate registries for testing purposes.
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//
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// Also note that the DefaultRegistry comes registered with a Collector for Go
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// runtime metrics (via NewGoCollector) and a Collector for process metrics (via
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// NewProcessCollector). With a custom registry, you are in control and decide
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// yourself about the Collectors to register.
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//
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// HTTP Exposition
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//
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// The Registry implements the Gatherer interface. The caller of the Gather
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// method can then expose the gathered metrics in some way. Usually, the metrics
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// are served via HTTP on the /metrics endpoint. That's happening in the example
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// above. The tools to expose metrics via HTTP are in the promhttp
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// sub-package. (The top-level functions in the prometheus package are
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// deprecated.)
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//
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// Pushing to the Pushgateway
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//
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// Function for pushing to the Pushgateway can be found in the push sub-package.
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//
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// Other Means of Exposition
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//
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// More ways of exposing metrics can easily be added. Sending metrics to
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// Graphite would be an example that will soon be implemented.
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package prometheus
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