prometheus

package
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 Go to latest Published: Dec 18, 2023 License: LGPL-3.0 Imports: 27 Imported by: 0

README

See go-doc.

Documentation

Overview

Package prometheus provides metrics primitives to instrument code for monitoring. It also offers a registry for metrics. Sub-packages allow to expose the registered metrics via HTTP (package promhttp) or push them to a Pushgateway (package push).

All exported functions and methods are safe to be used concurrently unless specified otherwise.

A Basic Example

As a starting point, a very basic usage example: 

package main

import (
	"log"
	"net/http"

	"github.com/prometheus/client_golang/prometheus"
	"github.com/prometheus/client_golang/prometheus/promhttp"
)

var (
	cpuTemp = prometheus.NewGauge(prometheus.GaugeOpts{
		Name: "cpu_temperature_celsius",
		Help: "Current temperature of the CPU.",
	})
	hdFailures = prometheus.NewCounterVec(
		prometheus.CounterOpts{
			Name: "hd_errors_total",
			Help: "Number of hard-disk errors.",
		},
		[]string{"device"},
	)
)

func init() {
	// Metrics have to be registered to be exposed:
	prometheus.MustRegister(cpuTemp)
	prometheus.MustRegister(hdFailures)
}

func main() {
	cpuTemp.Set(65.3)
	hdFailures.With(prometheus.Labels{"device":"/dev/sda"}).Inc()

	// The Handler function provides a default handler to expose metrics
	// via an HTTP server. "/metrics" is the usual endpoint for that.
	http.Handle("/metrics", promhttp.Handler())
	log.Fatal(http.ListenAndServe(":8080", nil))
}

This is a complete program that exports two metrics, a Gauge and a Counter, the latter with a label attached to turn it into a (one-dimensional) vector.

Metrics

The number of exported identifiers in this package might appear a bit overwhelming. However, in addition to the basic plumbing shown in the example above, you only need to understand the different metric types and their vector versions for basic usage.

Above, you have already touched the Counter and the Gauge. There are two more advanced metric types: the Summary and Histogram. A more thorough description of those four metric types can be found in the Prometheus docs: https://prometheus.io/docs/concepts/metric_types/

A fifth "type" of metric is Untyped. It behaves like a Gauge, but signals the Prometheus server not to assume anything about its type.

In addition to the fundamental metric types Gauge, Counter, Summary, Histogram, and Untyped, a very important part of the Prometheus data model is the partitioning of samples along dimensions called labels, which results in metric vectors. The fundamental types are GaugeVec, CounterVec, SummaryVec, HistogramVec, and UntypedVec.

While only the fundamental metric types implement the Metric interface, both the metrics and their vector versions implement the Collector interface. A Collector manages the collection of a number of Metrics, but for convenience, a Metric can also “collect itself”. Note that Gauge, Counter, Summary, Histogram, and Untyped are interfaces themselves while GaugeVec, CounterVec, SummaryVec, HistogramVec, and UntypedVec are not.

To create instances of Metrics and their vector versions, you need a suitable …Opts struct, i.e. GaugeOpts, CounterOpts, SummaryOpts, HistogramOpts, or UntypedOpts.

Custom Collectors and constant Metrics

While you could create your own implementations of Metric, most likely you will only ever implement the Collector interface on your own. At a first glance, a custom Collector seems handy to bundle Metrics for common registration (with the prime example of the different metric vectors above, which bundle all the metrics of the same name but with different labels).

There is a more involved use case, too: If you already have metrics available, created outside of the Prometheus context, you don't need the interface of the various Metric types. You essentially want to mirror the existing numbers into Prometheus Metrics during collection. An own implementation of the Collector interface is perfect for that. You can create Metric instances “on the fly” using NewConstMetric, NewConstHistogram, and NewConstSummary (and their respective Must… versions). That will happen in the Collect method. The Describe method has to return separate Desc instances, representative of the “throw-away” metrics to be created later. NewDesc comes in handy to create those Desc instances.

The Collector example illustrates the use case. You can also look at the source code of the processCollector (mirroring process metrics), the goCollector (mirroring Go metrics), or the expvarCollector (mirroring expvar metrics) as examples that are used in this package itself.

If you just need to call a function to get a single float value to collect as a metric, GaugeFunc, CounterFunc, or UntypedFunc might be interesting shortcuts.

Advanced Uses of the Registry

While MustRegister is the by far most common way of registering a Collector, sometimes you might want to handle the errors the registration might cause. As suggested by the name, MustRegister panics if an error occurs. With the Register function, the error is returned and can be handled.

An error is returned if the registered Collector is incompatible or inconsistent with already registered metrics. The registry aims for consistency of the collected metrics according to the Prometheus data model. Inconsistencies are ideally detected at registration time, not at collect time. The former will usually be detected at start-up time of a program, while the latter will only happen at scrape time, possibly not even on the first scrape if the inconsistency only becomes relevant later. That is the main reason why a Collector and a Metric have to describe themselves to the registry.

So far, everything we did operated on the so-called default registry, as it can be found in the global DefaultRegistry variable. With NewRegistry, you can create a custom registry, or you can even implement the Registerer or Gatherer interfaces yourself. The methods Register and Unregister work in the same way on a custom registry as the global functions Register and Unregister on the default registry.

There are a number of uses for custom registries: You can use registries with special properties, see NewPedanticRegistry. You can avoid global state, as it is imposed by the DefaultRegistry. You can use multiple registries at the same time to expose different metrics in different ways. You can use separate registries for testing purposes.

Also note that the DefaultRegistry comes registered with a Collector for Go runtime metrics (via NewGoCollector) and a Collector for process metrics (via NewProcessCollector). With a custom registry, you are in control and decide yourself about the Collectors to register.

HTTP Exposition

The Registry implements the Gatherer interface. The caller of the Gather method can then expose the gathered metrics in some way. Usually, the metrics are served via HTTP on the /metrics endpoint. That's happening in the example above. The tools to expose metrics via HTTP are in the promhttp sub-package. (The top-level functions in the prometheus package are deprecated.)

Pushing to the Pushgateway

Function for pushing to the Pushgateway can be found in the push sub-package.

Graphite Bridge

Functions and examples to push metrics from a Gatherer to Graphite can be found in the graphite sub-package.

Other Means of Exposition

More ways of exposing metrics can easily be added by following the approaches of the existing implementations.

Index

Constants

View Source 
const (
	// DefMaxAge is the default duration for which observations stay
	// relevant.
	DefMaxAge time.Duration = 10 * time.Minute
	// DefAgeBuckets is the default number of buckets used to calculate the
	// age of observations.
	DefAgeBuckets = 5
	// DefBufCap is the standard buffer size for collecting Summary observations.
	DefBufCap = 500
)

Default values for SummaryOpts.

Variables

View Source 
var (
	DefaultRegisterer Registerer = defaultRegistry
	DefaultGatherer   Gatherer   = defaultRegistry
)

DefaultRegisterer and DefaultGatherer are the implementations of the Registerer and Gatherer interface a number of convenience functions in this package act on. Initially, both variables point to the same Registry, which has a process collector (see NewProcessCollector) and a Go collector (see NewGoCollector) already registered. This approach to keep default instances as global state mirrors the approach of other packages in the Go standard library. Note that there are caveats. Change the variables with caution and only if you understand the consequences. Users who want to avoid global state altogether should not use the convenience function and act on custom instances instead.

View Source 
var (
	DefBuckets = []float64{.005, .01, .025, .05, .1, .25, .5, 1, 2.5, 5, 10}
)

DefBuckets are the default Histogram buckets. The default buckets are tailored to broadly measure the response time (in seconds) of a network service. Most likely, however, you will be required to define buckets customized to your use case.

View Source 
var (
	DefObjectives = map[float64]float64{0.5: 0.05, 0.9: 0.01, 0.99: 0.001}
)

DefObjectives are the default Summary quantile values.

Deprecated: DefObjectives will not be used as the default objectives in v0.10 of the library. The default Summary will have no quantiles then.

Functions

func BuildFQName 

func BuildFQName(namespace, subsystem, name string) string

BuildFQName joins the given three name components by "_". Empty name components are ignored. If the name parameter itself is empty, an empty string is returned, no matter what. Metric implementations included in this library use this function internally to generate the fully-qualified metric name from the name component in their Opts. Users of the library will only need this function if they implement their own Metric or instantiate a Desc (with NewDesc) directly.

func ExponentialBuckets 

func ExponentialBuckets(start, factor float64, count int) []float64

ExponentialBuckets creates 'count' buckets, where the lowest bucket has an upper bound of 'start' and each following bucket's upper bound is 'factor' times the previous bucket's upper bound. The final +Inf bucket is not counted and not included in the returned slice. The returned slice is meant to be used for the Buckets field of HistogramOpts.

The function panics if 'count' is 0 or negative, if 'start' is 0 or negative, or if 'factor' is less than or equal 1.

func Handler deprecated 

func Handler() http.Handler

Handler returns an HTTP handler for the DefaultGatherer. It is already instrumented with InstrumentHandler (using "prometheus" as handler name).

Deprecated: Please note the issues described in the doc comment of InstrumentHandler. You might want to consider using promhttp.Handler instead (which is not instrumented, but can be instrumented with the tooling provided in package promhttp).

func InstrumentHandler deprecated 

func InstrumentHandler(handlerName string, handler http.Handler) http.HandlerFunc

InstrumentHandler wraps the given HTTP handler for instrumentation. It registers four metric collectors (if not already done) and reports HTTP metrics to the (newly or already) registered collectors: http_requests_total (CounterVec), http_request_duration_microseconds (Summary), http_request_size_bytes (Summary), http_response_size_bytes (Summary). Each has a constant label named "handler" with the provided handlerName as value. http_requests_total is a metric vector partitioned by HTTP method (label name "method") and HTTP status code (label name "code").

Deprecated: InstrumentHandler has several issues. Use the tooling provided in package promhttp instead. The issues are the following:

- It uses Summaries rather than Histograms. Summaries are not useful if aggregation across multiple instances is required.

- It uses microseconds as unit, which is deprecated and should be replaced by seconds.

- The size of the request is calculated in a separate goroutine. Since this calculator requires access to the request header, it creates a race with any writes to the header performed during request handling. httputil.ReverseProxy is a prominent example for a handler performing such writes.

- It has additional issues with HTTP/2, cf. https://github.com/prometheus/client_golang/issues/272.

func InstrumentHandlerFunc deprecated 

func InstrumentHandlerFunc(handlerName string, handlerFunc func(http.ResponseWriter, *http.Request)) http.HandlerFunc

InstrumentHandlerFunc wraps the given function for instrumentation. It otherwise works in the same way as InstrumentHandler (and shares the same issues).

Deprecated: InstrumentHandlerFunc is deprecated for the same reasons as InstrumentHandler is. Use the tooling provided in package promhttp instead.

func InstrumentHandlerFuncWithOpts deprecated 

func InstrumentHandlerFuncWithOpts(opts SummaryOpts, handlerFunc func(http.ResponseWriter, *http.Request)) http.HandlerFunc

InstrumentHandlerFuncWithOpts works like InstrumentHandlerFunc (and shares the same issues) but provides more flexibility (at the cost of a more complex call syntax). See InstrumentHandlerWithOpts for details how the provided SummaryOpts are used.

Deprecated: InstrumentHandlerFuncWithOpts is deprecated for the same reasons as InstrumentHandler is. Use the tooling provided in package promhttp instead.

func InstrumentHandlerWithOpts deprecated 

func InstrumentHandlerWithOpts(opts SummaryOpts, handler http.Handler) http.HandlerFunc

InstrumentHandlerWithOpts works like InstrumentHandler (and shares the same issues) but provides more flexibility (at the cost of a more complex call syntax). As InstrumentHandler, this function registers four metric collectors, but it uses the provided SummaryOpts to create them. However, the fields "Name" and "Help" in the SummaryOpts are ignored. "Name" is replaced by "requests_total", "request_duration_microseconds", "request_size_bytes", and "response_size_bytes", respectively. "Help" is replaced by an appropriate help string. The names of the variable labels of the http_requests_total CounterVec are "method" (get, post, etc.), and "code" (HTTP status code).

If InstrumentHandlerWithOpts is called as follows, it mimics exactly the behavior of InstrumentHandler: 

prometheus.InstrumentHandlerWithOpts(
    prometheus.SummaryOpts{
         Subsystem:   "http",
         ConstLabels: prometheus.Labels{"handler": handlerName},
    },
    handler,
)

Technical detail: "requests_total" is a CounterVec, not a SummaryVec, so it cannot use SummaryOpts. Instead, a CounterOpts struct is created internally, and all its fields are set to the equally named fields in the provided SummaryOpts.

Deprecated: InstrumentHandlerWithOpts is deprecated for the same reasons as InstrumentHandler is. Use the tooling provided in package promhttp instead.

func LinearBuckets 

func LinearBuckets(start, width float64, count int) []float64

LinearBuckets creates 'count' buckets, each 'width' wide, where the lowest bucket has an upper bound of 'start'. The final +Inf bucket is not counted and not included in the returned slice. The returned slice is meant to be used for the Buckets field of HistogramOpts.

The function panics if 'count' is zero or negative.

func MustRegister 

func MustRegister(cs ...Collector)

MustRegister registers the provided Collectors with the DefaultRegisterer and panics if any error occurs.

MustRegister is a shortcut for DefaultRegisterer.MustRegister(cs...). See there for more details.

func Register 

func Register(c Collector) error

Register registers the provided Collector with the DefaultRegisterer.

Register is a shortcut for DefaultRegisterer.Register(c). See there for more details.

func UninstrumentedHandler deprecated 

func UninstrumentedHandler() http.Handler

UninstrumentedHandler returns an HTTP handler for the DefaultGatherer.

Deprecated: Use promhttp.Handler instead. See there for further documentation.

func Unregister 

func Unregister(c Collector) bool

Unregister removes the registration of the provided Collector from the DefaultRegisterer.

Unregister is a shortcut for DefaultRegisterer.Unregister(c). See there for more details.

Types

type AlreadyRegisteredError 

type AlreadyRegisteredError struct {
	ExistingCollector, NewCollector Collector
}

AlreadyRegisteredError is returned by the Register method if the Collector to be registered has already been registered before, or a different Collector that collects the same metrics has been registered before. Registration fails in that case, but you can detect from the kind of error what has happened. The error contains fields for the existing Collector and the (rejected) new Collector that equals the existing one. This can be used to find out if an equal Collector has been registered before and switch over to using the old one, as demonstrated in the example.

func (AlreadyRegisteredError) Error 

func (err AlreadyRegisteredError) Error() string

type Animate 

type Animate interface {
	SetTimestamp(int64)
	GetTimestamp() int64
}

type Collector 

type Collector interface {
	// Describe sends the super-set of all possible descriptors of metrics
	// collected by this Collector to the provided channel and returns once
	// the last descriptor has been sent. The sent descriptors fulfill the
	// consistency and uniqueness requirements described in the Desc
	// documentation. (It is valid if one and the same Collector sends
	// duplicate descriptors. Those duplicates are simply ignored. However,
	// two different Collectors must not send duplicate descriptors.) This
	// method idempotently sends the same descriptors throughout the
	// lifetime of the Collector. If a Collector encounters an error while
	// executing this method, it must send an invalid descriptor (created
	// with NewInvalidDesc) to signal the error to the registry.
	Describe(chan<- *Desc)
	// Collect is called by the Prometheus registry when collecting
	// metrics. The implementation sends each collected metric via the
	// provided channel and returns once the last metric has been sent. The
	// descriptor of each sent metric is one of those returned by
	// Describe. Returned metrics that share the same descriptor must differ
	// in their variable label values. This method may be called
	// concurrently and must therefore be implemented in a concurrency safe
	// way. Blocking occurs at the expense of total performance of rendering
	// all registered metrics. Ideally, Collector implementations support
	// concurrent readers.
	Collect(chan<- Metric)
}

Collector is the interface implemented by anything that can be used by Prometheus to collect metrics. A Collector has to be registered for collection. See Registerer.Register.

The stock metrics provided by this package (Gauge, Counter, Summary, Histogram, Untyped) are also Collectors (which only ever collect one metric, namely itself). An implementer of Collector may, however, collect multiple metrics in a coordinated fashion and/or create metrics on the fly. Examples for collectors already implemented in this library are the metric vectors (i.e. collection of multiple instances of the same Metric but with different label values) like GaugeVec or SummaryVec, and the ExpvarCollector.

func NewExpvarCollector 

func NewExpvarCollector(exports map[string]*Desc) Collector

NewExpvarCollector returns a newly allocated expvar Collector that still has to be registered with a Prometheus registry.

An expvar Collector collects metrics from the expvar interface. It provides a quick way to expose numeric values that are already exported via expvar as Prometheus metrics. Note that the data models of expvar and Prometheus are fundamentally different, and that the expvar Collector is inherently slower than native Prometheus metrics. Thus, the expvar Collector is probably great for experiments and prototying, but you should seriously consider a more direct implementation of Prometheus metrics for monitoring production systems.

The exports map has the following meaning:

The keys in the map correspond to expvar keys, i.e. for every expvar key you want to export as Prometheus metric, you need an entry in the exports map. The descriptor mapped to each key describes how to export the expvar value. It defines the name and the help string of the Prometheus metric proxying the expvar value. The type will always be Untyped.

For descriptors without variable labels, the expvar value must be a number or a bool. The number is then directly exported as the Prometheus sample value. (For a bool, 'false' translates to 0 and 'true' to 1). Expvar values that are not numbers or bools are silently ignored.

If the descriptor has one variable label, the expvar value must be an expvar map. The keys in the expvar map become the various values of the one Prometheus label. The values in the expvar map must be numbers or bools again as above.

For descriptors with more than one variable label, the expvar must be a nested expvar map, i.e. where the values of the topmost map are maps again etc. until a depth is reached that corresponds to the number of labels. The leaves of that structure must be numbers or bools as above to serve as the sample values.

Anything that does not fit into the scheme above is silently ignored.

func NewGoCollector 

func NewGoCollector() Collector

NewGoCollector returns a collector which exports metrics about the current go process.

func NewProcessCollector 

func NewProcessCollector(pid int, namespace string) Collector

NewProcessCollector returns a collector which exports the current state of process metrics including cpu, memory and file descriptor usage as well as the process start time for the given process id under the given namespace.

func NewProcessCollectorPIDFn 

func NewProcessCollectorPIDFn(
	pidFn func() (int, error),
	namespace string,
) Collector

NewProcessCollectorPIDFn returns a collector which exports the current state of process metrics including cpu, memory and file descriptor usage as well as the process start time under the given namespace. The given pidFn is called on each collect and is used to determine the process to export metrics for.

type Counter 

type Counter interface {
	Metric
	Collector
	Animate

	// Inc increments the counter by 1. Use Add to increment it by arbitrary
	// non-negative values.
	Inc()
	// Add adds the given value to the counter. It panics if the value is <
	// 0.
	Add(float64)
}

Counter is a Metric that represents a single numerical value that only ever goes up. That implies that it cannot be used to count items whose number can also go down, e.g. the number of currently running goroutines. Those "counters" are represented by Gauges.

A Counter is typically used to count requests served, tasks completed, errors occurred, etc.

To create Counter instances, use NewCounter.

func NewCounter 

func NewCounter(opts CounterOpts) Counter

NewCounter creates a new Counter based on the provided CounterOpts.

type CounterFunc 

type CounterFunc interface {
	Metric
	Collector
}

CounterFunc is a Counter whose value is determined at collect time by calling a provided function.

To create CounterFunc instances, use NewCounterFunc.

func NewCounterFunc 

func NewCounterFunc(opts CounterOpts, function func() float64) CounterFunc

NewCounterFunc creates a new CounterFunc based on the provided CounterOpts. The value reported is determined by calling the given function from within the Write method. Take into account that metric collection may happen concurrently. If that results in concurrent calls to Write, like in the case where a CounterFunc is directly registered with Prometheus, the provided function must be concurrency-safe. The function should also honor the contract for a Counter (values only go up, not down), but compliance will not be checked.

type CounterOpts 

type CounterOpts Opts

CounterOpts is an alias for Opts. See there for doc comments.

type CounterVec 

type CounterVec struct {
	// contains filtered or unexported fields
}

CounterVec is a Collector that bundles a set of Counters that all share the same Desc, but have different values for their variable labels. This is used if you want to count the same thing partitioned by various dimensions (e.g. number of HTTP requests, partitioned by response code and method). Create instances with NewCounterVec.

func NewCounterVec 

func NewCounterVec(opts CounterOpts, labelNames []string) *CounterVec

NewCounterVec creates a new CounterVec based on the provided CounterOpts and partitioned by the given label names.

func (CounterVec) Collect 

func (m CounterVec) Collect(ch chan<- Metric)

Collect implements Collector.

func (CounterVec) Delete 

func (m CounterVec) Delete(labels Labels) bool

Delete deletes the metric where the variable labels are the same as those passed in as labels. It returns true if a metric was deleted.

It is not an error if the number and names of the Labels are inconsistent with those of the VariableLabels in Desc. However, such inconsistent Labels can never match an actual metric, so the method will always return false in that case.

This method is used for the same purpose as DeleteLabelValues(...string). See there for pros and cons of the two methods.

func (CounterVec) DeleteLabelValues 

func (m CounterVec) DeleteLabelValues(lvs ...string) bool

DeleteLabelValues removes the metric where the variable labels are the same as those passed in as labels (same order as the VariableLabels in Desc). It returns true if a metric was deleted.

It is not an error if the number of label values is not the same as the number of VariableLabels in Desc. However, such inconsistent label count can never match an actual metric, so the method will always return false in that case.

Note that for more than one label value, this method is prone to mistakes caused by an incorrect order of arguments. Consider Delete(Labels) as an alternative to avoid that type of mistake. For higher label numbers, the latter has a much more readable (albeit more verbose) syntax, but it comes with a performance overhead (for creating and processing the Labels map). See also the CounterVec example.

func (CounterVec) Describe 

func (m CounterVec) Describe(ch chan<- *Desc)

Describe implements Collector. The length of the returned slice is always one.

func (*CounterVec) GetMetricWith 

func (m *CounterVec) GetMetricWith(labels Labels) (Counter, error)

GetMetricWith returns the Counter for the given Labels map (the label names must match those of the VariableLabels in Desc). If that label map is accessed for the first time, a new Counter is created. Implications of creating a Counter without using it and keeping the Counter for later use are the same as for GetMetricWithLabelValues.

An error is returned if the number and names of the Labels are inconsistent with those of the VariableLabels in Desc.

This method is used for the same purpose as GetMetricWithLabelValues(...string). See there for pros and cons of the two methods.

func (*CounterVec) GetMetricWithLabelValues 

func (m *CounterVec) GetMetricWithLabelValues(lvs ...string) (Counter, error)

GetMetricWithLabelValues returns the Counter for the given slice of label values (same order as the VariableLabels in Desc). If that combination of label values is accessed for the first time, a new Counter is created.

It is possible to call this method without using the returned Counter to only create the new Counter but leave it at its starting value 0. See also the SummaryVec example.

Keeping the Counter for later use is possible (and should be considered if performance is critical), but keep in mind that Reset, DeleteLabelValues and Delete can be used to delete the Counter from the CounterVec. In that case, the Counter will still exist, but it will not be exported anymore, even if a Counter with the same label values is created later.

An error is returned if the number of label values is not the same as the number of VariableLabels in Desc.

Note that for more than one label value, this method is prone to mistakes caused by an incorrect order of arguments. Consider GetMetricWith(Labels) as an alternative to avoid that type of mistake. For higher label numbers, the latter has a much more readable (albeit more verbose) syntax, but it comes with a performance overhead (for creating and processing the Labels map). See also the GaugeVec example.

func (CounterVec) Reset 

func (m CounterVec) Reset()

Reset deletes all metrics in this vector.

func (*CounterVec) With 

func (m *CounterVec) With(labels Labels) Counter

With works as GetMetricWith, but panics where GetMetricWithLabels would have returned an error. By not returning an error, With allows shortcuts like 

myVec.With(Labels{"code": "404", "method": "GET"}).Add(42)

func (*CounterVec) WithLabelValues 

func (m *CounterVec) WithLabelValues(lvs ...string) Counter

WithLabelValues works as GetMetricWithLabelValues, but panics where GetMetricWithLabelValues would have returned an error. By not returning an error, WithLabelValues allows shortcuts like 

myVec.WithLabelValues("404", "GET").Add(42)

type Desc 

type Desc struct {
	// contains filtered or unexported fields
}

Desc is the descriptor used by every Prometheus Metric. It is essentially the immutable meta-data of a Metric. The normal Metric implementations included in this package manage their Desc under the hood. Users only have to deal with Desc if they use advanced features like the ExpvarCollector or custom Collectors and Metrics.

Descriptors registered with the same registry have to fulfill certain consistency and uniqueness criteria if they share the same fully-qualified name: They must have the same help string and the same label names (aka label dimensions) in each, constLabels and variableLabels, but they must differ in the values of the constLabels.

Descriptors that share the same fully-qualified names and the same label values of their constLabels are considered equal.

Use NewDesc to create new Desc instances.

func NewDesc 

func NewDesc(fqName, help string, variableLabels []string, constLabels Labels) *Desc

NewDesc allocates and initializes a new Desc. Errors are recorded in the Desc and will be reported on registration time. variableLabels and constLabels can be nil if no such labels should be set. fqName and help must not be empty.

variableLabels only contain the label names. Their label values are variable and therefore not part of the Desc. (They are managed within the Metric.)

For constLabels, the label values are constant. Therefore, they are fully specified in the Desc. See the Opts documentation for the implications of constant labels.

func NewInvalidDesc 

func NewInvalidDesc(err error) *Desc

NewInvalidDesc returns an invalid descriptor, i.e. a descriptor with the provided error set. If a collector returning such a descriptor is registered, registration will fail with the provided error. NewInvalidDesc can be used by a Collector to signal inability to describe itself.

func (*Desc) String 

func (d *Desc) String() string

type Gatherer 

type Gatherer interface {
	// Gather calls the Collect method of the registered Collectors and then
	// gathers the collected metrics into a lexicographically sorted slice
	// of MetricFamily protobufs. Even if an error occurs, Gather attempts
	// to gather as many metrics as possible. Hence, if a non-nil error is
	// returned, the returned MetricFamily slice could be nil (in case of a
	// fatal error that prevented any meaningful metric collection) or
	// contain a number of MetricFamily protobufs, some of which might be
	// incomplete, and some might be missing altogether. The returned error
	// (which might be a MultiError) explains the details. In scenarios
	// where complete collection is critical, the returned MetricFamily
	// protobufs should be disregarded if the returned error is non-nil.
	Gather() ([]*dto.MetricFamily, error)
}

Gatherer is the interface for the part of a registry in charge of gathering the collected metrics into a number of MetricFamilies. The Gatherer interface comes with the same general implication as described for the Registerer interface.

type GathererFunc 

type GathererFunc func() ([]*dto.MetricFamily, error)

GathererFunc turns a function into a Gatherer.

func (GathererFunc) Gather 

func (gf GathererFunc) Gather() ([]*dto.MetricFamily, error)

Gather implements Gatherer.

type Gatherers 

type Gatherers []Gatherer

Gatherers is a slice of Gatherer instances that implements the Gatherer interface itself. Its Gather method calls Gather on all Gatherers in the slice in order and returns the merged results. Errors returned from the Gather calles are all returned in a flattened MultiError. Duplicate and inconsistent Metrics are skipped (first occurrence in slice order wins) and reported in the returned error.

Gatherers can be used to merge the Gather results from multiple Registries. It also provides a way to directly inject existing MetricFamily protobufs into the gathering by creating a custom Gatherer with a Gather method that simply returns the existing MetricFamily protobufs. Note that no registration is involved (in contrast to Collector registration), so obviously registration-time checks cannot happen. Any inconsistencies between the gathered MetricFamilies are reported as errors by the Gather method, and inconsistent Metrics are dropped. Invalid parts of the MetricFamilies (e.g. syntactically invalid metric or label names) will go undetected.

func (Gatherers) Gather 

func (gs Gatherers) Gather() ([]*dto.MetricFamily, error)

Gather implements Gatherer.

type Gauge 

type Gauge interface {
	Metric
	Collector
	Animate

	// Set sets the Gauge to an arbitrary value.
	Set(float64)
	// Inc increments the Gauge by 1. Use Add to increment it by arbitrary
	// values.
	Inc()
	// Dec decrements the Gauge by 1. Use Sub to decrement it by arbitrary
	// values.
	Dec()
	// Add adds the given value to the Gauge. (The value can be negative,
	// resulting in a decrease of the Gauge.)
	Add(float64)
	// Sub subtracts the given value from the Gauge. (The value can be
	// negative, resulting in an increase of the Gauge.)
	Sub(float64)

	// SetToCurrentTime sets the Gauge to the current Unix time in seconds.
	SetToCurrentTime()
}

Gauge is a Metric that represents a single numerical value that can arbitrarily go up and down.

A Gauge is typically used for measured values like temperatures or current memory usage, but also "counts" that can go up and down, like the number of running goroutines.

To create Gauge instances, use NewGauge.

func NewGauge 

func NewGauge(opts GaugeOpts) Gauge

NewGauge creates a new Gauge based on the provided GaugeOpts.

type GaugeFunc 

type GaugeFunc interface {
	Metric
	Collector
}

GaugeFunc is a Gauge whose value is determined at collect time by calling a provided function.

To create GaugeFunc instances, use NewGaugeFunc.

func NewGaugeFunc 

func NewGaugeFunc(opts GaugeOpts, function func() float64) GaugeFunc

NewGaugeFunc creates a new GaugeFunc based on the provided GaugeOpts. The value reported is determined by calling the given function from within the Write method. Take into account that metric collection may happen concurrently. If that results in concurrent calls to Write, like in the case where a GaugeFunc is directly registered with Prometheus, the provided function must be concurrency-safe.

type GaugeOpts 

type GaugeOpts Opts

GaugeOpts is an alias for Opts. See there for doc comments.

type GaugeVec 

type GaugeVec struct {
	// contains filtered or unexported fields
}

GaugeVec is a Collector that bundles a set of Gauges that all share the same Desc, but have different values for their variable labels. This is used if you want to count the same thing partitioned by various dimensions (e.g. number of operations queued, partitioned by user and operation type). Create instances with NewGaugeVec.

func NewGaugeVec 

func NewGaugeVec(opts GaugeOpts, labelNames []string) *GaugeVec

NewGaugeVec creates a new GaugeVec based on the provided GaugeOpts and partitioned by the given label names.

func (GaugeVec) Collect 

func (m GaugeVec) Collect(ch chan<- Metric)

Collect implements Collector.

func (GaugeVec) Delete 

func (m GaugeVec) Delete(labels Labels) bool

Delete deletes the metric where the variable labels are the same as those passed in as labels. It returns true if a metric was deleted.

It is not an error if the number and names of the Labels are inconsistent with those of the VariableLabels in Desc. However, such inconsistent Labels can never match an actual metric, so the method will always return false in that case.

This method is used for the same purpose as DeleteLabelValues(...string). See there for pros and cons of the two methods.

func (GaugeVec) DeleteLabelValues 

func (m GaugeVec) DeleteLabelValues(lvs ...string) bool

DeleteLabelValues removes the metric where the variable labels are the same as those passed in as labels (same order as the VariableLabels in Desc). It returns true if a metric was deleted.

It is not an error if the number of label values is not the same as the number of VariableLabels in Desc. However, such inconsistent label count can never match an actual metric, so the method will always return false in that case.

Note that for more than one label value, this method is prone to mistakes caused by an incorrect order of arguments. Consider Delete(Labels) as an alternative to avoid that type of mistake. For higher label numbers, the latter has a much more readable (albeit more verbose) syntax, but it comes with a performance overhead (for creating and processing the Labels map). See also the CounterVec example.

func (GaugeVec) Describe 

func (m GaugeVec) Describe(ch chan<- *Desc)

Describe implements Collector. The length of the returned slice is always one.

func (*GaugeVec) GetMetricWith 

func (m *GaugeVec) GetMetricWith(labels Labels) (Gauge, error)

GetMetricWith returns the Gauge for the given Labels map (the label names must match those of the VariableLabels in Desc). If that label map is accessed for the first time, a new Gauge is created. Implications of creating a Gauge without using it and keeping the Gauge for later use are the same as for GetMetricWithLabelValues.

An error is returned if the number and names of the Labels are inconsistent with those of the VariableLabels in Desc.

This method is used for the same purpose as GetMetricWithLabelValues(...string). See there for pros and cons of the two methods.

func (*GaugeVec) GetMetricWithLabelValues 

func (m *GaugeVec) GetMetricWithLabelValues(lvs ...string) (Gauge, error)

GetMetricWithLabelValues returns the Gauge for the given slice of label values (same order as the VariableLabels in Desc). If that combination of label values is accessed for the first time, a new Gauge is created.

It is possible to call this method without using the returned Gauge to only create the new Gauge but leave it at its starting value 0. See also the SummaryVec example.

Keeping the Gauge for later use is possible (and should be considered if performance is critical), but keep in mind that Reset, DeleteLabelValues and Delete can be used to delete the Gauge from the GaugeVec. In that case, the Gauge will still exist, but it will not be exported anymore, even if a Gauge with the same label values is created later. See also the CounterVec example.

An error is returned if the number of label values is not the same as the number of VariableLabels in Desc.

Note that for more than one label value, this method is prone to mistakes caused by an incorrect order of arguments. Consider GetMetricWith(Labels) as an alternative to avoid that type of mistake. For higher label numbers, the latter has a much more readable (albeit more verbose) syntax, but it comes with a performance overhead (for creating and processing the Labels map).

func (GaugeVec) Reset 

func (m GaugeVec) Reset()

Reset deletes all metrics in this vector.

func (*GaugeVec) With 

func (m *GaugeVec) With(labels Labels) Gauge

With works as GetMetricWith, but panics where GetMetricWithLabels would have returned an error. By not returning an error, With allows shortcuts like 

myVec.With(Labels{"code": "404", "method": "GET"}).Add(42)

func (*GaugeVec) WithLabelValues 

func (m *GaugeVec) WithLabelValues(lvs ...string) Gauge

WithLabelValues works as GetMetricWithLabelValues, but panics where GetMetricWithLabelValues would have returned an error. By not returning an error, WithLabelValues allows shortcuts like 

myVec.WithLabelValues("404", "GET").Add(42)

type Histogram 

type Histogram interface {
	Metric
	Collector
	Animate

	// Observe adds a single observation to the histogram.
	Observe(float64)
}

A Histogram counts individual observations from an event or sample stream in configurable buckets. Similar to a summary, it also provides a sum of observations and an observation count.

On the Prometheus server, quantiles can be calculated from a Histogram using the histogram_quantile function in the query language.

Note that Histograms, in contrast to Summaries, can be aggregated with the Prometheus query language (see the documentation for detailed procedures). However, Histograms require the user to pre-define suitable buckets, and they are in general less accurate. The Observe method of a Histogram has a very low performance overhead in comparison with the Observe method of a Summary.

To create Histogram instances, use NewHistogram.

func NewHistogram 

func NewHistogram(opts HistogramOpts) Histogram

NewHistogram creates a new Histogram based on the provided HistogramOpts. It panics if the buckets in HistogramOpts are not in strictly increasing order.

type HistogramOpts 

type HistogramOpts struct {
	// Namespace, Subsystem, and Name are components of the fully-qualified
	// name of the Histogram (created by joining these components with
	// "_"). Only Name is mandatory, the others merely help structuring the
	// name. Note that the fully-qualified name of the Histogram must be a
	// valid Prometheus metric name.
	Namespace string
	Subsystem string
	Name      string

	// Help provides information about this Histogram. Mandatory!
	//
	// Metrics with the same fully-qualified name must have the same Help
	// string.
	Help string

	// ConstLabels are used to attach fixed labels to this
	// Histogram. Histograms with the same fully-qualified name must have the
	// same label names in their ConstLabels.
	//
	// Note that in most cases, labels have a value that varies during the
	// lifetime of a process. Those labels are usually managed with a
	// HistogramVec. ConstLabels serve only special purposes. One is for the
	// special case where the value of a label does not change during the
	// lifetime of a process, e.g. if the revision of the running binary is
	// put into a label. Another, more advanced purpose is if more than one
	// Collector needs to collect Histograms with the same fully-qualified
	// name. In that case, those Summaries must differ in the values of
	// their ConstLabels. See the Collector examples.
	//
	// If the value of a label never changes (not even between binaries),
	// that label most likely should not be a label at all (but part of the
	// metric name).
	ConstLabels Labels

	// Buckets defines the buckets into which observations are counted. Each
	// element in the slice is the upper inclusive bound of a bucket. The
	// values must be sorted in strictly increasing order. There is no need
	// to add a highest bucket with +Inf bound, it will be added
	// implicitly. The default value is DefBuckets.
	Buckets []float64
}

HistogramOpts bundles the options for creating a Histogram metric. It is mandatory to set Name and Help to a non-empty string. All other fields are optional and can safely be left at their zero value.

type HistogramVec 

type HistogramVec struct {
	// contains filtered or unexported fields
}

HistogramVec is a Collector that bundles a set of Histograms that all share the same Desc, but have different values for their variable labels. This is used if you want to count the same thing partitioned by various dimensions (e.g. HTTP request latencies, partitioned by status code and method). Create instances with NewHistogramVec.

func NewHistogramVec 

func NewHistogramVec(opts HistogramOpts, labelNames []string) *HistogramVec

NewHistogramVec creates a new HistogramVec based on the provided HistogramOpts and partitioned by the given label names.

func (HistogramVec) Collect 

func (m HistogramVec) Collect(ch chan<- Metric)

Collect implements Collector.

func (HistogramVec) Delete 

func (m HistogramVec) Delete(labels Labels) bool

Delete deletes the metric where the variable labels are the same as those passed in as labels. It returns true if a metric was deleted.

It is not an error if the number and names of the Labels are inconsistent with those of the VariableLabels in Desc. However, such inconsistent Labels can never match an actual metric, so the method will always return false in that case.

This method is used for the same purpose as DeleteLabelValues(...string). See there for pros and cons of the two methods.

func (HistogramVec) DeleteLabelValues 

func (m HistogramVec) DeleteLabelValues(lvs ...string) bool

DeleteLabelValues removes the metric where the variable labels are the same as those passed in as labels (same order as the VariableLabels in Desc). It returns true if a metric was deleted.

It is not an error if the number of label values is not the same as the number of VariableLabels in Desc. However, such inconsistent label count can never match an actual metric, so the method will always return false in that case.

Note that for more than one label value, this method is prone to mistakes caused by an incorrect order of arguments. Consider Delete(Labels) as an alternative to avoid that type of mistake. For higher label numbers, the latter has a much more readable (albeit more verbose) syntax, but it comes with a performance overhead (for creating and processing the Labels map). See also the CounterVec example.

func (HistogramVec) Describe 

func (m HistogramVec) Describe(ch chan<- *Desc)

Describe implements Collector. The length of the returned slice is always one.

func (*HistogramVec) GetMetricWith 

func (m *HistogramVec) GetMetricWith(labels Labels) (Observer, error)

GetMetricWith returns the Histogram for the given Labels map (the label names must match those of the VariableLabels in Desc). If that label map is accessed for the first time, a new Histogram is created. Implications of creating a Histogram without using it and keeping the Histogram for later use are the same as for GetMetricWithLabelValues.

An error is returned if the number and names of the Labels are inconsistent with those of the VariableLabels in Desc.

This method is used for the same purpose as GetMetricWithLabelValues(...string). See there for pros and cons of the two methods.

func (*HistogramVec) GetMetricWithLabelValues 

func (m *HistogramVec) GetMetricWithLabelValues(lvs ...string) (Observer, error)

GetMetricWithLabelValues returns the Histogram for the given slice of label values (same order as the VariableLabels in Desc). If that combination of label values is accessed for the first time, a new Histogram is created.

It is possible to call this method without using the returned Histogram to only create the new Histogram but leave it at its starting value, a Histogram without any observations.

Keeping the Histogram for later use is possible (and should be considered if performance is critical), but keep in mind that Reset, DeleteLabelValues and Delete can be used to delete the Histogram from the HistogramVec. In that case, the Histogram will still exist, but it will not be exported anymore, even if a Histogram with the same label values is created later. See also the CounterVec example.

An error is returned if the number of label values is not the same as the number of VariableLabels in Desc.

Note that for more than one label value, this method is prone to mistakes caused by an incorrect order of arguments. Consider GetMetricWith(Labels) as an alternative to avoid that type of mistake. For higher label numbers, the latter has a much more readable (albeit more verbose) syntax, but it comes with a performance overhead (for creating and processing the Labels map). See also the GaugeVec example.

func (HistogramVec) Reset 

func (m HistogramVec) Reset()

Reset deletes all metrics in this vector.

func (*HistogramVec) With 

func (m *HistogramVec) With(labels Labels) Observer

With works as GetMetricWith, but panics where GetMetricWithLabels would have returned an error. By not returning an error, With allows shortcuts like 

myVec.With(Labels{"code": "404", "method": "GET"}).Observe(42.21)

func (*HistogramVec) WithLabelValues 

func (m *HistogramVec) WithLabelValues(lvs ...string) Observer

WithLabelValues works as GetMetricWithLabelValues, but panics where GetMetricWithLabelValues would have returned an error. By not returning an error, WithLabelValues allows shortcuts like 

myVec.WithLabelValues("404", "GET").Observe(42.21)

type LabelPairSorter 

type LabelPairSorter []*dto.LabelPair

LabelPairSorter implements sort.Interface. It is used to sort a slice of dto.LabelPair pointers. This is useful for implementing the Write method of custom metrics.

func (LabelPairSorter) Len 

func (s LabelPairSorter) Len() int

func (LabelPairSorter) Less 

func (s LabelPairSorter) Less(i, j int) bool

func (LabelPairSorter) Swap 

func (s LabelPairSorter) Swap(i, j int)

type Labels 

type Labels map[string]string

Labels represents a collection of label name -> value mappings. This type is commonly used with the With(Labels) and GetMetricWith(Labels) methods of metric vector Collectors, e.g.: 

myVec.With(Labels{"code": "404", "method": "GET"}).Add(42)

The other use-case is the specification of constant label pairs in Opts or to create a Desc.

type Metric 

type Metric interface {
	// Desc returns the descriptor for the Metric. This method idempotently
	// returns the same descriptor throughout the lifetime of the
	// Metric. The returned descriptor is immutable by contract. A Metric
	// unable to describe itself must return an invalid descriptor (created
	// with NewInvalidDesc).
	Desc() *Desc
	// Write encodes the Metric into a "Metric" Protocol Buffer data
	// transmission object.
	//
	// Metric implementations must observe concurrency safety as reads of
	// this metric may occur at any time, and any blocking occurs at the
	// expense of total performance of rendering all registered
	// metrics. Ideally, Metric implementations should support concurrent
	// readers.
	//
	// While populating dto.Metric, it is the responsibility of the
	// implementation to ensure validity of the Metric protobuf (like valid
	// UTF-8 strings or syntactically valid metric and label names). It is
	// recommended to sort labels lexicographically. (Implementers may find
	// LabelPairSorter useful for that.) Callers of Write should still make
	// sure of sorting if they depend on it.
	Write(*dto.Metric) error
}

A Metric models a single sample value with its meta data being exported to Prometheus. Implementations of Metric in this package are Gauge, Counter, Histogram, Summary, and Untyped.

func MustNewConstHistogram 

func MustNewConstHistogram(
	desc *Desc,
	count uint64,
	sum float64,
	buckets map[float64]uint64,
	labelValues ...string,
) Metric

MustNewConstHistogram is a version of NewConstHistogram that panics where NewConstMetric would have returned an error.

func MustNewConstMetric 

func MustNewConstMetric(desc *Desc, valueType ValueType, value float64, labelValues ...string) Metric

MustNewConstMetric is a version of NewConstMetric that panics where NewConstMetric would have returned an error.

func MustNewConstSummary 

func MustNewConstSummary(
	desc *Desc,
	count uint64,
	sum float64,
	quantiles map[float64]float64,
	labelValues ...string,
) Metric

MustNewConstSummary is a version of NewConstSummary that panics where NewConstMetric would have returned an error.

func NewConstHistogram 

func NewConstHistogram(
	desc *Desc,
	count uint64,
	sum float64,
	buckets map[float64]uint64,
	labelValues ...string,
) (Metric, error)

NewConstHistogram returns a metric representing a Prometheus histogram with fixed values for the count, sum, and bucket counts. As those parameters cannot be changed, the returned value does not implement the Histogram interface (but only the Metric interface). Users of this package will not have much use for it in regular operations. However, when implementing custom Collectors, it is useful as a throw-away metric that is generated on the fly to send it to Prometheus in the Collect method.

buckets is a map of upper bounds to cumulative counts, excluding the +Inf bucket.

NewConstHistogram returns an error if the length of labelValues is not consistent with the variable labels in Desc.

func NewConstMetric 

func NewConstMetric(desc *Desc, valueType ValueType, value float64, labelValues ...string) (Metric, error)

NewConstMetric returns a metric with one fixed value that cannot be changed. Users of this package will not have much use for it in regular operations. However, when implementing custom Collectors, it is useful as a throw-away metric that is generated on the fly to send it to Prometheus in the Collect method. NewConstMetric returns an error if the length of labelValues is not consistent with the variable labels in Desc.

func NewConstSummary 

func NewConstSummary(
	desc *Desc,
	count uint64,
	sum float64,
	quantiles map[float64]float64,
	labelValues ...string,
) (Metric, error)

NewConstSummary returns a metric representing a Prometheus summary with fixed values for the count, sum, and quantiles. As those parameters cannot be changed, the returned value does not implement the Summary interface (but only the Metric interface). Users of this package will not have much use for it in regular operations. However, when implementing custom Collectors, it is useful as a throw-away metric that is generated on the fly to send it to Prometheus in the Collect method.

quantiles maps ranks to quantile values. For example, a median latency of 0.23s and a 99th percentile latency of 0.56s would be expressed as: 

map[float64]float64{0.5: 0.23, 0.99: 0.56}

NewConstSummary returns an error if the length of labelValues is not consistent with the variable labels in Desc.

func NewInvalidMetric 

func NewInvalidMetric(desc *Desc, err error) Metric

NewInvalidMetric returns a metric whose Write method always returns the provided error. It is useful if a Collector finds itself unable to collect a metric and wishes to report an error to the registry.

type MultiError 

type MultiError []error

MultiError is a slice of errors implementing the error interface. It is used by a Gatherer to report multiple errors during MetricFamily gathering.

func (MultiError) Error 

func (errs MultiError) Error() string

func (MultiError) MaybeUnwrap 

func (errs MultiError) MaybeUnwrap() error

MaybeUnwrap returns nil if len(errs) is 0. It returns the first and only contained error as error if len(errs is 1). In all other cases, it returns the MultiError directly. This is helpful for returning a MultiError in a way that only uses the MultiError if needed.

type Observer 

type Observer interface {
	Observe(float64)
}

Observer is the interface that wraps the Observe method, which is used by Histogram and Summary to add observations.

type ObserverFunc 

type ObserverFunc func(float64)

The ObserverFunc type is an adapter to allow the use of ordinary functions as Observers. If f is a function with the appropriate signature, ObserverFunc(f) is an Observer that calls f.

This adapter is usually used in connection with the Timer type, and there are two general use cases:

The most common one is to use a Gauge as the Observer for a Timer. See the "Gauge" Timer example.

The more advanced use case is to create a function that dynamically decides which Observer to use for observing the duration. See the "Complex" Timer example.

func (ObserverFunc) Observe 

func (f ObserverFunc) Observe(value float64)

Observe calls f(value). It implements Observer.

type ObserverVec 

type ObserverVec interface {
	GetMetricWith(Labels) (Observer, error)
	GetMetricWithLabelValues(lvs ...string) (Observer, error)
	With(Labels) Observer
	WithLabelValues(...string) Observer

	Collector
}

ObserverVec is an interface implemented by `HistogramVec` and `SummaryVec`.

type Opts 

type Opts struct {
	// Namespace, Subsystem, and Name are components of the fully-qualified
	// name of the Metric (created by joining these components with
	// "_"). Only Name is mandatory, the others merely help structuring the
	// name. Note that the fully-qualified name of the metric must be a
	// valid Prometheus metric name.
	Namespace string
	Subsystem string
	Name      string

	// Help provides information about this metric. Mandatory!
	//
	// Metrics with the same fully-qualified name must have the same Help
	// string.
	Help string

	// ConstLabels are used to attach fixed labels to this metric. Metrics
	// with the same fully-qualified name must have the same label names in
	// their ConstLabels.
	//
	// Note that in most cases, labels have a value that varies during the
	// lifetime of a process. Those labels are usually managed with a metric
	// vector collector (like CounterVec, GaugeVec, UntypedVec). ConstLabels
	// serve only special purposes. One is for the special case where the
	// value of a label does not change during the lifetime of a process,
	// e.g. if the revision of the running binary is put into a
	// label. Another, more advanced purpose is if more than one Collector
	// needs to collect Metrics with the same fully-qualified name. In that
	// case, those Metrics must differ in the values of their
	// ConstLabels. See the Collector examples.
	//
	// If the value of a label never changes (not even between binaries),
	// that label most likely should not be a label at all (but part of the
	// metric name).
	ConstLabels Labels
}

Opts bundles the options for creating most Metric types. Each metric implementation XXX has its own XXXOpts type, but in most cases, it is just be an alias of this type (which might change when the requirement arises.)

It is mandatory to set Name and Help to a non-empty string. All other fields are optional and can safely be left at their zero value.

type Registerer 

type Registerer interface {
	// Register registers a new Collector to be included in metrics
	// collection. It returns an error if the descriptors provided by the
	// Collector are invalid or if they — in combination with descriptors of
	// already registered Collectors — do not fulfill the consistency and
	// uniqueness criteria described in the documentation of metric.Desc.
	//
	// If the provided Collector is equal to a Collector already registered
	// (which includes the case of re-registering the same Collector), the
	// returned error is an instance of AlreadyRegisteredError, which
	// contains the previously registered Collector.
	//
	// It is in general not safe to register the same Collector multiple
	// times concurrently.
	Register(Collector) error
	// MustRegister works like Register but registers any number of
	// Collectors and panics upon the first registration that causes an
	// error.
	MustRegister(...Collector)
	// Unregister unregisters the Collector that equals the Collector passed
	// in as an argument.  (Two Collectors are considered equal if their
	// Describe method yields the same set of descriptors.) The function
	// returns whether a Collector was unregistered.
	//
	// Note that even after unregistering, it will not be possible to
	// register a new Collector that is inconsistent with the unregistered
	// Collector, e.g. a Collector collecting metrics with the same name but
	// a different help string. The rationale here is that the same registry
	// instance must only collect consistent metrics throughout its
	// lifetime.
	Unregister(Collector) bool
}

Registerer is the interface for the part of a registry in charge of registering and unregistering. Users of custom registries should use Registerer as type for registration purposes (rather than the Registry type directly). In that way, they are free to use custom Registerer implementation (e.g. for testing purposes).

type Registry 

type Registry struct {
	// contains filtered or unexported fields
}

Registry registers Prometheus collectors, collects their metrics, and gathers them into MetricFamilies for exposition. It implements both Registerer and Gatherer. The zero value is not usable. Create instances with NewRegistry or NewPedanticRegistry.

func NewPedanticRegistry 

func NewPedanticRegistry() *Registry

NewPedanticRegistry returns a registry that checks during collection if each collected Metric is consistent with its reported Desc, and if the Desc has actually been registered with the registry.

Usually, a Registry will be happy as long as the union of all collected Metrics is consistent and valid even if some metrics are not consistent with their own Desc or a Desc provided by their registered Collector. Well-behaved Collectors and Metrics will only provide consistent Descs. This Registry is useful to test the implementation of Collectors and Metrics.

func NewRegistry 

func NewRegistry() *Registry

NewRegistry creates a new vanilla Registry without any Collectors pre-registered.

func (*Registry) Gather 

func (r *Registry) Gather() ([]*dto.MetricFamily, error)

Gather implements Gatherer.

func (*Registry) MustRegister 

func (r *Registry) MustRegister(cs ...Collector)

MustRegister implements Registerer.

func (*Registry) Register 

func (r *Registry) Register(c Collector) error

Register implements Registerer.

func (*Registry) Unregister 

func (r *Registry) Unregister(c Collector) bool

Unregister implements Registerer.

type Summary 

type Summary interface {
	Metric
	Collector
	Animate

	// Observe adds a single observation to the summary.
	Observe(float64)
}

A Summary captures individual observations from an event or sample stream and summarizes them in a manner similar to traditional summary statistics: 1. sum of observations, 2. observation count, 3. rank estimations.

A typical use-case is the observation of request latencies. By default, a Summary provides the median, the 90th and the 99th percentile of the latency as rank estimations.

Note that the rank estimations cannot be aggregated in a meaningful way with the Prometheus query language (i.e. you cannot average or add them). If you need aggregatable quantiles (e.g. you want the 99th percentile latency of all queries served across all instances of a service), consider the Histogram metric type. See the Prometheus documentation for more details.

To create Summary instances, use NewSummary.

func NewSummary 

func NewSummary(opts SummaryOpts) Summary

NewSummary creates a new Summary based on the provided SummaryOpts.

type SummaryOpts 

type SummaryOpts struct {
	// Namespace, Subsystem, and Name are components of the fully-qualified
	// name of the Summary (created by joining these components with
	// "_"). Only Name is mandatory, the others merely help structuring the
	// name. Note that the fully-qualified name of the Summary must be a
	// valid Prometheus metric name.
	Namespace string
	Subsystem string
	Name      string

	// Help provides information about this Summary. Mandatory!
	//
	// Metrics with the same fully-qualified name must have the same Help
	// string.
	Help string

	// ConstLabels are used to attach fixed labels to this
	// Summary. Summaries with the same fully-qualified name must have the
	// same label names in their ConstLabels.
	//
	// Note that in most cases, labels have a value that varies during the
	// lifetime of a process. Those labels are usually managed with a
	// SummaryVec. ConstLabels serve only special purposes. One is for the
	// special case where the value of a label does not change during the
	// lifetime of a process, e.g. if the revision of the running binary is
	// put into a label. Another, more advanced purpose is if more than one
	// Collector needs to collect Summaries with the same fully-qualified
	// name. In that case, those Summaries must differ in the values of
	// their ConstLabels. See the Collector examples.
	//
	// If the value of a label never changes (not even between binaries),
	// that label most likely should not be a label at all (but part of the
	// metric name).
	ConstLabels Labels

	// Objectives defines the quantile rank estimates with their respective
	// absolute error. If Objectives[q] = e, then the value reported for q
	// will be the φ-quantile value for some φ between q-e and q+e.  The
	// default value is DefObjectives. It is used if Objectives is left at
	// its zero value (i.e. nil). To create a Summary without Objectives,
	// set it to an empty map (i.e. map[float64]float64{}).
	//
	// Deprecated: Note that the current value of DefObjectives is
	// deprecated. It will be replaced by an empty map in v0.10 of the
	// library. Please explicitly set Objectives to the desired value.
	Objectives map[float64]float64

	// MaxAge defines the duration for which an observation stays relevant
	// for the summary. Must be positive. The default value is DefMaxAge.
	MaxAge time.Duration

	// AgeBuckets is the number of buckets used to exclude observations that
	// are older than MaxAge from the summary. A higher number has a
	// resource penalty, so only increase it if the higher resolution is
	// really required. For very high observation rates, you might want to
	// reduce the number of age buckets. With only one age bucket, you will
	// effectively see a complete reset of the summary each time MaxAge has
	// passed. The default value is DefAgeBuckets.
	AgeBuckets uint32

	// BufCap defines the default sample stream buffer size.  The default
	// value of DefBufCap should suffice for most uses. If there is a need
	// to increase the value, a multiple of 500 is recommended (because that
	// is the internal buffer size of the underlying package
	// "github.com/bmizerany/perks/quantile").
	BufCap uint32
}

SummaryOpts bundles the options for creating a Summary metric. It is mandatory to set Name and Help to a non-empty string. All other fields are optional and can safely be left at their zero value.

type SummaryVec 

type SummaryVec struct {
	// contains filtered or unexported fields
}

SummaryVec is a Collector that bundles a set of Summaries that all share the same Desc, but have different values for their variable labels. This is used if you want to count the same thing partitioned by various dimensions (e.g. HTTP request latencies, partitioned by status code and method). Create instances with NewSummaryVec.

func NewSummaryVec 

func NewSummaryVec(opts SummaryOpts, labelNames []string) *SummaryVec

NewSummaryVec creates a new SummaryVec based on the provided SummaryOpts and partitioned by the given label names.

func (SummaryVec) Collect 

func (m SummaryVec) Collect(ch chan<- Metric)

Collect implements Collector.

func (SummaryVec) Delete 

func (m SummaryVec) Delete(labels Labels) bool

Delete deletes the metric where the variable labels are the same as those passed in as labels. It returns true if a metric was deleted.

It is not an error if the number and names of the Labels are inconsistent with those of the VariableLabels in Desc. However, such inconsistent Labels can never match an actual metric, so the method will always return false in that case.

This method is used for the same purpose as DeleteLabelValues(...string). See there for pros and cons of the two methods.

func (SummaryVec) DeleteLabelValues 

func (m SummaryVec) DeleteLabelValues(lvs ...string) bool

DeleteLabelValues removes the metric where the variable labels are the same as those passed in as labels (same order as the VariableLabels in Desc). It returns true if a metric was deleted.

It is not an error if the number of label values is not the same as the number of VariableLabels in Desc. However, such inconsistent label count can never match an actual metric, so the method will always return false in that case.

Note that for more than one label value, this method is prone to mistakes caused by an incorrect order of arguments. Consider Delete(Labels) as an alternative to avoid that type of mistake. For higher label numbers, the latter has a much more readable (albeit more verbose) syntax, but it comes with a performance overhead (for creating and processing the Labels map). See also the CounterVec example.

func (SummaryVec) Describe 

func (m SummaryVec) Describe(ch chan<- *Desc)

Describe implements Collector. The length of the returned slice is always one.

func (*SummaryVec) GetMetricWith 

func (m *SummaryVec) GetMetricWith(labels Labels) (Observer, error)

GetMetricWith returns the Summary for the given Labels map (the label names must match those of the VariableLabels in Desc). If that label map is accessed for the first time, a new Summary is created. Implications of creating a Summary without using it and keeping the Summary for later use are the same as for GetMetricWithLabelValues.

An error is returned if the number and names of the Labels are inconsistent with those of the VariableLabels in Desc.

This method is used for the same purpose as GetMetricWithLabelValues(...string). See there for pros and cons of the two methods.

func (*SummaryVec) GetMetricWithLabelValues 

func (m *SummaryVec) GetMetricWithLabelValues(lvs ...string) (Observer, error)

GetMetricWithLabelValues returns the Summary for the given slice of label values (same order as the VariableLabels in Desc). If that combination of label values is accessed for the first time, a new Summary is created.

It is possible to call this method without using the returned Summary to only create the new Summary but leave it at its starting value, a Summary without any observations.

Keeping the Summary for later use is possible (and should be considered if performance is critical), but keep in mind that Reset, DeleteLabelValues and Delete can be used to delete the Summary from the SummaryVec. In that case, the Summary will still exist, but it will not be exported anymore, even if a Summary with the same label values is created later. See also the CounterVec example.

An error is returned if the number of label values is not the same as the number of VariableLabels in Desc.

Note that for more than one label value, this method is prone to mistakes caused by an incorrect order of arguments. Consider GetMetricWith(Labels) as an alternative to avoid that type of mistake. For higher label numbers, the latter has a much more readable (albeit more verbose) syntax, but it comes with a performance overhead (for creating and processing the Labels map). See also the GaugeVec example.

func (SummaryVec) Reset 

func (m SummaryVec) Reset()

Reset deletes all metrics in this vector.

func (*SummaryVec) With 

func (m *SummaryVec) With(labels Labels) Observer

With works as GetMetricWith, but panics where GetMetricWithLabels would have returned an error. By not returning an error, With allows shortcuts like 

myVec.With(Labels{"code": "404", "method": "GET"}).Observe(42.21)

func (*SummaryVec) WithLabelValues 

func (m *SummaryVec) WithLabelValues(lvs ...string) Observer

WithLabelValues works as GetMetricWithLabelValues, but panics where GetMetricWithLabelValues would have returned an error. By not returning an error, WithLabelValues allows shortcuts like 

myVec.WithLabelValues("404", "GET").Observe(42.21)

type Timer 

type Timer struct {
	// contains filtered or unexported fields
}

Timer is a helper type to time functions. Use NewTimer to create new instances.

func NewTimer 

func NewTimer(o Observer) *Timer

NewTimer creates a new Timer. The provided Observer is used to observe a duration in seconds. Timer is usually used to time a function call in the following way: 

func TimeMe() {
    timer := NewTimer(myHistogram)
    defer timer.ObserveDuration()
    // Do actual work.
}

func (*Timer) ObserveDuration 

func (t *Timer) ObserveDuration()

ObserveDuration records the duration passed since the Timer was created with NewTimer. It calls the Observe method of the Observer provided during construction with the duration in seconds as an argument. ObserveDuration is usually called with a defer statement.

Note that this method is only guaranteed to never observe negative durations if used with Go1.9+.

type UntypedFunc 

type UntypedFunc interface {
	Metric
	Collector
}

UntypedFunc works like GaugeFunc but the collected metric is of type "Untyped". UntypedFunc is useful to mirror an external metric of unknown type.

To create UntypedFunc instances, use NewUntypedFunc.

func NewUntypedFunc 

func NewUntypedFunc(opts UntypedOpts, function func() float64) UntypedFunc

NewUntypedFunc creates a new UntypedFunc based on the provided UntypedOpts. The value reported is determined by calling the given function from within the Write method. Take into account that metric collection may happen concurrently. If that results in concurrent calls to Write, like in the case where an UntypedFunc is directly registered with Prometheus, the provided function must be concurrency-safe.

type UntypedOpts 

type UntypedOpts Opts

UntypedOpts is an alias for Opts. See there for doc comments.

type ValueType 

type ValueType int

ValueType is an enumeration of metric types that represent a simple value. 

const (
	CounterValue ValueType
	GaugeValue
	UntypedValue
)

Possible values for the ValueType enum.

Source Files

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Directories

Path Synopsis
Package promhttp provides tooling around HTTP servers and clients.
 Package promhttp provides tooling around HTTP servers and clients.

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