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// Copyright 2022 The OpenZipkin Authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
/*
Package model contains the Zipkin V2 model which is used by the Zipkin Go
tracer implementation.
Third party instrumentation libraries can use the model and transport packages
found in this Zipkin Go library to directly interface with the Zipkin Server or
Zipkin Collectors without the need to use the tracer implementation itself.
*/
package model
// Copyright 2022 The OpenZipkin Authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package model
import (
"encoding/json"
"net"
"strings"
)
// Endpoint holds the network context of a node in the service graph.
type Endpoint struct {
ServiceName string
IPv4 net.IP
IPv6 net.IP
Port uint16
}
// MarshalJSON exports our Endpoint into the correct format for the Zipkin V2 API.
func (e Endpoint) MarshalJSON() ([]byte, error) {
return json.Marshal(&struct {
ServiceName string `json:"serviceName,omitempty"`
IPv4 net.IP `json:"ipv4,omitempty"`
IPv6 net.IP `json:"ipv6,omitempty"`
Port uint16 `json:"port,omitempty"`
}{
strings.ToLower(e.ServiceName),
e.IPv4,
e.IPv6,
e.Port,
})
}
// Empty returns if all Endpoint properties are empty / unspecified.
func (e *Endpoint) Empty() bool {
return e == nil ||
(e.ServiceName == "" && e.Port == 0 && len(e.IPv4) == 0 && len(e.IPv6) == 0)
}
// Copyright 2022 The OpenZipkin Authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package model
// Kind clarifies context of timestamp, duration and remoteEndpoint in a span.
type Kind string
// Available Kind values
const (
Undetermined Kind = ""
Client Kind = "CLIENT"
Server Kind = "SERVER"
Producer Kind = "PRODUCER"
Consumer Kind = "CONSUMER"
)
// Copyright 2022 The OpenZipkin Authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package model
import (
"encoding/json"
"errors"
"strings"
"time"
)
// unmarshal errors
var (
ErrValidTraceIDRequired = errors.New("valid traceId required")
ErrValidIDRequired = errors.New("valid span id required")
ErrValidDurationRequired = errors.New("valid duration required")
)
// BaggageFields holds the interface for consumers needing to interact with
// the fields in application logic.
type BaggageFields interface {
// Get returns the values for a field identified by its key.
Get(key string) []string
// Add adds the provided values to a header designated by key. If not
// accepted by the baggage implementation, it will return false.
Add(key string, value ...string) bool
// Set sets the provided values to a header designated by key. If not
// accepted by the baggage implementation, it will return false.
Set(key string, value ...string) bool
// Delete removes the field data designated by key. If not accepted by the
// baggage implementation, it will return false.
Delete(key string) bool
// Iterate will iterate over the available fields and for each one it will
// trigger the callback function.
Iterate(f func(key string, values []string))
}
// SpanContext holds the context of a Span.
type SpanContext struct {
TraceID TraceID `json:"traceId"`
ID ID `json:"id"`
ParentID *ID `json:"parentId,omitempty"`
Debug bool `json:"debug,omitempty"`
Sampled *bool `json:"-"`
Err error `json:"-"`
Baggage BaggageFields `json:"-"`
}
// SpanModel structure.
//
// If using this library to instrument your application you will not need to
// directly access or modify this representation. The SpanModel is exported for
// use cases involving 3rd party Go instrumentation libraries desiring to
// export data to a Zipkin server using the Zipkin V2 Span model.
type SpanModel struct {
SpanContext
Name string `json:"name,omitempty"`
Kind Kind `json:"kind,omitempty"`
Timestamp time.Time `json:"-"`
Duration time.Duration `json:"-"`
Shared bool `json:"shared,omitempty"`
LocalEndpoint *Endpoint `json:"localEndpoint,omitempty"`
RemoteEndpoint *Endpoint `json:"remoteEndpoint,omitempty"`
Annotations []Annotation `json:"annotations,omitempty"`
Tags map[string]string `json:"tags,omitempty"`
}
// MarshalJSON exports our Model into the correct format for the Zipkin V2 API.
func (s SpanModel) MarshalJSON() ([]byte, error) {
type Alias SpanModel
var timestamp int64
if !s.Timestamp.IsZero() {
if s.Timestamp.Unix() < 1 {
// Zipkin does not allow Timestamps before Unix epoch
return nil, ErrValidTimestampRequired
}
timestamp = s.Timestamp.Round(time.Microsecond).UnixNano() / 1e3
}
if s.Duration < time.Microsecond {
if s.Duration < 0 {
// negative duration is not allowed and signals a timing logic error
return nil, ErrValidDurationRequired
} else if s.Duration > 0 {
// sub microsecond durations are reported as 1 microsecond
s.Duration = 1 * time.Microsecond
}
} else {
// Duration will be rounded to nearest microsecond representation.
//
// NOTE: Duration.Round() is not available in Go 1.8 which we still support.
// To handle microsecond resolution rounding we'll add 500 nanoseconds to
// the duration. When truncated to microseconds in the call to marshal, it
// will be naturally rounded. See TestSpanDurationRounding in span_test.go
s.Duration += 500 * time.Nanosecond
}
s.Name = strings.ToLower(s.Name)
if s.LocalEndpoint.Empty() {
s.LocalEndpoint = nil
}
if s.RemoteEndpoint.Empty() {
s.RemoteEndpoint = nil
}
return json.Marshal(&struct {
T int64 `json:"timestamp,omitempty"`
D int64 `json:"duration,omitempty"`
Alias
}{
T: timestamp,
D: s.Duration.Nanoseconds() / 1e3,
Alias: (Alias)(s),
})
}
// UnmarshalJSON imports our Model from a Zipkin V2 API compatible span
// representation.
func (s *SpanModel) UnmarshalJSON(b []byte) error {
type Alias SpanModel
span := &struct {
T uint64 `json:"timestamp,omitempty"`
D uint64 `json:"duration,omitempty"`
*Alias
}{
Alias: (*Alias)(s),
}
if err := json.Unmarshal(b, &span); err != nil {
return err
}
if s.ID < 1 {
return ErrValidIDRequired
}
if span.T > 0 {
s.Timestamp = time.Unix(0, int64(span.T)*1e3)
}
s.Duration = time.Duration(span.D*1e3) * time.Nanosecond
if s.LocalEndpoint.Empty() {
s.LocalEndpoint = nil
}
if s.RemoteEndpoint.Empty() {
s.RemoteEndpoint = nil
}
return nil
}
// Copyright 2022 The OpenZipkin Authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package model
import (
"fmt"
"strconv"
)
// ID type
type ID uint64
// String outputs the 64-bit ID as hex string.
func (i ID) String() string {
return fmt.Sprintf("%016x", uint64(i))
}
// MarshalJSON serializes an ID type (SpanID, ParentSpanID) to HEX.
func (i ID) MarshalJSON() ([]byte, error) {
return []byte(fmt.Sprintf("%q", i.String())), nil
}
// UnmarshalJSON deserializes an ID type (SpanID, ParentSpanID) from HEX.
func (i *ID) UnmarshalJSON(b []byte) (err error) {
var id uint64
if len(b) < 3 {
return nil
}
id, err = strconv.ParseUint(string(b[1:len(b)-1]), 16, 64)
*i = ID(id)
return err
}
// Copyright 2022 The OpenZipkin Authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package model
import (
"fmt"
"strconv"
)
// TraceID is a 128 bit number internally stored as 2x uint64 (high & low).
// In case of 64 bit traceIDs, the value can be found in Low.
type TraceID struct {
High uint64
Low uint64
}
// Empty returns if TraceID has zero value.
func (t TraceID) Empty() bool {
return t.Low == 0 && t.High == 0
}
// String outputs the 128-bit traceID as hex string.
func (t TraceID) String() string {
if t.High == 0 {
return fmt.Sprintf("%016x", t.Low)
}
return fmt.Sprintf("%016x%016x", t.High, t.Low)
}
// TraceIDFromHex returns the TraceID from a hex string.
func TraceIDFromHex(h string) (t TraceID, err error) {
if len(h) > 16 {
if t.High, err = strconv.ParseUint(h[0:len(h)-16], 16, 64); err != nil {
return
}
t.Low, err = strconv.ParseUint(h[len(h)-16:], 16, 64)
return
}
t.Low, err = strconv.ParseUint(h, 16, 64)
return
}
// MarshalJSON custom JSON serializer to export the TraceID in the required
// zero padded hex representation.
func (t TraceID) MarshalJSON() ([]byte, error) {
return []byte(fmt.Sprintf("%q", t.String())), nil
}
// UnmarshalJSON custom JSON deserializer to retrieve the traceID from the hex
// encoded representation.
func (t *TraceID) UnmarshalJSON(traceID []byte) error {
if len(traceID) < 3 {
return ErrValidTraceIDRequired
}
// A valid JSON string is encoded wrapped in double quotes. We need to trim
// these before converting the hex payload.
tID, err := TraceIDFromHex(string(traceID[1 : len(traceID)-1]))
if err != nil {
return err
}
*t = tID
return nil
}
command-line-arguments.test
See [![go-doc](https://godoc.org/github.com/prometheus/client_golang/prometheus?status.svg)](https://godoc.org/github.com/prometheus/client_golang/prometheus).
See [![Go Reference](https://pkg.go.dev/badge/github.com/prometheus/client_golang/prometheus.svg)](https://pkg.go.dev/github.com/prometheus/client_golang/prometheus).
// Copyright 2021 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package prometheus
import "runtime/debug"
// NewBuildInfoCollector is the obsolete version of collectors.NewBuildInfoCollector.
// See there for documentation.
//
// Deprecated: Use collectors.NewBuildInfoCollector instead.
func NewBuildInfoCollector() Collector {
path, version, sum := "unknown", "unknown", "unknown"
if bi, ok := debug.ReadBuildInfo(); ok {
path = bi.Main.Path
version = bi.Main.Version
sum = bi.Main.Sum
}
c := &selfCollector{MustNewConstMetric(
NewDesc(
"go_build_info",
"Build information about the main Go module.",
nil, Labels{"path": path, "version": version, "checksum": sum},
),
GaugeValue, 1)}
c.init(c.self)
return c
}
......@@ -29,27 +29,72 @@ type Collector interface {
// 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.
// 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.
//
// Sending no descriptor at all marks the Collector as “unchecked”,
// i.e. no checks will be performed at registration time, and the
// Collector may yield any Metric it sees fit in its Collect method.
//
// This method idempotently sends the same descriptors throughout the
// lifetime of the Collector. It may be called concurrently and
// therefore must be implemented in a concurrency safe way.
//
// 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.
// descriptor of each sent metric is one of those returned by Describe
// (unless the Collector is unchecked, see above). 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)
}
// DescribeByCollect is a helper to implement the Describe method of a custom
// Collector. It collects the metrics from the provided Collector and sends
// their descriptors to the provided channel.
//
// If a Collector collects the same metrics throughout its lifetime, its
// Describe method can simply be implemented as:
//
// func (c customCollector) Describe(ch chan<- *Desc) {
// DescribeByCollect(c, ch)
// }
//
// However, this will not work if the metrics collected change dynamically over
// the lifetime of the Collector in a way that their combined set of descriptors
// changes as well. The shortcut implementation will then violate the contract
// of the Describe method. If a Collector sometimes collects no metrics at all
// (for example vectors like CounterVec, GaugeVec, etc., which only collect
// metrics after a metric with a fully specified label set has been accessed),
// it might even get registered as an unchecked Collector (cf. the Register
// method of the Registerer interface). Hence, only use this shortcut
// implementation of Describe if you are certain to fulfill the contract.
//
// The Collector example demonstrates a use of DescribeByCollect.
func DescribeByCollect(c Collector, descs chan<- *Desc) {
metrics := make(chan Metric)
go func() {
c.Collect(metrics)
close(metrics)
}()
for m := range metrics {
descs <- m.Desc()
}
}
// selfCollector implements Collector for a single Metric so that the Metric
// collects itself. Add it as an anonymous field to a struct that implements
// Metric, and call init with the Metric itself as an argument.
......@@ -73,3 +118,11 @@ func (c *selfCollector) Describe(ch chan<- *Desc) {
func (c *selfCollector) Collect(ch chan<- Metric) {
ch <- c.self
}
// collectorMetric is a metric that is also a collector.
// Because of selfCollector, most (if not all) Metrics in
// this package are also collectors.
type collectorMetric interface {
Metric
Collector
}
......@@ -15,6 +15,11 @@ package prometheus
import (
"errors"
"math"
"sync/atomic"
"time"
dto "github.com/prometheus/client_model/go"
)
// Counter is a Metric that represents a single numerical value that only ever
......@@ -38,10 +43,34 @@ type Counter interface {
Add(float64)
}
// ExemplarAdder is implemented by Counters that offer the option of adding a
// value to the Counter together with an exemplar. Its AddWithExemplar method
// works like the Add method of the Counter interface but also replaces the
// currently saved exemplar (if any) with a new one, created from the provided
// value, the current time as timestamp, and the provided labels. Empty Labels
// will lead to a valid (label-less) exemplar. But if Labels is nil, the current
// exemplar is left in place. AddWithExemplar panics if the value is < 0, if any
// of the provided labels are invalid, or if the provided labels contain more
// than 64 runes in total.
type ExemplarAdder interface {
AddWithExemplar(value float64, exemplar Labels)
}
// CounterOpts is an alias for Opts. See there for doc comments.
type CounterOpts Opts
// NewCounter creates a new Counter based on the provided CounterOpts.
//
// The returned implementation also implements ExemplarAdder. It is safe to
// perform the corresponding type assertion.
//
// The returned implementation tracks the counter value in two separate
// variables, a float64 and a uint64. The latter is used to track calls of the
// Inc method and calls of the Add method with a value that can be represented
// as a uint64. This allows atomic increments of the counter with optimal
// performance. (It is common to have an Inc call in very hot execution paths.)
// Both internal tracking values are added up in the Write method. This has to
// be taken into account when it comes to precision and overflow behavior.
func NewCounter(opts CounterOpts) Counter {
desc := NewDesc(
BuildFQName(opts.Namespace, opts.Subsystem, opts.Name),
......@@ -49,20 +78,87 @@ func NewCounter(opts CounterOpts) Counter {
nil,
opts.ConstLabels,
)
result := &counter{value: value{desc: desc, valType: CounterValue, labelPairs: desc.constLabelPairs}}
result := &counter{desc: desc, labelPairs: desc.constLabelPairs, now: time.Now}
result.init(result) // Init self-collection.
return result
}
type counter struct {
value
// valBits contains the bits of the represented float64 value, while
// valInt stores values that are exact integers. Both have to go first
// in the struct to guarantee alignment for atomic operations.
// http://golang.org/pkg/sync/atomic/#pkg-note-BUG
valBits uint64
valInt uint64
selfCollector
desc *Desc
labelPairs []*dto.LabelPair
exemplar atomic.Value // Containing nil or a *dto.Exemplar.
now func() time.Time // To mock out time.Now() for testing.
}
func (c *counter) Desc() *Desc {
return c.desc
}
func (c *counter) Add(v float64) {
if v < 0 {
panic(errors.New("counter cannot decrease in value"))
}
c.value.Add(v)
ival := uint64(v)
if float64(ival) == v {
atomic.AddUint64(&c.valInt, ival)
return
}
for {
oldBits := atomic.LoadUint64(&c.valBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + v)
if atomic.CompareAndSwapUint64(&c.valBits, oldBits, newBits) {
return
}
}
}
func (c *counter) AddWithExemplar(v float64, e Labels) {
c.Add(v)
c.updateExemplar(v, e)
}
func (c *counter) Inc() {
atomic.AddUint64(&c.valInt, 1)
}
func (c *counter) get() float64 {
fval := math.Float64frombits(atomic.LoadUint64(&c.valBits))
ival := atomic.LoadUint64(&c.valInt)
return fval + float64(ival)
}
func (c *counter) Write(out *dto.Metric) error {
val := c.get()
var exemplar *dto.Exemplar
if e := c.exemplar.Load(); e != nil {
exemplar = e.(*dto.Exemplar)
}
return populateMetric(CounterValue, val, c.labelPairs, exemplar, out)
}
func (c *counter) updateExemplar(v float64, l Labels) {
if l == nil {
return
}
e, err := newExemplar(v, c.now(), l)
if err != nil {
panic(err)
}
c.exemplar.Store(e)
}
// CounterVec is a Collector that bundles a set of Counters that all share the
......@@ -71,7 +167,7 @@ func (c *counter) Add(v float64) {
// (e.g. number of HTTP requests, partitioned by response code and
// method). Create instances with NewCounterVec.
type CounterVec struct {
*metricVec
*MetricVec
}
// NewCounterVec creates a new CounterVec based on the provided CounterOpts and
......@@ -84,12 +180,11 @@ func NewCounterVec(opts CounterOpts, labelNames []string) *CounterVec {
opts.ConstLabels,
)
return &CounterVec{
metricVec: newMetricVec(desc, func(lvs ...string) Metric {
result := &counter{value: value{
desc: desc,
valType: CounterValue,
labelPairs: makeLabelPairs(desc, lvs),
}}
MetricVec: NewMetricVec(desc, func(lvs ...string) Metric {
if len(lvs) != len(desc.variableLabels) {
panic(makeInconsistentCardinalityError(desc.fqName, desc.variableLabels, lvs))
}
result := &counter{desc: desc, labelPairs: MakeLabelPairs(desc, lvs), now: time.Now}
result.init(result) // Init self-collection.
return result
}),
......@@ -97,7 +192,7 @@ func NewCounterVec(opts CounterOpts, labelNames []string) *CounterVec {
}
// GetMetricWithLabelValues returns the Counter for the given slice of label
// values (same order as the VariableLabels in Desc). If that combination of
// values (same order as the variable labels 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
......@@ -111,7 +206,7 @@ func NewCounterVec(opts CounterOpts, labelNames []string) *CounterVec {
// 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.
// number of variable labels in Desc (minus any curried labels).
//
// 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
......@@ -119,8 +214,8 @@ func NewCounterVec(opts CounterOpts, labelNames []string) *CounterVec {
// 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 (m *CounterVec) GetMetricWithLabelValues(lvs ...string) (Counter, error) {
metric, err := m.metricVec.getMetricWithLabelValues(lvs...)
func (v *CounterVec) GetMetricWithLabelValues(lvs ...string) (Counter, error) {
metric, err := v.MetricVec.GetMetricWithLabelValues(lvs...)
if metric != nil {
return metric.(Counter), err
}
......@@ -128,19 +223,19 @@ func (m *CounterVec) GetMetricWithLabelValues(lvs ...string) (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
// must match those of the variable labels 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.
// with those of the variable labels in Desc (minus any curried labels).
//
// This method is used for the same purpose as
// GetMetricWithLabelValues(...string). See there for pros and cons of the two
// methods.
func (m *CounterVec) GetMetricWith(labels Labels) (Counter, error) {
metric, err := m.metricVec.getMetricWith(labels)
func (v *CounterVec) GetMetricWith(labels Labels) (Counter, error) {
metric, err := v.MetricVec.GetMetricWith(labels)
if metric != nil {
return metric.(Counter), err
}
......@@ -148,18 +243,57 @@ func (m *CounterVec) GetMetricWith(labels Labels) (Counter, error) {
}
// WithLabelValues works as GetMetricWithLabelValues, but panics where
// GetMetricWithLabelValues would have returned an error. By not returning an
// error, WithLabelValues allows shortcuts like
// GetMetricWithLabelValues would have returned an error. Not returning an
// error allows shortcuts like
// myVec.WithLabelValues("404", "GET").Add(42)
func (m *CounterVec) WithLabelValues(lvs ...string) Counter {
return m.metricVec.withLabelValues(lvs...).(Counter)
func (v *CounterVec) WithLabelValues(lvs ...string) Counter {
c, err := v.GetMetricWithLabelValues(lvs...)
if err != nil {
panic(err)
}
return c
}
// 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 (m *CounterVec) With(labels Labels) Counter {
return m.metricVec.with(labels).(Counter)
// returned an error. Not returning an error allows shortcuts like
// myVec.With(prometheus.Labels{"code": "404", "method": "GET"}).Add(42)
func (v *CounterVec) With(labels Labels) Counter {
c, err := v.GetMetricWith(labels)
if err != nil {
panic(err)
}
return c
}
// CurryWith returns a vector curried with the provided labels, i.e. the
// returned vector has those labels pre-set for all labeled operations performed
// on it. The cardinality of the curried vector is reduced accordingly. The
// order of the remaining labels stays the same (just with the curried labels
// taken out of the sequence – which is relevant for the
// (GetMetric)WithLabelValues methods). It is possible to curry a curried
// vector, but only with labels not yet used for currying before.
//
// The metrics contained in the CounterVec are shared between the curried and
// uncurried vectors. They are just accessed differently. Curried and uncurried
// vectors behave identically in terms of collection. Only one must be
// registered with a given registry (usually the uncurried version). The Reset
// method deletes all metrics, even if called on a curried vector.
func (v *CounterVec) CurryWith(labels Labels) (*CounterVec, error) {
vec, err := v.MetricVec.CurryWith(labels)
if vec != nil {
return &CounterVec{vec}, err
}
return nil, err
}
// MustCurryWith works as CurryWith but panics where CurryWith would have
// returned an error.
func (v *CounterVec) MustCurryWith(labels Labels) *CounterVec {
vec, err := v.CurryWith(labels)
if err != nil {
panic(err)
}
return vec
}
// CounterFunc is a Counter whose value is determined at collect time by calling a
......@@ -179,6 +313,8 @@ type CounterFunc interface {
// 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.
//
// Check out the ExampleGaugeFunc examples for the similar GaugeFunc.
func NewCounterFunc(opts CounterOpts, function func() float64) CounterFunc {
return newValueFunc(NewDesc(
BuildFQName(opts.Namespace, opts.Subsystem, opts.Name),
......
......@@ -19,6 +19,8 @@ import (
"sort"
"strings"
"github.com/cespare/xxhash/v2"
//nolint:staticcheck // Ignore SA1019. Need to keep deprecated package for compatibility.
"github.com/golang/protobuf/proto"
"github.com/prometheus/common/model"
......@@ -49,7 +51,7 @@ type Desc struct {
// constLabelPairs contains precalculated DTO label pairs based on
// the constant labels.
constLabelPairs []*dto.LabelPair
// VariableLabels contains names of labels for which the metric
// variableLabels contains names of labels for which the metric
// maintains variable values.
variableLabels []string
// id is a hash of the values of the ConstLabels and fqName. This
......@@ -67,24 +69,19 @@ type Desc struct {
// 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.
// be nil if no such labels should be set. fqName 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.
// specified in the Desc. See the Collector example for a usage pattern.
func NewDesc(fqName, help string, variableLabels []string, constLabels Labels) *Desc {
d := &Desc{
fqName: fqName,
help: help,
variableLabels: variableLabels,
}
if help == "" {
d.err = errors.New("empty help string")
return d
}
if !model.IsValidMetricName(model.LabelValue(fqName)) {
d.err = fmt.Errorf("%q is not a valid metric name", fqName)
return d
......@@ -98,7 +95,7 @@ func NewDesc(fqName, help string, variableLabels []string, constLabels Labels) *
// First add only the const label names and sort them...
for labelName := range constLabels {
if !checkLabelName(labelName) {
d.err = fmt.Errorf("%q is not a valid label name", labelName)
d.err = fmt.Errorf("%q is not a valid label name for metric %q", labelName, fqName)
return d
}
labelNames = append(labelNames, labelName)
......@@ -120,7 +117,7 @@ func NewDesc(fqName, help string, variableLabels []string, constLabels Labels) *
// dimension with a different mix between preset and variable labels.
for _, labelName := range variableLabels {
if !checkLabelName(labelName) {
d.err = fmt.Errorf("%q is not a valid label name", labelName)
d.err = fmt.Errorf("%q is not a valid label name for metric %q", labelName, fqName)
return d
}
labelNames = append(labelNames, "$"+labelName)
......@@ -131,24 +128,24 @@ func NewDesc(fqName, help string, variableLabels []string, constLabels Labels) *
return d
}
vh := hashNew()
xxh := xxhash.New()
for _, val := range labelValues {
vh = hashAdd(vh, val)
vh = hashAddByte(vh, separatorByte)
xxh.WriteString(val)
xxh.Write(separatorByteSlice)
}
d.id = vh
d.id = xxh.Sum64()
// Sort labelNames so that order doesn't matter for the hash.
sort.Strings(labelNames)
// Now hash together (in this order) the help string and the sorted
// label names.
lh := hashNew()
lh = hashAdd(lh, help)
lh = hashAddByte(lh, separatorByte)
xxh.Reset()
xxh.WriteString(help)
xxh.Write(separatorByteSlice)
for _, labelName := range labelNames {
lh = hashAdd(lh, labelName)
lh = hashAddByte(lh, separatorByte)
xxh.WriteString(labelName)
xxh.Write(separatorByteSlice)
}
d.dimHash = lh
d.dimHash = xxh.Sum64()
d.constLabelPairs = make([]*dto.LabelPair, 0, len(constLabels))
for n, v := range constLabels {
......@@ -157,7 +154,7 @@ func NewDesc(fqName, help string, variableLabels []string, constLabels Labels) *
Value: proto.String(v),
})
}
sort.Sort(LabelPairSorter(d.constLabelPairs))
sort.Sort(labelPairSorter(d.constLabelPairs))
return d
}
......
......@@ -11,10 +11,12 @@
// See the License for the specific language governing permissions and
// limitations under the License.
// 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).
// Package prometheus is the core instrumentation package. It 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). There is
// also a sub-package promauto, which provides metrics constructors with
// automatic registration.
//
// All exported functions and methods are safe to be used concurrently unless
// specified otherwise.
......@@ -72,32 +74,31 @@
// 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.
// vector versions for basic usage. Furthermore, if you are not concerned with
// fine-grained control of when and how to register metrics with the registry,
// have a look at the promauto package, which will effectively allow you to
// ignore registration altogether in simple cases.
//
// 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
// In addition to the fundamental metric types Gauge, Counter, Summary, and
// Histogram, 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.
// and HistogramVec.
//
// 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.
// a Metric can also “collect itself”. Note that Gauge, Counter, Summary, and
// Histogram are interfaces themselves while GaugeVec, CounterVec, SummaryVec,
// and HistogramVec 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.
// …Opts struct, i.e. GaugeOpts, CounterOpts, SummaryOpts, or HistogramOpts.
//
// Custom Collectors and constant Metrics
//
......@@ -113,10 +114,23 @@
// 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.
// NewConstSummary (and their respective Must… versions). NewConstMetric is used
// for all metric types with just a float64 as their value: Counter, Gauge, and
// a special “type” called Untyped. Use the latter if you are not sure if the
// mirrored metric is a Counter or a Gauge. Creation of the Metric instance
// happens 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. Alternatively,
// you could return no Desc at all, which will mark the Collector “unchecked”.
// No checks are performed at registration time, but metric consistency will
// still be ensured at scrape time, i.e. any inconsistencies will lead to scrape
// errors. Thus, with unchecked Collectors, the responsibility to not collect
// metrics that lead to inconsistencies in the total scrape result lies with the
// implementer of the Collector. While this is not a desirable state, it is
// sometimes necessary. The typical use case is a situation where the exact
// metrics to be returned by a Collector cannot be predicted at registration
// time, but the implementer has sufficient knowledge of the whole system to
// guarantee metric consistency.
//
// The Collector example illustrates the use case. You can also look at the
// source code of the processCollector (mirroring process metrics), the
......@@ -168,7 +182,6 @@
// 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
//
......
......@@ -22,43 +22,10 @@ type expvarCollector struct {
exports map[string]*Desc
}
// NewExpvarCollector returns a newly allocated expvar Collector that still has
// to be registered with a Prometheus registry.
// NewExpvarCollector is the obsolete version of collectors.NewExpvarCollector.
// See there for documentation.
//
// 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.
// Deprecated: Use collectors.NewExpvarCollector instead.
func NewExpvarCollector(exports map[string]*Desc) Collector {
return &expvarCollector{
exports: exports,
......
// Copyright 2018 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package prometheus
// Inline and byte-free variant of hash/fnv's fnv64a.
......
......@@ -13,6 +13,14 @@
package prometheus
import (
"math"
"sync/atomic"
"time"
dto "github.com/prometheus/client_model/go"
)
// Gauge is a Metric that represents a single numerical value that can
// arbitrarily go up and down.
//
......@@ -48,13 +56,74 @@ type Gauge interface {
type GaugeOpts Opts
// NewGauge creates a new Gauge based on the provided GaugeOpts.
//
// The returned implementation is optimized for a fast Set method. If you have a
// choice for managing the value of a Gauge via Set vs. Inc/Dec/Add/Sub, pick
// the former. For example, the Inc method of the returned Gauge is slower than
// the Inc method of a Counter returned by NewCounter. This matches the typical
// scenarios for Gauges and Counters, where the former tends to be Set-heavy and
// the latter Inc-heavy.
func NewGauge(opts GaugeOpts) Gauge {
return newValue(NewDesc(
desc := NewDesc(
BuildFQName(opts.Namespace, opts.Subsystem, opts.Name),
opts.Help,
nil,
opts.ConstLabels,
), GaugeValue, 0)
)
result := &gauge{desc: desc, labelPairs: desc.constLabelPairs}
result.init(result) // Init self-collection.
return result
}
type gauge struct {
// valBits contains the bits of the represented float64 value. It has
// to go first in the struct to guarantee alignment for atomic
// operations. http://golang.org/pkg/sync/atomic/#pkg-note-BUG
valBits uint64
selfCollector
desc *Desc
labelPairs []*dto.LabelPair
}
func (g *gauge) Desc() *Desc {
return g.desc
}
func (g *gauge) Set(val float64) {
atomic.StoreUint64(&g.valBits, math.Float64bits(val))
}
func (g *gauge) SetToCurrentTime() {
g.Set(float64(time.Now().UnixNano()) / 1e9)
}
func (g *gauge) Inc() {
g.Add(1)
}
func (g *gauge) Dec() {
g.Add(-1)
}
func (g *gauge) Add(val float64) {
for {
oldBits := atomic.LoadUint64(&g.valBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + val)
if atomic.CompareAndSwapUint64(&g.valBits, oldBits, newBits) {
return
}
}
}
func (g *gauge) Sub(val float64) {
g.Add(val * -1)
}
func (g *gauge) Write(out *dto.Metric) error {
val := math.Float64frombits(atomic.LoadUint64(&g.valBits))
return populateMetric(GaugeValue, val, g.labelPairs, nil, out)
}
// GaugeVec is a Collector that bundles a set of Gauges that all share the same
......@@ -63,7 +132,7 @@ func NewGauge(opts GaugeOpts) Gauge {
// (e.g. number of operations queued, partitioned by user and operation
// type). Create instances with NewGaugeVec.
type GaugeVec struct {
*metricVec
*MetricVec
}
// NewGaugeVec creates a new GaugeVec based on the provided GaugeOpts and
......@@ -76,14 +145,19 @@ func NewGaugeVec(opts GaugeOpts, labelNames []string) *GaugeVec {
opts.ConstLabels,
)
return &GaugeVec{
metricVec: newMetricVec(desc, func(lvs ...string) Metric {
return newValue(desc, GaugeValue, 0, lvs...)
MetricVec: NewMetricVec(desc, func(lvs ...string) Metric {
if len(lvs) != len(desc.variableLabels) {
panic(makeInconsistentCardinalityError(desc.fqName, desc.variableLabels, lvs))
}
result := &gauge{desc: desc, labelPairs: MakeLabelPairs(desc, lvs)}
result.init(result) // Init self-collection.
return result
}),
}
}
// GetMetricWithLabelValues returns the Gauge for the given slice of label
// values (same order as the VariableLabels in Desc). If that combination of
// values (same order as the variable labels 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
......@@ -98,15 +172,15 @@ func NewGaugeVec(opts GaugeOpts, labelNames []string) *GaugeVec {
// example.
//
// An error is returned if the number of label values is not the same as the
// number of VariableLabels in Desc.
// number of variable labels in Desc (minus any curried labels).
//
// 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 (m *GaugeVec) GetMetricWithLabelValues(lvs ...string) (Gauge, error) {
metric, err := m.metricVec.getMetricWithLabelValues(lvs...)
func (v *GaugeVec) GetMetricWithLabelValues(lvs ...string) (Gauge, error) {
metric, err := v.MetricVec.GetMetricWithLabelValues(lvs...)
if metric != nil {
return metric.(Gauge), err
}
......@@ -114,19 +188,19 @@ func (m *GaugeVec) GetMetricWithLabelValues(lvs ...string) (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
// must match those of the variable labels 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.
// with those of the variable labels in Desc (minus any curried labels).
//
// This method is used for the same purpose as
// GetMetricWithLabelValues(...string). See there for pros and cons of the two
// methods.
func (m *GaugeVec) GetMetricWith(labels Labels) (Gauge, error) {
metric, err := m.metricVec.getMetricWith(labels)
func (v *GaugeVec) GetMetricWith(labels Labels) (Gauge, error) {
metric, err := v.MetricVec.GetMetricWith(labels)
if metric != nil {
return metric.(Gauge), err
}
......@@ -134,18 +208,57 @@ func (m *GaugeVec) GetMetricWith(labels Labels) (Gauge, error) {
}
// WithLabelValues works as GetMetricWithLabelValues, but panics where
// GetMetricWithLabelValues would have returned an error. By not returning an
// error, WithLabelValues allows shortcuts like
// GetMetricWithLabelValues would have returned an error. Not returning an
// error allows shortcuts like
// myVec.WithLabelValues("404", "GET").Add(42)
func (m *GaugeVec) WithLabelValues(lvs ...string) Gauge {
return m.metricVec.withLabelValues(lvs...).(Gauge)
func (v *GaugeVec) WithLabelValues(lvs ...string) Gauge {
g, err := v.GetMetricWithLabelValues(lvs...)
if err != nil {
panic(err)
}
return g
}
// 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 (m *GaugeVec) With(labels Labels) Gauge {
return m.metricVec.with(labels).(Gauge)
// returned an error. Not returning an error allows shortcuts like
// myVec.With(prometheus.Labels{"code": "404", "method": "GET"}).Add(42)
func (v *GaugeVec) With(labels Labels) Gauge {
g, err := v.GetMetricWith(labels)
if err != nil {
panic(err)
}
return g
}
// CurryWith returns a vector curried with the provided labels, i.e. the
// returned vector has those labels pre-set for all labeled operations performed
// on it. The cardinality of the curried vector is reduced accordingly. The
// order of the remaining labels stays the same (just with the curried labels
// taken out of the sequence – which is relevant for the
// (GetMetric)WithLabelValues methods). It is possible to curry a curried
// vector, but only with labels not yet used for currying before.
//
// The metrics contained in the GaugeVec are shared between the curried and
// uncurried vectors. They are just accessed differently. Curried and uncurried
// vectors behave identically in terms of collection. Only one must be
// registered with a given registry (usually the uncurried version). The Reset
// method deletes all metrics, even if called on a curried vector.
func (v *GaugeVec) CurryWith(labels Labels) (*GaugeVec, error) {
vec, err := v.MetricVec.CurryWith(labels)
if vec != nil {
return &GaugeVec{vec}, err
}
return nil, err
}
// MustCurryWith works as CurryWith but panics where CurryWith would have
// returned an error.
func (v *GaugeVec) MustCurryWith(labels Labels) *GaugeVec {
vec, err := v.CurryWith(labels)
if err != nil {
panic(err)
}
return vec
}
// GaugeFunc is a Gauge whose value is determined at collect time by calling a
......@@ -160,9 +273,12 @@ type GaugeFunc interface {
// 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.
// concurrently. Therefore, it must be safe to call the provided function
// concurrently.
//
// NewGaugeFunc is a good way to create an “info” style metric with a constant
// value of 1. Example:
// https://github.com/prometheus/common/blob/8558a5b7db3c84fa38b4766966059a7bd5bfa2ee/version/info.go#L36-L56
func NewGaugeFunc(opts GaugeOpts, function func() float64) GaugeFunc {
return newValueFunc(NewDesc(
BuildFQName(opts.Namespace, opts.Subsystem, opts.Name),
......
// Copyright 2018 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package prometheus
import (
"fmt"
"runtime"
"runtime/debug"
"time"
)
type goCollector struct {
goroutinesDesc *Desc
threadsDesc *Desc
gcDesc *Desc
goInfoDesc *Desc
// metrics to describe and collect
metrics memStatsMetrics
}
// NewGoCollector returns a collector which exports metrics about the current
// go process.
func NewGoCollector() Collector {
return &goCollector{
goroutinesDesc: NewDesc(
"go_goroutines",
"Number of goroutines that currently exist.",
nil, nil),
threadsDesc: NewDesc(
"go_threads",
"Number of OS threads created.",
nil, nil),
gcDesc: NewDesc(
"go_gc_duration_seconds",
"A summary of the GC invocation durations.",
nil, nil),
goInfoDesc: NewDesc(
"go_info",
"Information about the Go environment.",
nil, Labels{"version": runtime.Version()}),
metrics: memStatsMetrics{
func goRuntimeMemStats() memStatsMetrics {
return memStatsMetrics{
{
desc: NewDesc(
memstatNamespace("alloc_bytes"),
......@@ -214,44 +197,54 @@ func NewGoCollector() Collector {
),
eval: func(ms *runtime.MemStats) float64 { return float64(ms.NextGC) },
valType: GaugeValue,
}, {
desc: NewDesc(
memstatNamespace("last_gc_time_seconds"),
"Number of seconds since 1970 of last garbage collection.",
nil, nil,
),
eval: func(ms *runtime.MemStats) float64 { return float64(ms.LastGC) / 1e9 },
valType: GaugeValue,
}, {
desc: NewDesc(
memstatNamespace("gc_cpu_fraction"),
"The fraction of this program's available CPU time used by the GC since the program started.",
nil, nil,
),
eval: func(ms *runtime.MemStats) float64 { return ms.GCCPUFraction },
valType: GaugeValue,
},
},
}
}
func memstatNamespace(s string) string {
return fmt.Sprintf("go_memstats_%s", s)
type baseGoCollector struct {
goroutinesDesc *Desc
threadsDesc *Desc
gcDesc *Desc
gcLastTimeDesc *Desc
goInfoDesc *Desc
}
func newBaseGoCollector() baseGoCollector {
return baseGoCollector{
goroutinesDesc: NewDesc(
"go_goroutines",
"Number of goroutines that currently exist.",
nil, nil),
threadsDesc: NewDesc(
"go_threads",
"Number of OS threads created.",
nil, nil),
gcDesc: NewDesc(
"go_gc_duration_seconds",
"A summary of the pause duration of garbage collection cycles.",
nil, nil),
gcLastTimeDesc: NewDesc(
memstatNamespace("last_gc_time_seconds"),
"Number of seconds since 1970 of last garbage collection.",
nil, nil),
goInfoDesc: NewDesc(
"go_info",
"Information about the Go environment.",
nil, Labels{"version": runtime.Version()}),
}
}
// Describe returns all descriptions of the collector.
func (c *goCollector) Describe(ch chan<- *Desc) {
func (c *baseGoCollector) Describe(ch chan<- *Desc) {
ch <- c.goroutinesDesc
ch <- c.threadsDesc
ch <- c.gcDesc
ch <- c.gcLastTimeDesc
ch <- c.goInfoDesc
for _, i := range c.metrics {
ch <- i.desc
}
}
// Collect returns the current state of all metrics of the collector.
func (c *goCollector) Collect(ch chan<- Metric) {
func (c *baseGoCollector) Collect(ch chan<- Metric) {
ch <- MustNewConstMetric(c.goroutinesDesc, GaugeValue, float64(runtime.NumGoroutine()))
n, _ := runtime.ThreadCreateProfile(nil)
ch <- MustNewConstMetric(c.threadsDesc, GaugeValue, float64(n))
......@@ -265,18 +258,18 @@ func (c *goCollector) Collect(ch chan<- Metric) {
quantiles[float64(idx+1)/float64(len(stats.PauseQuantiles)-1)] = pq.Seconds()
}
quantiles[0.0] = stats.PauseQuantiles[0].Seconds()
ch <- MustNewConstSummary(c.gcDesc, uint64(stats.NumGC), float64(stats.PauseTotal.Seconds()), quantiles)
ch <- MustNewConstSummary(c.gcDesc, uint64(stats.NumGC), stats.PauseTotal.Seconds(), quantiles)
ch <- MustNewConstMetric(c.gcLastTimeDesc, GaugeValue, float64(stats.LastGC.UnixNano())/1e9)
ch <- MustNewConstMetric(c.goInfoDesc, GaugeValue, 1)
ms := &runtime.MemStats{}
runtime.ReadMemStats(ms)
for _, i := range c.metrics {
ch <- MustNewConstMetric(i.desc, i.valType, i.eval(ms))
}
func memstatNamespace(s string) string {
return "go_memstats_" + s
}
// memStatsMetrics provide description, value, and value type for memstat metrics.
// memStatsMetrics provide description, evaluator, runtime/metrics name, and
// value type for memstat metrics.
// TODO(bwplotka): Remove with end Go 1.16 EOL and replace with runtime/metrics.Description
type memStatsMetrics []struct {
desc *Desc
eval func(*runtime.MemStats) float64
......
// Copyright 2021 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//go:build !go1.17
// +build !go1.17
package prometheus
import (
"runtime"
"sync"
"time"
)
type goCollector struct {
base baseGoCollector
// ms... are memstats related.
msLast *runtime.MemStats // Previously collected memstats.
msLastTimestamp time.Time
msMtx sync.Mutex // Protects msLast and msLastTimestamp.
msMetrics memStatsMetrics
msRead func(*runtime.MemStats) // For mocking in tests.
msMaxWait time.Duration // Wait time for fresh memstats.
msMaxAge time.Duration // Maximum allowed age of old memstats.
}
// NewGoCollector is the obsolete version of collectors.NewGoCollector.
// See there for documentation.
//
// Deprecated: Use collectors.NewGoCollector instead.
func NewGoCollector() Collector {
msMetrics := goRuntimeMemStats()
msMetrics = append(msMetrics, struct {
desc *Desc
eval func(*runtime.MemStats) float64
valType ValueType
}{
// This metric is omitted in Go1.17+, see https://github.com/prometheus/client_golang/issues/842#issuecomment-861812034
desc: NewDesc(
memstatNamespace("gc_cpu_fraction"),
"The fraction of this program's available CPU time used by the GC since the program started.",
nil, nil,
),
eval: func(ms *runtime.MemStats) float64 { return ms.GCCPUFraction },
valType: GaugeValue,
})
return &goCollector{
base: newBaseGoCollector(),
msLast: &runtime.MemStats{},
msRead: runtime.ReadMemStats,
msMaxWait: time.Second,
msMaxAge: 5 * time.Minute,
msMetrics: msMetrics,
}
}
// Describe returns all descriptions of the collector.
func (c *goCollector) Describe(ch chan<- *Desc) {
c.base.Describe(ch)
for _, i := range c.msMetrics {
ch <- i.desc
}
}
// Collect returns the current state of all metrics of the collector.
func (c *goCollector) Collect(ch chan<- Metric) {
var (
ms = &runtime.MemStats{}
done = make(chan struct{})
)
// Start reading memstats first as it might take a while.
go func() {
c.msRead(ms)
c.msMtx.Lock()
c.msLast = ms
c.msLastTimestamp = time.Now()
c.msMtx.Unlock()
close(done)
}()
// Collect base non-memory metrics.
c.base.Collect(ch)
timer := time.NewTimer(c.msMaxWait)
select {
case <-done: // Our own ReadMemStats succeeded in time. Use it.
timer.Stop() // Important for high collection frequencies to not pile up timers.
c.msCollect(ch, ms)
return
case <-timer.C: // Time out, use last memstats if possible. Continue below.
}
c.msMtx.Lock()
if time.Since(c.msLastTimestamp) < c.msMaxAge {
// Last memstats are recent enough. Collect from them under the lock.
c.msCollect(ch, c.msLast)
c.msMtx.Unlock()
return
}
// If we are here, the last memstats are too old or don't exist. We have
// to wait until our own ReadMemStats finally completes. For that to
// happen, we have to release the lock.
c.msMtx.Unlock()
<-done
c.msCollect(ch, ms)
}
func (c *goCollector) msCollect(ch chan<- Metric, ms *runtime.MemStats) {
for _, i := range c.msMetrics {
ch <- MustNewConstMetric(i.desc, i.valType, i.eval(ms))
}
}
// Copyright 2021 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//go:build go1.17
// +build go1.17
package prometheus
import (
"math"
"runtime"
"runtime/metrics"
"strings"
"sync"
//nolint:staticcheck // Ignore SA1019. Need to keep deprecated package for compatibility.
"github.com/golang/protobuf/proto"
dto "github.com/prometheus/client_model/go"
"github.com/prometheus/client_golang/prometheus/internal"
)
const (
goGCHeapTinyAllocsObjects = "/gc/heap/tiny/allocs:objects"
goGCHeapAllocsObjects = "/gc/heap/allocs:objects"
goGCHeapFreesObjects = "/gc/heap/frees:objects"
goGCHeapAllocsBytes = "/gc/heap/allocs:bytes"
goGCHeapObjects = "/gc/heap/objects:objects"
goGCHeapGoalBytes = "/gc/heap/goal:bytes"
goMemoryClassesTotalBytes = "/memory/classes/total:bytes"
goMemoryClassesHeapObjectsBytes = "/memory/classes/heap/objects:bytes"
goMemoryClassesHeapUnusedBytes = "/memory/classes/heap/unused:bytes"
goMemoryClassesHeapReleasedBytes = "/memory/classes/heap/released:bytes"
goMemoryClassesHeapFreeBytes = "/memory/classes/heap/free:bytes"
goMemoryClassesHeapStacksBytes = "/memory/classes/heap/stacks:bytes"
goMemoryClassesOSStacksBytes = "/memory/classes/os-stacks:bytes"
goMemoryClassesMetadataMSpanInuseBytes = "/memory/classes/metadata/mspan/inuse:bytes"
goMemoryClassesMetadataMSPanFreeBytes = "/memory/classes/metadata/mspan/free:bytes"
goMemoryClassesMetadataMCacheInuseBytes = "/memory/classes/metadata/mcache/inuse:bytes"
goMemoryClassesMetadataMCacheFreeBytes = "/memory/classes/metadata/mcache/free:bytes"
goMemoryClassesProfilingBucketsBytes = "/memory/classes/profiling/buckets:bytes"
goMemoryClassesMetadataOtherBytes = "/memory/classes/metadata/other:bytes"
goMemoryClassesOtherBytes = "/memory/classes/other:bytes"
)
// runtime/metrics names required for runtimeMemStats like logic.
var rmForMemStats = []string{goGCHeapTinyAllocsObjects,
goGCHeapAllocsObjects,
goGCHeapFreesObjects,
goGCHeapAllocsBytes,
goGCHeapObjects,
goGCHeapGoalBytes,
goMemoryClassesTotalBytes,
goMemoryClassesHeapObjectsBytes,
goMemoryClassesHeapUnusedBytes,
goMemoryClassesHeapReleasedBytes,
goMemoryClassesHeapFreeBytes,
goMemoryClassesHeapStacksBytes,
goMemoryClassesOSStacksBytes,
goMemoryClassesMetadataMSpanInuseBytes,
goMemoryClassesMetadataMSPanFreeBytes,
goMemoryClassesMetadataMCacheInuseBytes,
goMemoryClassesMetadataMCacheFreeBytes,
goMemoryClassesProfilingBucketsBytes,
goMemoryClassesMetadataOtherBytes,
goMemoryClassesOtherBytes,
}
func bestEffortLookupRM(lookup []string) []metrics.Description {
ret := make([]metrics.Description, 0, len(lookup))
for _, rm := range metrics.All() {
for _, m := range lookup {
if m == rm.Name {
ret = append(ret, rm)
}
}
}
return ret
}
type goCollector struct {
opt GoCollectorOptions
base baseGoCollector
// mu protects updates to all fields ensuring a consistent
// snapshot is always produced by Collect.
mu sync.Mutex
// rm... fields all pertain to the runtime/metrics package.
rmSampleBuf []metrics.Sample
rmSampleMap map[string]*metrics.Sample
rmMetrics []collectorMetric
// With Go 1.17, the runtime/metrics package was introduced.
// From that point on, metric names produced by the runtime/metrics
// package could be generated from runtime/metrics names. However,
// these differ from the old names for the same values.
//
// This field exist to export the same values under the old names
// as well.
msMetrics memStatsMetrics
}
const (
// Those are not exposed due to need to move Go collector to another package in v2.
// See issue https://github.com/prometheus/client_golang/issues/1030.
goRuntimeMemStatsCollection uint32 = 1 << iota
goRuntimeMetricsCollection
)
// GoCollectorOptions should not be used be directly by anything, except `collectors` package.
// Use it via collectors package instead. See issue
// https://github.com/prometheus/client_golang/issues/1030.
//
// Deprecated: Use collectors.WithGoCollections
type GoCollectorOptions struct {
// EnabledCollection sets what type of collections collector should expose on top of base collection.
// By default it's goMemStatsCollection | goRuntimeMetricsCollection.
EnabledCollections uint32
}
func (c GoCollectorOptions) isEnabled(flag uint32) bool {
return c.EnabledCollections&flag != 0
}
const defaultGoCollections = goRuntimeMemStatsCollection
// NewGoCollector is the obsolete version of collectors.NewGoCollector.
// See there for documentation.
//
// Deprecated: Use collectors.NewGoCollector instead.
func NewGoCollector(opts ...func(o *GoCollectorOptions)) Collector {
opt := GoCollectorOptions{EnabledCollections: defaultGoCollections}
for _, o := range opts {
o(&opt)
}
var descriptions []metrics.Description
if opt.isEnabled(goRuntimeMetricsCollection) {
descriptions = metrics.All()
} else if opt.isEnabled(goRuntimeMemStatsCollection) {
descriptions = bestEffortLookupRM(rmForMemStats)
}
// Collect all histogram samples so that we can get their buckets.
// The API guarantees that the buckets are always fixed for the lifetime
// of the process.
var histograms []metrics.Sample
for _, d := range descriptions {
if d.Kind == metrics.KindFloat64Histogram {
histograms = append(histograms, metrics.Sample{Name: d.Name})
}
}
if len(histograms) > 0 {
metrics.Read(histograms)
}
bucketsMap := make(map[string][]float64)
for i := range histograms {
bucketsMap[histograms[i].Name] = histograms[i].Value.Float64Histogram().Buckets
}
// Generate a Desc and ValueType for each runtime/metrics metric.
metricSet := make([]collectorMetric, 0, len(descriptions))
sampleBuf := make([]metrics.Sample, 0, len(descriptions))
sampleMap := make(map[string]*metrics.Sample, len(descriptions))
for i := range descriptions {
d := &descriptions[i]
namespace, subsystem, name, ok := internal.RuntimeMetricsToProm(d)
if !ok {
// Just ignore this metric; we can't do anything with it here.
// If a user decides to use the latest version of Go, we don't want
// to fail here. This condition is tested in TestExpectedRuntimeMetrics.
continue
}
// Set up sample buffer for reading, and a map
// for quick lookup of sample values.
sampleBuf = append(sampleBuf, metrics.Sample{Name: d.Name})
sampleMap[d.Name] = &sampleBuf[len(sampleBuf)-1]
var m collectorMetric
if d.Kind == metrics.KindFloat64Histogram {
_, hasSum := rmExactSumMap[d.Name]
unit := d.Name[strings.IndexRune(d.Name, ':')+1:]
m = newBatchHistogram(
NewDesc(
BuildFQName(namespace, subsystem, name),
d.Description,
nil,
nil,
),
internal.RuntimeMetricsBucketsForUnit(bucketsMap[d.Name], unit),
hasSum,
)
} else if d.Cumulative {
m = NewCounter(CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: name,
Help: d.Description,
})
} else {
m = NewGauge(GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: name,
Help: d.Description,
})
}
metricSet = append(metricSet, m)
}
var msMetrics memStatsMetrics
if opt.isEnabled(goRuntimeMemStatsCollection) {
msMetrics = goRuntimeMemStats()
}
return &goCollector{
opt: opt,
base: newBaseGoCollector(),
rmSampleBuf: sampleBuf,
rmSampleMap: sampleMap,
rmMetrics: metricSet,
msMetrics: msMetrics,
}
}
// Describe returns all descriptions of the collector.
func (c *goCollector) Describe(ch chan<- *Desc) {
c.base.Describe(ch)
for _, i := range c.msMetrics {
ch <- i.desc
}
for _, m := range c.rmMetrics {
ch <- m.Desc()
}
}
// Collect returns the current state of all metrics of the collector.
func (c *goCollector) Collect(ch chan<- Metric) {
// Collect base non-memory metrics.
c.base.Collect(ch)
// Collect must be thread-safe, so prevent concurrent use of
// rmSampleBuf. Just read into rmSampleBuf but write all the data
// we get into our Metrics or MemStats.
//
// This lock also ensures that the Metrics we send out are all from
// the same updates, ensuring their mutual consistency insofar as
// is guaranteed by the runtime/metrics package.
//
// N.B. This locking is heavy-handed, but Collect is expected to be called
// relatively infrequently. Also the core operation here, metrics.Read,
// is fast (O(tens of microseconds)) so contention should certainly be
// low, though channel operations and any allocations may add to that.
c.mu.Lock()
defer c.mu.Unlock()
if len(c.rmSampleBuf) > 0 {
// Populate runtime/metrics sample buffer.
metrics.Read(c.rmSampleBuf)
}
if c.opt.isEnabled(goRuntimeMetricsCollection) {
// Collect all our metrics from rmSampleBuf.
for i, sample := range c.rmSampleBuf {
// N.B. switch on concrete type because it's significantly more efficient
// than checking for the Counter and Gauge interface implementations. In
// this case, we control all the types here.
switch m := c.rmMetrics[i].(type) {
case *counter:
// Guard against decreases. This should never happen, but a failure
// to do so will result in a panic, which is a harsh consequence for
// a metrics collection bug.
v0, v1 := m.get(), unwrapScalarRMValue(sample.Value)
if v1 > v0 {
m.Add(unwrapScalarRMValue(sample.Value) - m.get())
}
m.Collect(ch)
case *gauge:
m.Set(unwrapScalarRMValue(sample.Value))
m.Collect(ch)
case *batchHistogram:
m.update(sample.Value.Float64Histogram(), c.exactSumFor(sample.Name))
m.Collect(ch)
default:
panic("unexpected metric type")
}
}
}
// ms is a dummy MemStats that we populate ourselves so that we can
// populate the old metrics from it if goMemStatsCollection is enabled.
if c.opt.isEnabled(goRuntimeMemStatsCollection) {
var ms runtime.MemStats
memStatsFromRM(&ms, c.rmSampleMap)
for _, i := range c.msMetrics {
ch <- MustNewConstMetric(i.desc, i.valType, i.eval(&ms))
}
}
}
// unwrapScalarRMValue unwraps a runtime/metrics value that is assumed
// to be scalar and returns the equivalent float64 value. Panics if the
// value is not scalar.
func unwrapScalarRMValue(v metrics.Value) float64 {
switch v.Kind() {
case metrics.KindUint64:
return float64(v.Uint64())
case metrics.KindFloat64:
return v.Float64()
case metrics.KindBad:
// Unsupported metric.
//
// This should never happen because we always populate our metric
// set from the runtime/metrics package.
panic("unexpected unsupported metric")
default:
// Unsupported metric kind.
//
// This should never happen because we check for this during initialization
// and flag and filter metrics whose kinds we don't understand.
panic("unexpected unsupported metric kind")
}
}
var rmExactSumMap = map[string]string{
"/gc/heap/allocs-by-size:bytes": "/gc/heap/allocs:bytes",
"/gc/heap/frees-by-size:bytes": "/gc/heap/frees:bytes",
}
// exactSumFor takes a runtime/metrics metric name (that is assumed to
// be of kind KindFloat64Histogram) and returns its exact sum and whether
// its exact sum exists.
//
// The runtime/metrics API for histograms doesn't currently expose exact
// sums, but some of the other metrics are in fact exact sums of histograms.
func (c *goCollector) exactSumFor(rmName string) float64 {
sumName, ok := rmExactSumMap[rmName]
if !ok {
return 0
}
s, ok := c.rmSampleMap[sumName]
if !ok {
return 0
}
return unwrapScalarRMValue(s.Value)
}
func memStatsFromRM(ms *runtime.MemStats, rm map[string]*metrics.Sample) {
lookupOrZero := func(name string) uint64 {
if s, ok := rm[name]; ok {
return s.Value.Uint64()
}
return 0
}
// Currently, MemStats adds tiny alloc count to both Mallocs AND Frees.
// The reason for this is because MemStats couldn't be extended at the time
// but there was a desire to have Mallocs at least be a little more representative,
// while having Mallocs - Frees still represent a live object count.
// Unfortunately, MemStats doesn't actually export a large allocation count,
// so it's impossible to pull this number out directly.
tinyAllocs := lookupOrZero(goGCHeapTinyAllocsObjects)
ms.Mallocs = lookupOrZero(goGCHeapAllocsObjects) + tinyAllocs
ms.Frees = lookupOrZero(goGCHeapFreesObjects) + tinyAllocs
ms.TotalAlloc = lookupOrZero(goGCHeapAllocsBytes)
ms.Sys = lookupOrZero(goMemoryClassesTotalBytes)
ms.Lookups = 0 // Already always zero.
ms.HeapAlloc = lookupOrZero(goMemoryClassesHeapObjectsBytes)
ms.Alloc = ms.HeapAlloc
ms.HeapInuse = ms.HeapAlloc + lookupOrZero(goMemoryClassesHeapUnusedBytes)
ms.HeapReleased = lookupOrZero(goMemoryClassesHeapReleasedBytes)
ms.HeapIdle = ms.HeapReleased + lookupOrZero(goMemoryClassesHeapFreeBytes)
ms.HeapSys = ms.HeapInuse + ms.HeapIdle
ms.HeapObjects = lookupOrZero(goGCHeapObjects)
ms.StackInuse = lookupOrZero(goMemoryClassesHeapStacksBytes)
ms.StackSys = ms.StackInuse + lookupOrZero(goMemoryClassesOSStacksBytes)
ms.MSpanInuse = lookupOrZero(goMemoryClassesMetadataMSpanInuseBytes)
ms.MSpanSys = ms.MSpanInuse + lookupOrZero(goMemoryClassesMetadataMSPanFreeBytes)
ms.MCacheInuse = lookupOrZero(goMemoryClassesMetadataMCacheInuseBytes)
ms.MCacheSys = ms.MCacheInuse + lookupOrZero(goMemoryClassesMetadataMCacheFreeBytes)
ms.BuckHashSys = lookupOrZero(goMemoryClassesProfilingBucketsBytes)
ms.GCSys = lookupOrZero(goMemoryClassesMetadataOtherBytes)
ms.OtherSys = lookupOrZero(goMemoryClassesOtherBytes)
ms.NextGC = lookupOrZero(goGCHeapGoalBytes)
// N.B. GCCPUFraction is intentionally omitted. This metric is not useful,
// and often misleading due to the fact that it's an average over the lifetime
// of the process.
// See https://github.com/prometheus/client_golang/issues/842#issuecomment-861812034
// for more details.
ms.GCCPUFraction = 0
}
// batchHistogram is a mutable histogram that is updated
// in batches.
type batchHistogram struct {
selfCollector
// Static fields updated only once.
desc *Desc
hasSum bool
// Because this histogram operates in batches, it just uses a
// single mutex for everything. updates are always serialized
// but Write calls may operate concurrently with updates.
// Contention between these two sources should be rare.
mu sync.Mutex
buckets []float64 // Inclusive lower bounds, like runtime/metrics.
counts []uint64
sum float64 // Used if hasSum is true.
}
// newBatchHistogram creates a new batch histogram value with the given
// Desc, buckets, and whether or not it has an exact sum available.
//
// buckets must always be from the runtime/metrics package, following
// the same conventions.
func newBatchHistogram(desc *Desc, buckets []float64, hasSum bool) *batchHistogram {
// We need to remove -Inf values. runtime/metrics keeps them around.
// But -Inf bucket should not be allowed for prometheus histograms.
if buckets[0] == math.Inf(-1) {
buckets = buckets[1:]
}
h := &batchHistogram{
desc: desc,
buckets: buckets,
// Because buckets follows runtime/metrics conventions, there's
// 1 more value in the buckets list than there are buckets represented,
// because in runtime/metrics, the bucket values represent *boundaries*,
// and non-Inf boundaries are inclusive lower bounds for that bucket.
counts: make([]uint64, len(buckets)-1),
hasSum: hasSum,
}
h.init(h)
return h
}
// update updates the batchHistogram from a runtime/metrics histogram.
//
// sum must be provided if the batchHistogram was created to have an exact sum.
// h.buckets must be a strict subset of his.Buckets.
func (h *batchHistogram) update(his *metrics.Float64Histogram, sum float64) {
counts, buckets := his.Counts, his.Buckets
h.mu.Lock()
defer h.mu.Unlock()
// Clear buckets.
for i := range h.counts {
h.counts[i] = 0
}
// Copy and reduce buckets.
var j int
for i, count := range counts {
h.counts[j] += count
if buckets[i+1] == h.buckets[j+1] {
j++
}
}
if h.hasSum {
h.sum = sum
}
}
func (h *batchHistogram) Desc() *Desc {
return h.desc
}
func (h *batchHistogram) Write(out *dto.Metric) error {
h.mu.Lock()
defer h.mu.Unlock()
sum := float64(0)
if h.hasSum {
sum = h.sum
}
dtoBuckets := make([]*dto.Bucket, 0, len(h.counts))
totalCount := uint64(0)
for i, count := range h.counts {
totalCount += count
if !h.hasSum {
if count != 0 {
// N.B. This computed sum is an underestimate.
sum += h.buckets[i] * float64(count)
}
}
// Skip the +Inf bucket, but only for the bucket list.
// It must still count for sum and totalCount.
if math.IsInf(h.buckets[i+1], 1) {
break
}
// Float64Histogram's upper bound is exclusive, so make it inclusive
// by obtaining the next float64 value down, in order.
upperBound := math.Nextafter(h.buckets[i+1], h.buckets[i])
dtoBuckets = append(dtoBuckets, &dto.Bucket{
CumulativeCount: proto.Uint64(totalCount),
UpperBound: proto.Float64(upperBound),
})
}
out.Histogram = &dto.Histogram{
Bucket: dtoBuckets,
SampleCount: proto.Uint64(totalCount),
SampleSum: proto.Float64(sum),
}
return nil
}
......@@ -16,9 +16,13 @@ package prometheus
import (
"fmt"
"math"
"runtime"
"sort"
"sync"
"sync/atomic"
"time"
//nolint:staticcheck // Ignore SA1019. Need to keep deprecated package for compatibility.
"github.com/golang/protobuf/proto"
dto "github.com/prometheus/client_model/go"
......@@ -43,7 +47,12 @@ type Histogram interface {
Metric
Collector
// Observe adds a single observation to the histogram.
// Observe adds a single observation to the histogram. Observations are
// usually positive or zero. Negative observations are accepted but
// prevent current versions of Prometheus from properly detecting
// counter resets in the sum of observations. See
// https://prometheus.io/docs/practices/histograms/#count-and-sum-of-observations
// for details.
Observe(float64)
}
......@@ -107,9 +116,38 @@ func ExponentialBuckets(start, factor float64, count int) []float64 {
return buckets
}
// ExponentialBucketsRange creates 'count' buckets, where the lowest bucket is
// 'min' and the highest bucket is 'max'. 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 'min' is 0 or negative.
func ExponentialBucketsRange(min, max float64, count int) []float64 {
if count < 1 {
panic("ExponentialBucketsRange count needs a positive count")
}
if min <= 0 {
panic("ExponentialBucketsRange min needs to be greater than 0")
}
// Formula for exponential buckets.
// max = min*growthFactor^(bucketCount-1)
// We know max/min and highest bucket. Solve for growthFactor.
growthFactor := math.Pow(max/min, 1.0/float64(count-1))
// Now that we know growthFactor, solve for each bucket.
buckets := make([]float64, count)
for i := 1; i <= count; i++ {
buckets[i-1] = min * math.Pow(growthFactor, float64(i-1))
}
return buckets
}
// 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.
// mandatory to set Name to a non-empty string. All other fields are optional
// and can safely be left at their zero value, although it is strongly
// encouraged to set a Help string.
type HistogramOpts struct {
// Namespace, Subsystem, and Name are components of the fully-qualified
// name of the Histogram (created by joining these components with
......@@ -120,29 +158,22 @@ type HistogramOpts struct {
Subsystem string
Name string
// Help provides information about this Histogram. Mandatory!
// Help provides information about this Histogram.
//
// 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.
// 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
// 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 are only used rarely. In particular, do not use them to
// attach the same labels to all your metrics. Those use cases are
// better covered by target labels set by the scraping Prometheus
// server, or by one specific metric (e.g. a build_info or a
// machine_role metric). See also
// https://prometheus.io/docs/instrumenting/writing_exporters/#target-labels-not-static-scraped-labels
ConstLabels Labels
// Buckets defines the buckets into which observations are counted. Each
......@@ -155,6 +186,10 @@ type HistogramOpts struct {
// NewHistogram creates a new Histogram based on the provided HistogramOpts. It
// panics if the buckets in HistogramOpts are not in strictly increasing order.
//
// The returned implementation also implements ExemplarObserver. It is safe to
// perform the corresponding type assertion. Exemplars are tracked separately
// for each bucket.
func NewHistogram(opts HistogramOpts) Histogram {
return newHistogram(
NewDesc(
......@@ -169,7 +204,7 @@ func NewHistogram(opts HistogramOpts) Histogram {
func newHistogram(desc *Desc, opts HistogramOpts, labelValues ...string) Histogram {
if len(desc.variableLabels) != len(labelValues) {
panic(errInconsistentCardinality)
panic(makeInconsistentCardinalityError(desc.fqName, desc.variableLabels, labelValues))
}
for _, n := range desc.variableLabels {
......@@ -190,7 +225,9 @@ func newHistogram(desc *Desc, opts HistogramOpts, labelValues ...string) Histogr
h := &histogram{
desc: desc,
upperBounds: opts.Buckets,
labelPairs: makeLabelPairs(desc, labelValues),
labelPairs: MakeLabelPairs(desc, labelValues),
counts: [2]*histogramCounts{{}, {}},
now: time.Now,
}
for i, upperBound := range h.upperBounds {
if i < len(h.upperBounds)-1 {
......@@ -207,30 +244,60 @@ func newHistogram(desc *Desc, opts HistogramOpts, labelValues ...string) Histogr
}
}
}
// Finally we know the final length of h.upperBounds and can make counts.
h.counts = make([]uint64, len(h.upperBounds))
// Finally we know the final length of h.upperBounds and can make buckets
// for both counts as well as exemplars:
h.counts[0].buckets = make([]uint64, len(h.upperBounds))
h.counts[1].buckets = make([]uint64, len(h.upperBounds))
h.exemplars = make([]atomic.Value, len(h.upperBounds)+1)
h.init(h) // Init self-collection.
return h
}
type histogram struct {
type histogramCounts struct {
// sumBits contains the bits of the float64 representing the sum of all
// observations. sumBits and count have to go first in the struct to
// guarantee alignment for atomic operations.
// http://golang.org/pkg/sync/atomic/#pkg-note-BUG
sumBits uint64
count uint64
buckets []uint64
}
selfCollector
// Note that there is no mutex required.
type histogram struct {
// countAndHotIdx enables lock-free writes with use of atomic updates.
// The most significant bit is the hot index [0 or 1] of the count field
// below. Observe calls update the hot one. All remaining bits count the
// number of Observe calls. Observe starts by incrementing this counter,
// and finish by incrementing the count field in the respective
// histogramCounts, as a marker for completion.
//
// Calls of the Write method (which are non-mutating reads from the
// perspective of the histogram) swap the hot–cold under the writeMtx
// lock. A cooldown is awaited (while locked) by comparing the number of
// observations with the initiation count. Once they match, then the
// last observation on the now cool one has completed. All cool fields must
// be merged into the new hot before releasing writeMtx.
//
// Fields with atomic access first! See alignment constraint:
// http://golang.org/pkg/sync/atomic/#pkg-note-BUG
countAndHotIdx uint64
selfCollector
desc *Desc
writeMtx sync.Mutex // Only used in the Write method.
upperBounds []float64
counts []uint64
// Two counts, one is "hot" for lock-free observations, the other is
// "cold" for writing out a dto.Metric. It has to be an array of
// pointers to guarantee 64bit alignment of the histogramCounts, see
// http://golang.org/pkg/sync/atomic/#pkg-note-BUG.
counts [2]*histogramCounts
upperBounds []float64
labelPairs []*dto.LabelPair
exemplars []atomic.Value // One more than buckets (to include +Inf), each a *dto.Exemplar.
now func() time.Time // To mock out time.Now() for testing.
}
func (h *histogram) Desc() *Desc {
......@@ -238,6 +305,89 @@ func (h *histogram) Desc() *Desc {
}
func (h *histogram) Observe(v float64) {
h.observe(v, h.findBucket(v))
}
func (h *histogram) ObserveWithExemplar(v float64, e Labels) {
i := h.findBucket(v)
h.observe(v, i)
h.updateExemplar(v, i, e)
}
func (h *histogram) Write(out *dto.Metric) error {
// For simplicity, we protect this whole method by a mutex. It is not in
// the hot path, i.e. Observe is called much more often than Write. The
// complication of making Write lock-free isn't worth it, if possible at
// all.
h.writeMtx.Lock()
defer h.writeMtx.Unlock()
// Adding 1<<63 switches the hot index (from 0 to 1 or from 1 to 0)
// without touching the count bits. See the struct comments for a full
// description of the algorithm.
n := atomic.AddUint64(&h.countAndHotIdx, 1<<63)
// count is contained unchanged in the lower 63 bits.
count := n & ((1 << 63) - 1)
// The most significant bit tells us which counts is hot. The complement
// is thus the cold one.
hotCounts := h.counts[n>>63]
coldCounts := h.counts[(^n)>>63]
// Await cooldown.
for count != atomic.LoadUint64(&coldCounts.count) {
runtime.Gosched() // Let observations get work done.
}
his := &dto.Histogram{
Bucket: make([]*dto.Bucket, len(h.upperBounds)),
SampleCount: proto.Uint64(count),
SampleSum: proto.Float64(math.Float64frombits(atomic.LoadUint64(&coldCounts.sumBits))),
}
var cumCount uint64
for i, upperBound := range h.upperBounds {
cumCount += atomic.LoadUint64(&coldCounts.buckets[i])
his.Bucket[i] = &dto.Bucket{
CumulativeCount: proto.Uint64(cumCount),
UpperBound: proto.Float64(upperBound),
}
if e := h.exemplars[i].Load(); e != nil {
his.Bucket[i].Exemplar = e.(*dto.Exemplar)
}
}
// If there is an exemplar for the +Inf bucket, we have to add that bucket explicitly.
if e := h.exemplars[len(h.upperBounds)].Load(); e != nil {
b := &dto.Bucket{
CumulativeCount: proto.Uint64(count),
UpperBound: proto.Float64(math.Inf(1)),
Exemplar: e.(*dto.Exemplar),
}
his.Bucket = append(his.Bucket, b)
}
out.Histogram = his
out.Label = h.labelPairs
// Finally add all the cold counts to the new hot counts and reset the cold counts.
atomic.AddUint64(&hotCounts.count, count)
atomic.StoreUint64(&coldCounts.count, 0)
for {
oldBits := atomic.LoadUint64(&hotCounts.sumBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + his.GetSampleSum())
if atomic.CompareAndSwapUint64(&hotCounts.sumBits, oldBits, newBits) {
atomic.StoreUint64(&coldCounts.sumBits, 0)
break
}
}
for i := range h.upperBounds {
atomic.AddUint64(&hotCounts.buckets[i], atomic.LoadUint64(&coldCounts.buckets[i]))
atomic.StoreUint64(&coldCounts.buckets[i], 0)
}
return nil
}
// findBucket returns the index of the bucket for the provided value, or
// len(h.upperBounds) for the +Inf bucket.
func (h *histogram) findBucket(v float64) int {
// TODO(beorn7): For small numbers of buckets (<30), a linear search is
// slightly faster than the binary search. If we really care, we could
// switch from one search strategy to the other depending on the number
......@@ -247,38 +397,43 @@ func (h *histogram) Observe(v float64) {
// 11 buckets: 38.3 ns/op linear - binary 48.7 ns/op
// 100 buckets: 78.1 ns/op linear - binary 54.9 ns/op
// 300 buckets: 154 ns/op linear - binary 61.6 ns/op
i := sort.SearchFloat64s(h.upperBounds, v)
if i < len(h.counts) {
atomic.AddUint64(&h.counts[i], 1)
return sort.SearchFloat64s(h.upperBounds, v)
}
// observe is the implementation for Observe without the findBucket part.
func (h *histogram) observe(v float64, bucket int) {
// We increment h.countAndHotIdx so that the counter in the lower
// 63 bits gets incremented. At the same time, we get the new value
// back, which we can use to find the currently-hot counts.
n := atomic.AddUint64(&h.countAndHotIdx, 1)
hotCounts := h.counts[n>>63]
if bucket < len(h.upperBounds) {
atomic.AddUint64(&hotCounts.buckets[bucket], 1)
}
atomic.AddUint64(&h.count, 1)
for {
oldBits := atomic.LoadUint64(&h.sumBits)
oldBits := atomic.LoadUint64(&hotCounts.sumBits)
newBits := math.Float64bits(math.Float64frombits(oldBits) + v)
if atomic.CompareAndSwapUint64(&h.sumBits, oldBits, newBits) {
if atomic.CompareAndSwapUint64(&hotCounts.sumBits, oldBits, newBits) {
break
}
}
// Increment count last as we take it as a signal that the observation
// is complete.
atomic.AddUint64(&hotCounts.count, 1)
}
func (h *histogram) Write(out *dto.Metric) error {
his := &dto.Histogram{}
buckets := make([]*dto.Bucket, len(h.upperBounds))
his.SampleSum = proto.Float64(math.Float64frombits(atomic.LoadUint64(&h.sumBits)))
his.SampleCount = proto.Uint64(atomic.LoadUint64(&h.count))
var count uint64
for i, upperBound := range h.upperBounds {
count += atomic.LoadUint64(&h.counts[i])
buckets[i] = &dto.Bucket{
CumulativeCount: proto.Uint64(count),
UpperBound: proto.Float64(upperBound),
// updateExemplar replaces the exemplar for the provided bucket. With empty
// labels, it's a no-op. It panics if any of the labels is invalid.
func (h *histogram) updateExemplar(v float64, bucket int, l Labels) {
if l == nil {
return
}
e, err := newExemplar(v, h.now(), l)
if err != nil {
panic(err)
}
his.Bucket = buckets
out.Histogram = his
out.Label = h.labelPairs
return nil
h.exemplars[bucket].Store(e)
}
// HistogramVec is a Collector that bundles a set of Histograms that all share the
......@@ -287,7 +442,7 @@ func (h *histogram) Write(out *dto.Metric) error {
// (e.g. HTTP request latencies, partitioned by status code and method). Create
// instances with NewHistogramVec.
type HistogramVec struct {
*metricVec
*MetricVec
}
// NewHistogramVec creates a new HistogramVec based on the provided HistogramOpts and
......@@ -300,14 +455,14 @@ func NewHistogramVec(opts HistogramOpts, labelNames []string) *HistogramVec {
opts.ConstLabels,
)
return &HistogramVec{
metricVec: newMetricVec(desc, func(lvs ...string) Metric {
MetricVec: NewMetricVec(desc, func(lvs ...string) Metric {
return newHistogram(desc, opts, lvs...)
}),
}
}
// GetMetricWithLabelValues returns the Histogram for the given slice of label
// values (same order as the VariableLabels in Desc). If that combination of
// values (same order as the variable labels 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
......@@ -322,7 +477,7 @@ func NewHistogramVec(opts HistogramOpts, labelNames []string) *HistogramVec {
// example.
//
// An error is returned if the number of label values is not the same as the
// number of VariableLabels in Desc.
// number of variable labels in Desc (minus any curried labels).
//
// 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
......@@ -330,8 +485,8 @@ func NewHistogramVec(opts HistogramOpts, labelNames []string) *HistogramVec {
// 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 (m *HistogramVec) GetMetricWithLabelValues(lvs ...string) (Observer, error) {
metric, err := m.metricVec.getMetricWithLabelValues(lvs...)
func (v *HistogramVec) GetMetricWithLabelValues(lvs ...string) (Observer, error) {
metric, err := v.MetricVec.GetMetricWithLabelValues(lvs...)
if metric != nil {
return metric.(Observer), err
}
......@@ -339,19 +494,19 @@ func (m *HistogramVec) GetMetricWithLabelValues(lvs ...string) (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
// must match those of the variable labels 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.
// with those of the variable labels in Desc (minus any curried labels).
//
// This method is used for the same purpose as
// GetMetricWithLabelValues(...string). See there for pros and cons of the two
// methods.
func (m *HistogramVec) GetMetricWith(labels Labels) (Observer, error) {
metric, err := m.metricVec.getMetricWith(labels)
func (v *HistogramVec) GetMetricWith(labels Labels) (Observer, error) {
metric, err := v.MetricVec.GetMetricWith(labels)
if metric != nil {
return metric.(Observer), err
}
......@@ -359,18 +514,57 @@ func (m *HistogramVec) GetMetricWith(labels Labels) (Observer, error) {
}
// WithLabelValues works as GetMetricWithLabelValues, but panics where
// GetMetricWithLabelValues would have returned an error. By not returning an
// error, WithLabelValues allows shortcuts like
// GetMetricWithLabelValues would have returned an error. Not returning an
// error allows shortcuts like
// myVec.WithLabelValues("404", "GET").Observe(42.21)
func (m *HistogramVec) WithLabelValues(lvs ...string) Observer {
return m.metricVec.withLabelValues(lvs...).(Observer)
func (v *HistogramVec) WithLabelValues(lvs ...string) Observer {
h, err := v.GetMetricWithLabelValues(lvs...)
if err != nil {
panic(err)
}
return h
}
// 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 (m *HistogramVec) With(labels Labels) Observer {
return m.metricVec.with(labels).(Observer)
// With works as GetMetricWith but panics where GetMetricWithLabels would have
// returned an error. Not returning an error allows shortcuts like
// myVec.With(prometheus.Labels{"code": "404", "method": "GET"}).Observe(42.21)
func (v *HistogramVec) With(labels Labels) Observer {
h, err := v.GetMetricWith(labels)
if err != nil {
panic(err)
}
return h
}
// CurryWith returns a vector curried with the provided labels, i.e. the
// returned vector has those labels pre-set for all labeled operations performed
// on it. The cardinality of the curried vector is reduced accordingly. The
// order of the remaining labels stays the same (just with the curried labels
// taken out of the sequence – which is relevant for the
// (GetMetric)WithLabelValues methods). It is possible to curry a curried
// vector, but only with labels not yet used for currying before.
//
// The metrics contained in the HistogramVec are shared between the curried and
// uncurried vectors. They are just accessed differently. Curried and uncurried
// vectors behave identically in terms of collection. Only one must be
// registered with a given registry (usually the uncurried version). The Reset
// method deletes all metrics, even if called on a curried vector.
func (v *HistogramVec) CurryWith(labels Labels) (ObserverVec, error) {
vec, err := v.MetricVec.CurryWith(labels)
if vec != nil {
return &HistogramVec{vec}, err
}
return nil, err
}
// MustCurryWith works as CurryWith but panics where CurryWith would have
// returned an error.
func (v *HistogramVec) MustCurryWith(labels Labels) ObserverVec {
vec, err := v.CurryWith(labels)
if err != nil {
panic(err)
}
return vec
}
type constHistogram struct {
......@@ -422,7 +616,7 @@ func (h *constHistogram) Write(out *dto.Metric) error {
// bucket.
//
// NewConstHistogram returns an error if the length of labelValues is not
// consistent with the variable labels in Desc.
// consistent with the variable labels in Desc or if Desc is invalid.
func NewConstHistogram(
desc *Desc,
count uint64,
......@@ -430,6 +624,9 @@ func NewConstHistogram(
buckets map[float64]uint64,
labelValues ...string,
) (Metric, error) {
if desc.err != nil {
return nil, desc.err
}
if err := validateLabelValues(labelValues, len(desc.variableLabels)); err != nil {
return nil, err
}
......@@ -438,12 +635,12 @@ func NewConstHistogram(
count: count,
sum: sum,
buckets: buckets,
labelPairs: makeLabelPairs(desc, labelValues),
labelPairs: MakeLabelPairs(desc, labelValues),
}, nil
}
// MustNewConstHistogram is a version of NewConstHistogram that panics where
// NewConstMetric would have returned an error.
// NewConstHistogram would have returned an error.
func MustNewConstHistogram(
desc *Desc,
count uint64,
......