rcrowley/go-metrics
GitHub: rcrowley/go-metrics
Coda Hale Metrics 的 Go 移植版,为 Go 应用提供计数器、仪表盘、直方图、计时器等指标采集与多后端上报能力,现已被归档。
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# go-metrics

Coda Hale 的 Metrics 库的 Go 移植版:。
文档:。
## 自 2025 年 4 月 1 日起归档
此仓库不再维护。作者建议您探索以下更新的、被更广泛采用的库来
满足您的 Go 监控需求:
* [OpenTelemetry Go SDK](https://opentelemetry.io/docs/languages/go/instrumentation/#metrics)
* [Prometheus Go 客户端库](https://pkg.go.dev/github.com/prometheus/client_golang/prometheus)
## 用法
创建并更新指标:
```
c := metrics.NewCounter()
metrics.Register("foo", c)
c.Inc(47)
g := metrics.NewGauge()
metrics.Register("bar", g)
g.Update(47)
r := NewRegistry()
g := metrics.NewRegisteredFunctionalGauge("cache-evictions", r, func() int64 { return cache.getEvictionsCount() })
s := metrics.NewExpDecaySample(1028, 0.015) // or metrics.NewUniformSample(1028)
h := metrics.NewHistogram(s)
metrics.Register("baz", h)
h.Update(47)
m := metrics.NewMeter()
metrics.Register("quux", m)
m.Mark(47)
t := metrics.NewTimer()
metrics.Register("bang", t)
t.Time(func() {})
t.Update(47)
```
Register() 不是线程安全的。对于线程安全的指标注册,请使用
GetOrRegister:
```
t := metrics.GetOrRegisterTimer("account.create.latency", nil)
t.Time(func() {})
t.Update(47)
```
**注意:** 务必注销短生命周期的 meter 和 timer,否则它们会导致
内存泄漏:
```
// Will call Stop() on the Meter to allow for garbage collection
metrics.Unregister("quux")
// Or similarly for a Timer that embeds a Meter
metrics.Unregister("bang")
```
定期以人类可读的形式将每个指标记录到标准错误输出:
```
go metrics.Log(metrics.DefaultRegistry, 5 * time.Second, log.New(os.Stderr, "metrics: ", log.Lmicroseconds))
```
定期以更易于解析的形式将每个指标记录到 syslog:
```
w, _ := syslog.Dial("unixgram", "/dev/log", syslog.LOG_INFO, "metrics")
go metrics.Syslog(metrics.DefaultRegistry, 60e9, w)
```
使用 [Graphite 客户端](https://github.com/cyberdelia/go-metrics-graphite) 定期将每个指标发送到 Graphite:
```
import "github.com/cyberdelia/go-metrics-graphite"
addr, _ := net.ResolveTCPAddr("tcp", "127.0.0.1:2003")
go graphite.Graphite(metrics.DefaultRegistry, 10e9, "metrics", addr)
```
定期将每个指标发送到 InfluxDB:
**注意:** 由于 InfluxDB API 的不断变动,此功能已从库中移除。实际上,所有的客户端库都在逐步淘汰。请查看
issue [#121](https://github.com/rcrowley/go-metrics/issues/121) 和
[#124](https://github.com/rcrowley/go-metrics/issues/124) 以了解进展和详细信息。
```
import "github.com/vrischmann/go-metrics-influxdb"
go influxdb.InfluxDB(metrics.DefaultRegistry,
10e9,
"127.0.0.1:8086",
"database-name",
"username",
"password"
)
```
使用 [Librato 客户端](https://github.com/mihasya/go-metrics-librato) 定期将每个指标上传到 Librato:
**注意**:此仓库中 `librato` 包下包含的客户端
已被弃用,并移至上面链接的仓库。
```
import "github.com/mihasya/go-metrics-librato"
go librato.Librato(metrics.DefaultRegistry,
10e9, // interval
"example@example.com", // account owner email address
"token", // Librato API token
"hostname", // source
[]float64{0.95}, // percentiles to send
time.Millisecond, // time unit
)
```
定期将每个指标发送到 StatHat:
```
import "github.com/rcrowley/go-metrics/stathat"
go stathat.Stathat(metrics.DefaultRegistry, 10e9, "example@example.com")
```
将所有指标连同 expvars 一起维护在 `/debug/metrics`:
这使用了与[官方 expvar](http://golang.org/pkg/expvar/)相同的机制,
但暴露在 `/debug/metrics` 下,它会以 JSON 格式显示您所有常规的 expvars
以及所有的 go-metrics。
```
import "github.com/rcrowley/go-metrics/exp"
exp.Exp(metrics.DefaultRegistry)
```
## 安装
```
go get github.com/rcrowley/go-metrics
```
StatHat 支持还需要它们的 Go 客户端:
```
go get github.com/stathat/go
```
## 发布指标
以下目标提供了相应的客户端:
* AppOptics - https://github.com/ysamlan/go-metrics-appoptics
* Librato - https://github.com/mihasya/go-metrics-librato
* Graphite - https://github.com/cyberdelia/go-metrics-graphite
* InfluxDB - https://github.com/vrischmann/go-metrics-influxdb
* Ganglia - https://github.com/appscode/metlia
* Prometheus - https://github.com/deathowl/go-metrics-prometheus
* DataDog - https://github.com/syntaqx/go-metrics-datadog
* SignalFX - https://github.com/pascallouisperez/go-metrics-signalfx
* Honeycomb - https://github.com/getspine/go-metrics-honeycomb
* Wavefront - https://github.com/wavefrontHQ/go-metrics-wavefront
* Open-Falcon - https://github.com/g4zhuj/go-metrics-falcon
* AWS CloudWatch - [https://github.com/savaki/cloudmetrics](https://github.com/savaki/cloudmetrics)
标签:API集成, EVTX分析, Go, Ruby工具, SOC Prime, 可观测性, 开发工具, 性能监控, 指标度量, 日志审计