open-consul/vendor/github.com/armon/go-metrics
James Phillips 43dab05630
Updates armon/go-metrics.
2016-08-09 16:27:17 -07:00
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circonus Updates armon/go-metrics and adds Circonus vendored libraries. 2016-07-19 16:54:21 -07:00
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LICENSE Manage dependencies via Godep 2016-02-12 16:50:37 -08:00
README.md Manage dependencies via Godep 2016-02-12 16:50:37 -08:00
const_unix.go Manage dependencies via Godep 2016-02-12 16:50:37 -08:00
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inmem.go Updates armon/go-metrics and adds Circonus vendored libraries. 2016-07-19 16:54:21 -07:00
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metrics.go Updates armon/go-metrics and adds Circonus vendored libraries. 2016-07-19 16:54:21 -07:00
sink.go Updates armon/go-metrics and adds Circonus vendored libraries. 2016-07-19 16:54:21 -07:00
start.go Updates armon/go-metrics and adds Circonus vendored libraries. 2016-07-19 16:54:21 -07:00
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statsite.go Updates armon/go-metrics and adds Circonus vendored libraries. 2016-07-19 16:54:21 -07:00

README.md

go-metrics

This library provides a metrics package which can be used to instrument code, expose application metrics, and profile runtime performance in a flexible manner.

Current API: GoDoc

Sinks

The metrics package makes use of a MetricSink interface to support delivery to any type of backend. Currently the following sinks are provided:

  • StatsiteSink : Sinks to a statsite instance (TCP)
  • StatsdSink: Sinks to a StatsD / statsite instance (UDP)
  • PrometheusSink: Sinks to a Prometheus metrics endpoint (exposed via HTTP for scrapes)
  • InmemSink : Provides in-memory aggregation, can be used to export stats
  • FanoutSink : Sinks to multiple sinks. Enables writing to multiple statsite instances for example.
  • BlackholeSink : Sinks to nowhere

In addition to the sinks, the InmemSignal can be used to catch a signal, and dump a formatted output of recent metrics. For example, when a process gets a SIGUSR1, it can dump to stderr recent performance metrics for debugging.

Examples

Here is an example of using the package:

func SlowMethod() {
    // Profiling the runtime of a method
    defer metrics.MeasureSince([]string{"SlowMethod"}, time.Now())
}

// Configure a statsite sink as the global metrics sink
sink, _ := metrics.NewStatsiteSink("statsite:8125")
metrics.NewGlobal(metrics.DefaultConfig("service-name"), sink)

// Emit a Key/Value pair
metrics.EmitKey([]string{"questions", "meaning of life"}, 42)

Here is an example of setting up an signal handler:

// Setup the inmem sink and signal handler
inm := metrics.NewInmemSink(10*time.Second, time.Minute)
sig := metrics.DefaultInmemSignal(inm)
metrics.NewGlobal(metrics.DefaultConfig("service-name"), inm)

// Run some code
inm.SetGauge([]string{"foo"}, 42)
inm.EmitKey([]string{"bar"}, 30)

inm.IncrCounter([]string{"baz"}, 42)
inm.IncrCounter([]string{"baz"}, 1)
inm.IncrCounter([]string{"baz"}, 80)

inm.AddSample([]string{"method", "wow"}, 42)
inm.AddSample([]string{"method", "wow"}, 100)
inm.AddSample([]string{"method", "wow"}, 22)

....

When a signal comes in, output like the following will be dumped to stderr:

[2014-01-28 14:57:33.04 -0800 PST][G] 'foo': 42.000
[2014-01-28 14:57:33.04 -0800 PST][P] 'bar': 30.000
[2014-01-28 14:57:33.04 -0800 PST][C] 'baz': Count: 3 Min: 1.000 Mean: 41.000 Max: 80.000 Stddev: 39.509
[2014-01-28 14:57:33.04 -0800 PST][S] 'method.wow': Count: 3 Min: 22.000 Mean: 54.667 Max: 100.000 Stddev: 40.513