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.. | ||
.gitignore | ||
LICENSE | ||
README.md | ||
const_unix.go | ||
const_windows.go | ||
inmem.go | ||
inmem_signal.go | ||
metrics.go | ||
sink.go | ||
start.go | ||
statsd.go | ||
statsite.go |
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.
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