github.com/armon/go-metrics/circonus

A Golang library for exporting performance and runtime metrics to external metrics systems (i.e. statsite, statsd)


License
MIT
Install
go get github.com/armon/go-metrics/circonus

Documentation

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.

Labels

Most metrics do have an equivalent ending with WithLabels, such methods allow to push metrics with labels and use some features of underlying Sinks (ex: translated into Prometheus labels).

Since some of these labels may increase greatly cardinality of metrics, the library allow to filter labels using a blacklist/whitelist filtering system which is global to all metrics.

  • If Config.AllowedLabels is not nil, then only labels specified in this value will be sent to underlying Sink, otherwise, all labels are sent by default.
  • If Config.BlockedLabels is not nil, any label specified in this value will not be sent to underlying Sinks.

By default, both Config.AllowedLabels and Config.BlockedLabels are nil, meaning that no tags are filetered at all, but it allow to a user to globally block some tags with high cardinality at application level.

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 a 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