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Capturing JVM- and application-level metrics. So you know what's going on.

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README.md

Metrics

Capturing JVM- and application-level metrics. So you know what's going on.

Requirements

  • Java SE 6
  • Scala 2.8.1
  • Jackson 1.6.4

How To Use

First, specify Metrics as a dependency:

val codaRepo = "Coda Hale's Repository" at "http://repo.codahale.com/"
val metrics = "com.yammer" %% "metrics" % "2.0.0-BETA2" withSources()

(Or whatever it takes for you to get Maven or Ivy happy.)

Second, instrument your classes:

import java.util.concurrent.TimeUnit
import com.yammer.metrics.Instrumented

class ThingFinder extends Instrumented {
  // measure the # of records per second returned
  private val resultsMeter = metrics.meter("results", "records", TimeUnit.SECONDS)
  // measure the # of milliseconds each query takes and the number of
  // queries per second being performed
  private val dbTimer = metrics.timer("database", TimeUnit.MILLISECONDS, TimeUnit.SECONDS)

  def findThings() = {
    val results = dbTimer.time {
      // perform an action which gets timed
      Database.query("WHOO")
    }

    // calculate the rate of new things found
    resultsMeter.mark(results.size)

    // etc.
  }
}

Metrics comes with four types of metrics:

  • Gauges are instantaneous readings of values (e.g., a queue depth).
  • Counters are 64-bit integers which can be incremented or decremented.
  • Meters are increment-only counters which keep track of the rate of events. They provide mean rates, plus exponentially-weighted moving averages which use the same formula that the UNIX 1-, 5-, and 15-minute load averages use.
  • Timers record the duration as well as the rate of events. In addition to the rate information that meters provide, timers also provide the count, maximum, minimum, mean, standard deviation, median, 75th percentile, 95th percentile, 98th percentile, 99th percentile, and 99.9th percentile of timings. (They do so using a method called reservoir sampling which allows them to efficiently keep a small, statistically representative sample of all the measurements.)

Third, report these metrics via either the console, HTTP+JSON, or JMX:

import com.yammer.metrics.Metrics

object MyAppRunner  {
  def main(args: Array[String]) {
    Metrics.enableHttpReporting(8081) // listen on port 8081
    Metrics.enableConsoleReporting(10, TimeUnit.SECONDS) // print to STDERR every 10s
    Metrics.enableJmxReporting()
  }
}

License

Copyright (c) 2010 Coda Hale, Yammer.com

Published under The MIT License, see LICENSE

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