milenkovicm / kamon-prometheus Edit

A Kamon backend to support Prometheus

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This library provides a Kamon module that can serve metrics to Prometheus, an open source service monitoring system and time series database. Since Prometheus uses a scraping mechanism and its own data model, this module bridges the gap between the two. It converts Kamon metrics into a Prometheus-friendly format and provides integrations for both Spray and Akka HTTP so that your application can serve metrics to Prometheus.


  • Converts Kamon metrics data to conform to Prometheus’ data model, including:

    • Reasonably handles all Kamon entities, including custom entities

    • Preservation of units of measurement

  • Provides Spray and Akka HTTP route that supports:

    • Both text and Protocol buffer representation formats

    • Optional gzip compression

  • Allows collection of snapshots without an endpoint using an actor

  • Allows configuration of:

    • Refresh interval to match Prometheus

    • Metric subscriptions to export

    • Additional Prometheus labels on exported metrics


In order to use this module, you will need to add the following dependency to your build.sbt:

libraryDependencies += "com.monsanto.arch" %% "kamon-prometheus" % "0.2.0"

You may also need to add JCenter as a resolver:

resolvers += Resolver.jcenterRepo

Kamon’s module loader should automatically detect the presence of kamon-prometheus and start it. However, in order to be useful, you will need to include the extension’s Spray or Akka HTTP routes somewhere in your service so that Prometheus can invoke it.


This module depends on:

Additional dependencies are required if you are interested in building the library.


You can configure the module much like any other Kamon module, by modifying your application.conf. All of the configuration entries for kamon-prometheus are placed under kamon.prometheus.

Refresh interval

The kamon.prometheus.refresh-interval setting determines how often the kamon-prometheus will flush and serve new data. This setting must be at least as large as kamon.metric.tick-interval, and should match Prometheus’ scrape_interval. The default refresh interval is one minute, which matches Prometheus’ default.


Like most other Kamon reporting module, kamon-prometheus allows you to configure the metric categories to which the module will subscribe. By default, the following subscriptions are included:

The default kamon-prometheus subscriptions
kamon.prometheus {
  subscriptions {
    histogram        = [ "**" ]
    min-max-counter  = [ "**" ]
    gauge            = [ "**" ]
    counter          = [ "**" ]
    trace            = [ "**" ]
    trace-segment    = [ "**" ]
    akka-actor       = [ "**" ]
    akka-dispatcher  = [ "**" ]
    akka-router      = [ "**" ]
    system-metric    = [ "**" ]
    http-server      = [ "**" ]
    spray-can-server = [ "**" ]

Additional labels

kamon-prometheus will automatically add a metric’s tags, name, and category to a published metric as labels. If you which to add additional labels, you can add them under the kamon.prometheus.labels path, which is empty by default.

For example, given:

The default kamon-prometheus subscriptions
kamon.prometheus {
  labels {
    application_name = "my cool app"
    application_version = "42"

All metrics published by kamon-prometheus will add the labels application_name="my cool app" and application_version="42" to all published metrics. Keep in mind that label names may munged to fit Prometheus’ naming requirements.


There are currently three principal ways to use kamon-prometheus:

  1. Using the Spray endpoint

  2. Using the Akka HTTP endpoint

  3. Collecting metrics via an Actor

Once you have made the metrics available, you will need to configure Prometheus to scrape your application.

Using the Spray endpoint

The module provides a Spray route which you can access via SprayEndpoint(system).route where system is an actor system. You can place this route anywhere in your application, but keep in mind that Prometheus scrapes /metrics by default. The following is the code for a minimal application that will serve metrics from http://localhost:8888/metrics:

A minimal Spray application
import com.monsanto.arch.kamon.prometheus.spray.SprayEndpoint
import spray.routing.SimpleRoutingApp

object Main extends App with SimpleRoutingApp {
  implicit val actorSystem = ActorSystem()

  startServer("localhost", 8888) {
    path("metrics") {

Note that the route will only respond to GET requests and will automatically handle compression and media type negotiation. If there is no content yet (generally before the first set of metrics has been collected), the route will return a No Content response (204).

Using the Akka HTTP endpoint

Using the Akka HTTP endpoint is just like using the Spray endpoint above, except that you use a different Akka extension.

A minimal Akka HTTP application
import akka.http.scaladsl.Http
import akka.http.scaladsl.server.Directives._
import com.monsanto.arch.kamon.prometheus.akka_http.AkkaHttpEndpoint

object Main extends App {
  implicit val system = ActorSystem()
  implicit val materializer = ActorMaterializer()

  val route = {
    path("metrics") {

  val bindingFuture = Http().bindAndHandle(route, "localhost", 8888)

Getting snapshots with an actor

For this functionality, please consult the documentation for PrometheusExtension.

Consuming the metrics

Finally, all you need to do is configure a scrape configuration in Prometheus. The following snippet is a minimal example that shold work with the minimal server from the previous section.

A minimal Prometheus configuration snippet
  - job_name: example
      - targets: ['localhost:8888']

Note that the above configuration uses the default scrape_interval (one minute, matching kamon-prometheus’ default.) and metrics_path (/metrics).


Building the library

You can use sbt to build the library, but you will need to have Google’s protocol buffers compiler protoc on your path. You can download Protocol buffers directly from Google. However, there may be simpler options. For example, on OS X, you can use homebrew and just brew install protobuf.

Additionally, to build the demo, you will need to have Docker set up.

Contributing to the project

Outside contributions to this project are welcome! Please review for more information.

Future plans

Check out the issues page. Please star issues that are important to you.