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Harness provides you with high level application metrics. It collects metrics from various sources and forwards them to the collector. You can use any collector that implements the Statsd interface. Harness also collects metrics from ActiveSupport::Notifications and forwards them to the collector.

Harness only assumes one thing: the collector can do proper metric aggregation and statistics. Example: using statsd will calculate the 90th percentile and averages.

Harness is designed for very high traffic applications. Instrumenting code should cost as close to 0 as possible. All metrics are processed in a separate thread. The main thread will never do any more work than needed. Using a thread allows you to instrument 10,000's metrics per second without worrying.

Harness's has two main goals:

  1. Make instrumentation fast and cheap
  2. Provide high level system metrics (think like a car dashboard for your app).

Solving #1 is easy: include Harness::Instrumented in your class. #2 is slightly more complicated, but Harness automatically collects all the metrics for you.

Application Independent Metrics

Most ruby applications are using a similar stack: rack, a cache, a key value store, job processor, and persistent data store. Visiblity is the most important thing when it comes to application performance. You can only improve something when you can measure it. Harness takes care of the measuring. Harness integrates with common components in the ruby eosystem and gives you the data you need. You should put this data on your dashboard and pay attention to it.

These metrics should be enough to give you a high level overview on how all the different layers in your stack are performing. Harness is not for drilling down into a specific request or peice of code. You should use the ruby-prof for that. In short, Harness is not a replacement for new-relic. They serve different purposes. However, you could deduce all the information newrelic provides from instrumentation data.

Supported Libraries & Projects

Harness is an interface. All integrations use the interface. Instrumentation for popular libraries are provided as gems. This allows anyone to release instrumentations. Individual gems can be maintained and released separate of this gem. Here is the definite list.


Harness provides the same interface as statsd. You can interact with Harness directly. This is not advised. You should include or extend Harness::Instrumentation in your class. Here are some examples.

class UseCase
  include Harness::Instrumentation

  def run!
    increment 'foo'
    increment 'foo', 5

    decrement 'foo'
    decrement 'foo', 5

    count 'foo', 1000

    time 'foo' do
      # do hard work

That's all there is to it!


Harness has two configuration options: the queue and collector. Harness::AsyncQueue is the default queue. This means all metrics are logged in a separate thread to never block the main thread. This makes harness more performant in high traffic scenarios. Harness::NullCollector. There is also a Harness::SyncQueue useful for testing (but really used in practice).

Harness.collector = Statsd.new 'something.com'
Harness.queue = Harness::AsyncQueue


  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Added some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request