Anake

Ananke is a Java library that allows Java applications to communicate with and send information to a StatsD listener. You can use Ananke to send metrics from your Java applications to a StatsD server, which will then send the metrics to Metricly.

Configuration

1. Setup the Metricly StatsD integration or the Etsy StatsD integration if you haven’t already. We recommend setting up the Metricly StatsD integration if you don’t have a StatsD server already; if you have a StatsD server setup, we recommend setting up the Etsy StatsD integration.
2. Include the proper dependency from Maven for the appropriate build manager.
3. Invoke the StatsD client interface in a central location that your various Java classes can access.

StatsDClient client = new NetuitiveStatsDClient("localhost", "8000");

4. Utilize code instrumentation to send metrics, events, service checks, and more into Metricly (basic examples included below each type). Metricly supports the following metric types: - Decrement (Counter – Down): Decrease the count of how many times something happened per second.

 client.decrement(new DecrementRequest()
  .withMetric("tokens_left.count")
  .withValue(-1));

• Event: A log of something that happened, including a title and a description of the event.

 client.event(new EventRequest()
  .withTitle("Event Title")
  .withText("Send help!"));

• Gauge: An arbitrary, persistent value (e.g., a fuel meter).

 client.gauge(new GaugeRequest()
  .withMetric("gas_tank.level")
  .withValue(1L));

• Histograms: The statistical distribution of a set of values.

 client.histogram(new HistogramRequest()
  .withMetric("file.upload.size")
  .withValue(2MB));

• Increment (Counter – Up): Increase the count of how many times something happened per second.

 client.increment(new IncrementRequest()
  .withMetric("page_view.count")
  .withValue(1));

• Service Check: A check to see if a service is either up or down.

 client.servicecheck(new ServiceCheckRequest()
  .withName("my_service")
  .withStatus(1));

• Sets: A number of unique elements received over a set interval.

 client.set(new SetRequest()
  .withName("users.unique")
  .withValue(user.id));

• Timed: Pass in a callable function that Ananke will time how long it takes to run and then passes the value on.

 client.timed(new TimedRequest()
  .withFunc("pageloadtime()");

• Timing: Measure in milliseconds how long an action took.

 client.timing(new TimingRequest()
  .withMetric("x")
  .withValue(xms));

Java Integration Options

We have several different options for monitoring Java applications. Each method varies in terms of setup difficulty and the amount / type of information it collects.

Method	Description
Ananke	Java library you can use to push metrics to the StatsD listener embedded in our Linux agent. This approach requires that you integrate the StatsDReporter into your applications.
Dropwizard	Integrate the dropwizard-metrics library into your Dropwizard application and configure it to send metrics to the StatsD listener embedded in our Linux agent.
Iris	Java library you can use to push metrics directly to Metricly’s REST API.
Java Agent	Open-source and open-license Java agent the does the byte-code instrumentation for you. No changes to source code required.
JMX	Integration that relies on our Linux agent to collect JVM metrics (e.g., heap size, garbage collection, etc.) without code-level instrumentation.