jefersonm/signalfx-java

Java libraries for SignalFx code

SignalFx client libraries

This repository contains libraries for instrumenting Java applications and reporting metrics to SignalFx. You will need a SignalFx account and organization API token to use them. For more information on SignalFx and to create an account, go to http://www.signalfx.com.

We recommend sending metrics with Java using Codahale Metrics version 3.0+. You can also use Yammer Metrics 2.0.x (an earlier version of Codahale Metrics). More information on the Codahale Metrics library can be found on the Codahale Metrics website.

You can also use the module signalfx-java to send metrics directly to SignalFx using protocol buffers, without using Codahale or Yammer metrics.

Supported languages

• Java 6+ with signalfx-metrics.

Using this library in your project

With Maven

If you're using Maven, add the following to your project's pom.xml file.

• To work with Codahale 3.0.x:

<dependency>
  <groupId>com.signalfx.public</groupId>
  <artifactId>signalfx-codahale</artifactId>
  <version>0.0.39</version>
</dependency>

• To work with Yammer Metrics 2.0.x:

<dependency>
<groupId>com.signalfx.public</groupId>
  <artifactId>signalfx-yammer</artifactId>
  <version>0.0.39</version>
</dependency>

With SBT

If you're using SBT, add the following to your project's build.sbt file.

• To work with Codahale 3.0.x:

libraryDependencies += "com.signalfx.public" % "signalfx-codahale" % "0.0.39"

• To work with Yammer Metrics 2.0.x:

libraryDependencies += "com.signalfx.public" % "signalfx-yammer" % "0.0.39"

From source

You can also install this library from source by cloning the repo and using mvn install as follows. However, we strongly recommend using the automated mechanisms described above.

$ git clone https://github.com/signalfx/signalfx-java.git
Cloning into 'signalfx-java'...
remote: Counting objects: 930, done.
remote: Compressing objects: 100% (67/67), done.
remote: Total 930 (delta 20), reused 0 (delta 0)
Receiving objects: 100% (930/930), 146.79 KiB | 0 bytes/s, done.
Resolving deltas: 100% (289/289), done.
Checking connectivity... done.
$ cd signalfx-java
$ mvn install
[INFO] Scanning for projects...
...
...
...
[INFO] SignalFx parent .................................. SUCCESS [  2.483 s]
[INFO] SignalFx Protocol Buffer definitions ............. SUCCESS [  5.503 s]
[INFO] SignalFx Protobuf Utilities ...................... SUCCESS [  2.269 s]
[INFO] SignalFx java libraries .......................... SUCCESS [  3.728 s]
[INFO] Codahale to SignalFx ............................. SUCCESS [  2.910 s]
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 17.120 s
[INFO] ------------------------------------------------------------------------

Sending metrics

Codahale Metrics 3.0.x

1. Set up the Codahale reporter

final MetricRegistry metricRegistry = new MetricRegistry();
final SignalFxReporter signalfxReporter = new SignalFxReporter.Builder(
    metricRegistry,
    "SIGNALFX_AUTH_TOKEN"
).build();
signalfxReporter.start(1, TimeUnit.SECONDS);
final MetricMetadata metricMetadata = signalfxReporter.getMetricMetadata();

2. Send a metric

// This will send the current time in ms to SignalFx as a gauge
metricRegistry.register("gauge", new Gauge<Long>() {
    public Long getValue() {
        return System.currentTimeMillis();
    }
});

3. Add existing dimensions and metadata to metrics

You can add SignalFx specific metadata to Codahale metrics by first gathering available metadata using getMetricMetadata(), then attaching the MetricMetadata to the metric.

When you use MetricMetadata, call the .register() method you get from the call forMetric() rather than registering your metric directly with the metricRegistry. This will construct a unique Codahale string for your metric.

/*
 * This will send the size of a queue as a gauge, and attach dimension
 * 'queue_name' to the gauge.
 */
final Queue customerQueue = new ArrayBlockingQueue(100);
metricMetadata.forMetric(new Gauge<Long>() {
    @Override
    public Long getValue() {
        return customerQueue.size();
    }
}).withDimension("queue_name", "customer_backlog")
  .register(metricRegistry);

4. (optional) Add dimensions without knowing if they already exist

We recommend creating your Codahale object as a field of your class, as a counter or gauge, then using that field to increment values. If you don't want to maintain this for reasons of code cleanliness, you can create it on the fly with our builders.

For example, if you wanted a timer that included a dimension indicating which store it is from, you could use code like this.

Timer t = metricMetadata
    .forBuilder(MetricBuilder.TIMERS)
    .withMetricName("request_time")
    .withDimension("storename", "electronics")
    .createOrGet(metricRegistery);

Timer.Context c = t.time();
try {
    System.out.println("Doing store things");
} finally {
    c.close();
}

/*
 * Java 7 alternative:
 *
 * try (Timer.Context ignored = t.time()) {
 *     System.out.println("Doing store things");
 * }
 */

After setting up Codahale

After setting up a SignalFxReporter, you can use Codahale metrics as you normally would, reported at the frequency configured by the SignalFxReporter.

Default Dimensions

Sometimes there is a desire to set one or more dimension key/value pairs on every datapoint that is reported by this library. In order to do this call addDimension(String key, String value) or addDimensions(Map<String,String> dimensions) on the SignalFxReport.Builder object. Note that if IncrementalCounter is used to create a distributed counter you will want to make sure that none of the dimensions passed to addDimension/addDimensions are unique to the reporting source (e.g. hostname, AWSUniqueId) as this will make make the counter non-distributed. For such dimensions use addUniqueDimensions/addUniqueDimension on the SignalFxReport.Builder object.

AWS Integration

To enable AWS integration in SignalFx (i.e aws tag/property syncing) to a metric you can use com.signalfx.metrics.aws.AWSInstanceInfo. And either add it as a dimension in MetricMetadata or add it as a default dimension.

String instanceInfo = AWSInstanceInfo.get()
Timer t = metricMetadata
    .forBuilder(MetricBuilder.TIMERS)
    .withMetricName("request_time")
    .withDimension(AWSInstanceInfo.DIMENSION_NAME, instanceInfo)
    .createOrGet(metricRegistery);

/**
 * As default dimension
 */
final SignalFxReporter signalfxReporter = new SignalFxReporter.Builder(
    metricRegistry,
    "SIGNALFX_AUTH_TOKEN"
).addUniqueDimension(AWSInstanceInfo.DIMENSION_NAME, instanceInfo).build();

Yammer Metrics

You can also use this library with Yammer metrics 2.0.x as shown in the following examples.

1. Set up Yammer metrics

final MetricRegistry metricRegistry = new MetricRegistry();
final SignalFxReporter signalfxReporter = new SignalFxReporter.Builder(
    metricRegistery,
    "SIGNALFX_AUTH_TOKEN"
).build();
signalfxReporter.start(1, TimeUnit.SECONDS);
final MetricMetadata metricMetadata = signalfxReporter.getMetricMetadata();

2. Send a metric with Yammer metrics

// This will send the current time in ms to SignalFx as a gauge
MetricName gaugeName = new MetricName("group", "type", "gauge");
Metric gauge = metricRegistry.newGauge(gaugeName, new Gauge<Long>() {
    @Override
    public Long value() {
        return System.currentTimeMillis();
    }
});

3. Add Dimensions and SignalFx metadata to Yammer metrics

Use the MetricMetadata of the reporter as shown.

final Queue customerQueue = new ArrayBlockingQueue(100);

MetricName gaugeName = new MetricName("group", "type", "gauge");
Metric gauge = metricRegistry.newGauge(gaugeName, new Gauge<Integer>() {
    @Override
    public Integer value() {
        return customerQueue.size();
    }
});

metricMetadata.forMetric(gauge)
    .withDimension("queue_name", "customer_backlog");

4. Adding Dimensions without knowing if they already exist

This is not supported in Yammer Metrics 2.0.x.

Changing the default source

The default source name for metrics is discovered by [SourceNameHelper] (signalfx-java/src/main/java/com/signalfx/metrics/SourceNameHelper.java). If you want to override the default behavior, you can pass a third parameter to your Builder and that String is then used as the source.

For example:

final SignalFxReporter signalfxReporter = new SignalFxReporter.Builder(
    metricRegistry,
    "SIGNALFX_AUTH_TOKEN",
    "MYHOST1"
).build();

Default Dimensions

Sometimes there is a desire to set one or more dimension key/value pairs on every datapoint that is reported by this library. In order to do this call addDimension(String key, String value) or addDimensions(Map<String,String> dimensions) on the SignalFxReport.Builder object.

AWS Integration

To enable AWS integration in SignalFx (i.e aws tag/property syncing) to a metric you can use com.signalfx.metrics.aws.AWSInstanceInfo. And either add it as a dimension in MetricMetadata or add it as a default dimension.

String instanceInfo = AWSInstanceInfo.get()
Timer t = metricMetadata
    .forBuilder(MetricBuilder.TIMERS)
    .withMetricName("request_time")
    .withDimension(AWSInstanceInfo.DIMENSION_NAME, instanceInfo)
    .createOrGet(metricRegistery);

/**
 * As default dimension
 */
final SignalFxReporter signalfxReporter = new SignalFxReporter.Builder(
    metricRegistry,
    "SIGNALFX_AUTH_TOKEN"
).addDimension(AWSInstanceInfo.DIMENSION_NAME, instanceInfo).build();

Example Project

You can find a full-stack example project called "signalfx-java-examples" in the repo.

Run it as follows:

1. Download the code and create an "auth" file in the "signalfx-java-examples" directory. The auth file should contain the following:

   auth=<signalfx API Token>
   host=https://ingest.signalfx.com
   

2. Run the following commands in your terminal to install and run the example project, replacing path/to/signalfx-java-examples with the location of the example project code in your environment. You must have Maven installed.

   cd path/to/signalfx-java-examples
   mvn install
   # an example for Yammer 2.x metrics
   mvn exec:java -Dexec.mainClass="com.signalfx.example.YammerExample"
   # an example for sending datapoints and events using protocol buffers
   mvn exec:java -Dexec.mainClass="com.signalfx.example.ProtobufExample"
   

New metrics and events from the example project should appear in SignalFx.

Sending metrics without using Codahale

We recommend sending metrics using Codahale as shown above. You can also interact with our Java library directly if you do not want to use Codahale. To do this, you will need to build the metric manually using protocol buffers as shown in the following example. Sending both datapoints and events are now supported using protocol buffers.

SignalFxReceiverEndpoint signalFxEndpoint = new SignalFxEndpoint();
AggregateMetricSender mf = new AggregateMetricSender("test.SendMetrics",
    new HttpDataPointProtobufReceiverFactory(signalFxEndpoint).setVersion(2),
    new HttpEventProtobufReceiverFactory(signalFxEndpoint),
    new StaticAuthToken(auth_token),
    Collections.<OnSendErrorHandler> singleton(new OnSendErrorHandler() {
        @Override
        public void handleError(MetricError metricError) {
            System.out.println("Unable to POST metrics: " + metricError.getMessage());
        }
    }));

try (AggregateMetricSender.Session i = mf.createSession()) {
    i.setDatapoint(
        SignalFxProtocolBuffers.DataPoint.newBuilder()
            .setMetric("curtime")
            .setMetricType(SignalFxProtocolBuffers.MetricType.GAUGE)
            .setValue(
                SignalFxProtocolBuffers.Datum.newBuilder()
                    .setIntValue(System.currentTimeMillis()))
            .addDimensions(
                SignalFxProtocolBuffers.Dimension.newBuilder()
                    .setKey("source")
                    .setValue("java"))
            .build());

    i.setEvent(
            SignalFxProtocolBuffers.Event.newBuilder()
                  .setEventType("Deployments")
                  .setCategory(SignalFxProtocolBuffers.EventCategory.USER_DEFINED)
                  .setTimestamp(System.currentTimeMillis())
                  .addDimensions(
                    SignalFxProtocolBuffers.Dimension.newBuilder()
                                      .setKey("source")
                                      .setValue("java"))
                  .addProperties(
                    SignalFxProtocolBuffers.Property.newBuilder()
                                    .setKey("version")
                                    .setValue(
                                            SignalFxProtocolBuffers.PropertyValue.newBuilder()
                                                    .setIntValue(2)
                                                    .build())
                                    .build())
                  .build());
}

Sending metrics through a http proxy

To send metrics through a http proxy one can set the standard java system properties used to control http protocol handling. There are 3 properties you can set to specify the proxy that will be used by the http protocol handler:

• http.proxyHost: the host name of the proxy server
• http.proxyPort: the port number, the default value being 80.
• http.nonProxyHosts: a list of hosts that should be reached directly, bypassing the proxy. This is a list of regular expressions separated by '|'. Any host matching one of these regular expressions will be reached through a direct connection instead of through a proxy.

Basic example:

$ java -Dhttp.proxyHost=webcache.mydomain.com -Dhttp.proxyPort=8080”

Example with directive to bypass proxy for localhost and host.mydomain.com:

$ java -Dhttp.proxyHost=webcache.mydomain.com -Dhttp.proxyPort=8080 -Dhttp.noProxyHosts=”localhost|host.mydomain.com”

Executing SignalFlow computations

SignalFlow is SignalFx's real-time analytics computation language. The SignalFlow API allows SignalFx users to execute real-time streaming analytics computations on the SignalFx platform. For more information, head over to our Developers documentation:

• SignalFlow Overview
• Getting started with the SignalFlow API

Executing a SignalFlow program is very simple with this client library:

String program = "data('cpu.utilization').mean().publish()";
SignalFlowClient flow = new SignalFlowClient("MY_TOKEN");
try {
    System.out.println("Executing " + program);
    Computation computation = flow.execute(program);
    for (ChannelMessage message : computation) {
        switch (message.getType()) {
        case DATA_MESSAGE:
            DataMessage dataMessage = (DataMessage) message;
            System.out.printf("%d: %s%n",
                    dataMessage.getLogicalTimestampMs(), dataMessage.getData());
            break;

        case EVENT_MESSAGE:
            EventMessage eventMessage = (EventMessage) message;
            System.out.printf("%d: %s%n",
                    eventMessage.getTimestampMs(),
                    eventMessage.getProperties());
            break;
        }
    }
}

Metadata about the timeseries is received from the iterable stream, and it is also automatically intercepted by the client library and made available through the Computation object returned by execute():

case DATA_MESSAGE:
    DataMessage dataMessage = (DataMessage) message;
    for (Map<String, Number> datum : dataMessage.getData()) {
        Map<String,Object> metadata = computation.getMetadata(datum.getKey());
        // ...
    }

License

Apache Software License v2. Copyright © 2014-2017 SignalFx