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.
- Java 6+ with
signalfx-metrics
.
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>0.0.48</version>
</dependency>
- To work with Yammer Metrics 2.0.x:
<dependency>
<groupId>com.signalfx.public</groupId>
<artifactId>signalfx-yammer</artifactId>
<version>0.0.48</version>
</dependency>
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" % "0.0.48"
- To work with Yammer Metrics 2.0.x:
libraryDependencies += "com.signalfx.public" % "signalfx-yammer" % "0.0.48"
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] ------------------------------------------------------------------------
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();
final SfxMetrics metrics = new SfxMetrics(metricRegistry, metricMetadata);
// This will send the current time in ms to SignalFx as a gauge
metrics.registerGauge("gauge", new Gauge<Long>() {
public Long getValue() {
return System.currentTimeMillis();
}
});
/*
* 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);
metrics.registerGauge("queue_size", new Gauge<Long>() {
@Override
public Long getValue() {
return customerQueue.size();
}
}, "queue_name", "customer_backlog");
We recommend creating your Codahale object as a field of your class (a
Counter
, Gauge<?>
, Histogram
or Timer
) then using that field to
increment or update values. If you don't want to maintain this for reasons of
code cleanliness, you can always just create it on the fly.
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 = metrics.timer("request_time", "storename", "electronics");
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");
* }
*/
// Or on the fly:
Timer.Context c = metrics.timer("request_time").time();
try {
// Do something
} finally {
c.close();
}
After setting up a SignalFxReporter, you can use Codahale metrics as you
normally would, reported at the frequency configured by the SignalFxReporter
.
You can also use this library with Yammer metrics 2.0.x as shown in the following examples.
final MetricsRegistry metricsRegistry = new MetricsRegistry();
final SignalFxReporter signalfxReporter = new SignalFxReporter.Builder(
metricsRegistry,
"SIGNALFX_AUTH_TOKEN"
).build();
signalfxReporter.start(1, TimeUnit.SECONDS);
final MetricMetadata metricMetadata = signalfxReporter.getMetricMetadata();
Note: the SfxMetrics
helper is not supported for 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();
}
});
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");
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();
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
SignalFxReporter.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
addUniqueDimension()/addUniqueDimensions()
on the
SignalFxReporter.Builder
object.
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 = metrics.timer("request_time", AWSInstanceInfo.DIMENSION_NAME, instanceInfo);
/**
* As default dimension
*/
final SignalFxReporter signalfxReporter = new SignalFxReporter.Builder(
metricRegistry,
"SIGNALFX_AUTH_TOKEN"
).addUniqueDimension(AWSInstanceInfo.DIMENSION_NAME, instanceInfo).build();
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());
}
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 serverhttp.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”
By default, the Java library compresses datapoint payloads when sending them to
SignalFx. This can provide significant egress volume savings when sending data
to SignalFx's ingest API. This behavior can be disabled by setting the
com.signalfx.public.java.disableHttpCompression
system property to true
:
$ java -Dcom.signalfx.public.java.disableHttpCompression=true ...
You can find a full-stack example project called "signalfx-java-examples" in the repo.
Run it as follows:
-
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
-
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.
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:
Executing a SignalFlow program is very simple with this client library:
String program = "data('cpu.utilization').mean().publish()";
SignalFlowClient flow = new SignalFlowClient("MY_TOKEN");
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());
// ...
}
Apache Software License v2. Copyright © 2014-2017 SignalFx