opentelemetry-java-instrumentation/examples/rest-spark

REST Spark

This project provides a simple REST API using the Spark web framework. Even if the framework is not directly supported, manual instrumentation is used to trace one of the endpoints. A MongoClient is traced so that Mongo calls are part of the Spark trace.

Run the demo

Prerequisites

Be sure to build the project so that the latest version of dd-trace-java components are used. You can build all libraries and examples launching from the dd-trace-java root folder:

./gradlew clean shadowJar

Then you can prepare the distributable version of the rest-spark as follows:

cd examples/rest-spark
./gradlew installDist

Then you can start all services via Docker:

DD_API_KEY=<your_datadog_api_key> docker-compose up -d

A valid DD_API_KEY is required to post collected traces to the Datadog backend.

Run the application

Launch the application using the run wrapper you've built during the installDist step:

JAVA_OPTS=-javaagent:../../dd-java-agent/build/libs/dd-java-agent-{version}.jar -Ddd.service.name=rest-spark build/install/rest-spark/bin/rest-spark

0.2.0-SNAPSHOT is an example of what {version} looks like.

Generate traces

With your web browser

Once the application runs. Go to the following url:

• http://localhost:4567/key/something
• http://localhost:4567/key/something_else

Then get back to Datadog and wait a bit to see a trace coming.

Auto-instrumentation with the dd-trace-agent

The instrumentation is entirely done by the Java Agent which embed a set of rules that automatically recognizes & instruments:

• The Mongo client

The Java Agent embeds the OpenTracing Java Agent.