Getting Started

The Datadog Profiler requires JDK Flight Recorder. The Datadog Profiler library is supported in OpenJDK 11+, Oracle Java 11+, OpenJDK 8 (version 8u262+) and Zulu Java 8+ (minor version 1.8.0_212+). All JVM-based languages, such as Scala, Groovy, Kotlin, and Clojure are supported. To begin profiling applications:

1. If you are already using Datadog, upgrade your agent to version 7.20.2+ or 6.20.2+. If you don’t have APM enabled to set up your application to send data to Datadog, in your Agent, set the DD_APM_ENABLED environment variable to true and listening to the port 8126/TCP.

2. Download dd-java-agent.jar, which contains the Java Agent class files:

   wget -O dd-java-agent.jar 'https://repository.sonatype.org/service/local/artifact/maven/redirect?r=central-proxy&g=com.datadoghq&a=dd-java-agent&v=LATEST'
   

   Note: Profiler is available in the dd-java-agent.jar library in versions 0.55+.

3. Set -Ddd.profiling.enabled flag or DD_PROFILING_ENABLED environment variable to true. Update to your service invocation should look like:

   java -javaagent:dd-java-agent.jar -Ddd.profiling.enabled=true -XX:FlightRecorderOptions=stackdepth=256 -jar <YOUR_SERVICE>.jar <YOUR_SERVICE_FLAGS>
   

4. After a minute or two, visualize your profiles on the Datadog APM > Profiling page.

Note:

• The -javaagent argument needs to be before -jar, adding it as a JVM option rather than an application argument. For more information, see the Oracle documentation:

  # Good:
  java -javaagent:dd-java-agent.jar ... -jar my-service.jar -more-flags
  # Bad:
  java -jar my-service.jar -javaagent:dd-java-agent.jar ...
  

• We strongly recommend that you specify the service and version as this gives you the ability to slice and dice your profiles across these dimensions. Use environment variables to set the parameters:

The Datadog Profiler requires Python 2.7+. Memory profiling is available on Python 3.5+. To begin profiling applications:

1. If you are already using Datadog, upgrade your agent to version 7.20.2+ or 6.20.2+.

2. Install ddtrace which contains both tracing and profiler:

   pip install ddtrace
   

   Note: Profiler is available in the ddtrace library for versions 0.36+.

3. To automatically profile your code, set DD_PROFILING_ENABLED environment variable to true when you use ddtrace-run:

   DD_PROFILING_ENABLED=true ddtrace-run python app.py
   

   Note: DD_PROFILING_ENABLED is only supported in dd-trace version 0.40+. Use the alternate method if you are running an older version of dd-trace.

   Alternate method

   If you prefer to instrument the profiler through code, import ddtrace.profile.auto. After import, the Profiler starts:

   import ddtrace.profiling.auto
   

4. After a minute or two, visualize your profiles on the Datadog APM > Profiler page.

• It is strongly recommended to add tags like service or version as it provides the ability to slice and dice your profiles across these dimensions, enhancing your overall product experience. Use environment variables to set the parameters:

• When your process forks using os.fork, the profiler is stopped in the child process.

  For Python 3.7+ on POSIX platforms, a new profiler is started if you enabled the profiler via ddtrace-run or ddtrace.profiling.auto.

  If you manually create a Profiler(), use Python < 3.6, or run on a non-POSIX platform, manually restart the profiler in your child with:

  ddtrace.profiling.auto.start_profiler()
  

• If you want to manually control the lifecycle of the profiler, use the ddtrace.profiling.profiler.Profiler object:

  from ddtrace.profiling import Profiler
  
  prof = Profiler()
  prof.start()
  
  # At shutdown
  prof.stop()
  

The Datadog Profiler requires Go 1.12+. To begin profiling applications:

1. If you are already using Datadog, upgrade your agent to version 7.20.2+ or 6.20.2+.

2. Get dd-trace-go using the command:

   go get gopkg.in/DataDog/dd-trace-go.v1
   

   Note: Profiler is available in the dd-trace-go library for versions 1.23.0+.

3. Import the profiler at the start of your application:

   import "gopkg.in/DataDog/dd-trace-go.v1/profiler"
   

4. Add the following snippet to start the profiler:

   err := profiler.Start(
       profiler.WithService("<SERVICE_NAME>"),
       profiler.WithEnv("<ENVIRONMENT>"),
       profiler.WithVersion("<APPLICATION_VERSION>"),
       profiler.WithTags("<KEY1>:<VALUE1>,<KEY2>:<VALUE2>"),
   )
   if err != nil {
       log.Fatal(err)
   }
   defer profiler.Stop()
   

5. After a minute or two, visualize your profiles in the Datadog APM > Profiler page.

Note:

• By default only the CPU and Heap profile are enabled. Use profiler.WithProfileTypes to enable additional profile types.

• You can set profiler parameters in code with these functions:

• Alternatively you can set profiler configuration using environment variables: