Docs » Supported integrations in Splunk Observability Cloud » Instrument back-end applications to send spans to Splunk APM » Instrument Java applications for Splunk Observability Cloud » Instrument your Java application for Splunk Observability Cloud

Instrument your Java application for Splunk Observability Cloud πŸ”—

The Java agent from the Splunk Distribution of OpenTelemetry Java can automatically instrument your Java application by injecting instrumentation to Java classes. To get started, use the guided setup or follow the instructions manually.

Generate customized instructions using the guided setup πŸ”—

To generate all the basic installation commands for your environment and application, use the Java guided setup. To access the Java guided setup, follow these steps:

  1. Log in to Splunk Observability Cloud.

  2. Open the Java guided setup . Optionally, you can navigate to the guided setup on your own:

    1. In the navigation menu, select Data Management.

    2. Go to the Available integrations tab, or select Add Integration in the Deployed integrations tab.

    3. In the integration filter menu, select By Product.

    4. Select the APM product.

    5. Select the Java tile to open the Java guided setup.

Install the Splunk Distribution of OpenTelemetry Java manually πŸ”—

If you don’t use the guided setup, follow these instructions to manually install the Splunk Distribution of OpenTelemetry Java:

Install and activate the Java agent πŸ”—

Follow these steps to automatically instrument your application using the Java agent:

  1. Check that you meet the requirements. See Java agent compatibility and requirements.

  2. Download the JAR file for the latest version of the agent:

    curl -L \
    -o splunk-otel-javaagent.jar
  3. Set the OTEL_SERVICE_NAME environment variable:

    export OTEL_SERVICE_NAME=<yourServiceName>
  4. (Optional) Set the endpoint URL if the Splunk Distribution of OpenTelemetry Collector is running on a different host:

    export OTEL_EXPORTER_OTLP_ENDPOINT=<yourCollectorEndpoint>:<yourCollectorPort>
  5. (Optional) Set the deployment environment and service version:

    export OTEL_RESOURCE_ATTRIBUTES='deployment.environment=<envtype>,service.version=<version>'
  6. Set the -javaagent argument to the path of the Java agent:

    java -javaagent:./splunk-otel-javaagent.jar -jar <myapp>.jar


    If your application runs on a supported Java server, see Define agent paths for Java application servers for Splunk Observability Cloud.

If no data appears in APM, see Troubleshoot Java instrumentation for Splunk Observability Cloud.

If you need to add custom attributes to spans or want to manually generate spans, instrument your Java application or service manually. See Manually instrument Java applications for Splunk Observability Cloud.

Activate AlwaysOn Profiling πŸ”—

To activate AlwaysOn Profiling, use the following system property argument. You can also use the SPLUNK_PROFILER_ENABLED environment variable. For more information, see Introduction to AlwaysOn Profiling for Splunk APM.

To activate memory profiling, set the splunk.profiler.memory.enabled system property or the SPLUNK_PROFILER_MEMORY_ENABLED environment variable to true after activating AlwaysOn Profiling.


OpenJDK versions 15.0 to 17.0.8 are not supported for memory profiling. See in the JDK bug system for more information.

The following example shows how to activate the profiler using the system property:

java -javaagent:./splunk-otel-javaagent.jar \
-Dsplunk.profiler.enabled=true \
-Dsplunk.profiler.memory.enabled=true \
-Dotel.exporter.otlp.endpoint=http(s)://collector:4318 \
-jar <your_application>.jar

See Get data into Splunk APM AlwaysOn Profiling for more information. For more settings, see Java settings for AlwaysOn Profiling.

Metrics collection πŸ”—

Starting from version 2.5.0, the Java agent collects metrics by default when instrumenting an application or service automatically. To migrate metric collection from version 1.x to 2.x, see Migration guide for OpenTelemetry Java 2.x metrics.

If your metrics endpoint is different than the default value, set the OTEL_EXPORTER_OTLP_METRICS_ENDPOINT environment variable. See Configure the Java agent for Splunk Observability Cloud for more information.

If you activate memory profiling, metrics collection is activated automatically and cannot be deactivated.


Metrics ingest might result in increased data ingest costs. To deactivate metrics collection, set the OTEL_METRICS_EXPORTER environment variable or the -Dotel.metrics.exporter property to none.

Logs collection πŸ”—

By default, the Java agent injects trace and span metadata automatically into logs. The agent then sends the annotated logs to the OpenTelemetry Collector, which exports them to Splunk Observability Cloud. For more information on trace-log correlation, see Connect Java trace data with logs for Splunk Observability Cloud.


Logs ingest might result in increased data ingest costs. To deactivate logs collection, set the OTEL_LOGS_EXPORTER environment variable or the -Dotel.logs.exporter property to none.

Ignore specific endpoints πŸ”—

By default, the Java agent collects traces from all the endpoints of your application. To ignore specific endpoints, use the rules sampler and define drop rules.

In the following example, the sampler drops all SERVER spans whose endpoints match healtcheck, and sends the rest of spans using the fallback sampler, parentbased_always_on:

export OTEL_TRACES_SAMPLER_ARG=drop=/healthcheck;fallback=parentbased_always_on

See Configure the Java agent for Splunk Observability Cloud for more information.

Configure the Java agent πŸ”—

You can configure the agent using environment variables or by setting system properties as runtime arguments. For more details about both methods, see Configuration methods.

For advanced configuration of the JVM agent, like changing trace propagation formats, correlating traces and logs, or activating custom sampling, see Configure the Java agent for Splunk Observability Cloud.

Deploy the Java agent in Kubernetes πŸ”—

To deploy the Java agent in Kubernetes, follow these steps:

  1. Edit the Dockerfile for your application image to add the following commands:

    # Adds the latest version of the Splunk Java agent
    ADD .
    # Modifies the entry point
    ENTRYPOINT ["java","-javaagent:splunk-otel-javaagent.jar","-jar","./<myapp>.jar"]
  2. Configure the Kubernetes Downward API to expose environment variables to Kubernetes resources.

    The following example shows how to update a deployment to expose environment variables by adding the agent configuration under the .spec.template.spec.containers.env section:

    apiVersion: apps/v1
    kind: Deployment
          app: your-application
          - name: myapp
                - name: SPLUNK_OTEL_AGENT
                      fieldPath: status.hostIP
                - name: OTEL_EXPORTER_OTLP_ENDPOINT
                value: "http://$(SPLUNK_OTEL_AGENT):4318"
                - name: OTEL_SERVICE_NAME
                value: "<serviceName>"
                - name: OTEL_RESOURCE_ATTRIBUTES
                value: "deployment.environment=<environmentName>"


You can also deploy instrumentation using the Kubernetes Operator. See Automatic discovery and configuration for back-end applications in Kubernetes for more information.

Deploy the Java agent in Cloudfoundry πŸ”—

To instrument a Java application in Cloudfoundry, use the Splunk OpenTelemetry Java Agent buildpack framework. The framework automatically instruments your application to send traces to Splunk Observability Cloud.

See for instructions.

Send data directly to Splunk Observability Cloud πŸ”—

By default, the agent sends all telemetry to the local instance of the Splunk Distribution of OpenTelemetry Collector.

If you need to send data directly to Splunk Observability Cloud, set the following environment variables:

export SPLUNK_ACCESS_TOKEN=<access_token>
export SPLUNK_REALM=<realm>

To obtain an access token, see Retrieve and manage user API access tokens using Splunk Observability Cloud.

To find your Splunk realm, see Note about realms.

For more information on the ingest API endpoints, see Send APM traces .


This procedure applies to spans and traces. To send AlwaysOn Profiling data, you must use the OTel Collector.

Set the source host πŸ”—

To override the host used by the agent, use the environment variable OTEL_RESOURCE_ATTRIBUTES to set your host’s name to the desired source:


Instrument Lambda functions πŸ”—

You can instrument AWS Lambda functions using the Splunk OpenTelemetry Lambda Layer. See Instrument your AWS Lambda function for Splunk Observability Cloud for more information.

Upgrade the Splunk Distribution of OpenTelemetry Java πŸ”—

New releases of the Splunk Distribution of OpenTelemetry Java happen after a new upstream release, or when new features and enhancements are available.

Upgrade to each new version of the Splunk Distribution of OpenTelemetry Java after it’s released. To find out about new releases, watch the GitHub repository at


See the versioning document in GitHub to learn more about version numbers. Major versions contain a large number of changes, which might result in increased risk to your production environment. Minor version changes indicate common releases, which contain a modest number of changes Patch releases are infrequent and contain specific fixes or enhancements.

Best practices for upgrades πŸ”—

To reduce the risk of issues with an upgrade, do the following:

  • See the release notes and changelog for each release to determine if the release has changes that might affect your environment. Pay attention to mentions of libraries, frameworks, and tools that your software uses.

  • Never put untested code into production. Verify that the new build works in a staging or pre-production environment before promoting it to production. Don’t use snapshot builds in production.

  • Use canary instances. Let the canaries operate with the code before releasing the code to production. Run the canaries for at least a few hours, and preferably for a few days.

  • Minimize the number of dependencies, including instrumentation, that change in a given release. Determining the root cause of a problem after upgrading multiple dependencies at the same time can be difficult.

  • Pin version numbers in your build pipeline. Don’t use the latest URL in automated processes.

This page was last updated on Jul 05, 2024.