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Getting started with Data Prepper

Data Prepper is an independent component, not an OpenSearch plugin, that converts data for use with OpenSearch. It’s not bundled with the all-in-one OpenSearch installation packages.

If you are migrating from Open Distro Data Prepper, see Migrating from Open Distro.

1. Installing Data Prepper

There are two ways to install Data Prepper: you can run the Docker image or build from source.

The easiest way to use Data Prepper is by running the Docker image. We suggest that you use this approach if you have Docker available. Run the following command:

docker pull opensearchproject/data-prepper:latest

If you have special requirements that require you to build from source, or if you want to contribute, see the Developer Guide.

2. Configuring Data Prepper

Two configuration files are required to run a Data Prepper instance. Optionally, you can configure a Log4j 2 configuration file. See Configuring Log4j for more information. The following list describes the purpose of each configuration file:

  • pipelines.yaml: This file describes which data pipelines to run, including sources, processors, and sinks.
  • data-prepper-config.yaml: This file contains Data Prepper server settings that allow you to interact with exposed Data Prepper server APIs.
  • (optional): This file contains Log4j 2 configuration options and can be a JSON, YAML, XML, or .properties file type.

For Data Prepper versions earlier than 2.0, the .jar file expects the pipeline configuration file path to be followed by the server configuration file path. See the following configuration path example:

java -jar data-prepper-core-$VERSION.jar pipelines.yaml data-prepper-config.yaml

Optionally, you can add "-Dlog4j.configurationFile=config/" to the command to pass a custom Log4j 2 configuration file. If you don’t provide a properties file, Data Prepper defaults to the file in the shared-config directory.

Starting with Data Prepper 2.0, you can launch Data Prepper by using the following data-prepper script that does not require any additional command line arguments:


Configuration files are read from specific subdirectories in the application’s home directory:

  1. pipelines/: Used for pipeline configurations. Pipeline configurations can be written in one or more YAML files.
  2. config/data-prepper-config.yaml: Used for the Data Prepper server configuration.

You can supply your own pipeline configuration file path followed by the server configuration file path. However, this method will not be supported in a future release. See the following example:

bin/data-prepper pipelines.yaml data-prepper-config.yaml

The Log4j 2 configuration file is read from the config/ file located in the application’s home directory.

To configure Data Prepper, see the following information for each use case:

  • Trace analytics: Learn how to collect trace data and customize a pipeline that ingests and transforms that data.
  • Log analytics: Learn how to set up Data Prepper for log observability.

3. Defining a pipeline

Create a Data Prepper pipeline file named pipelines.yaml using the following configuration:

  workers: 2
  delay: "5000"
    - stdout:

4. Running Data Prepper

Run the following command with your pipeline configuration YAML.

docker run --name data-prepper \
    -v /${PWD}/pipelines.yaml:/usr/share/data-prepper/pipelines/pipelines.yaml \

The example pipeline configuration above demonstrates a simple pipeline with a source (random) sending data to a sink (stdout). For examples of more advanced pipeline configurations, see Pipelines.

After starting Data Prepper, you should see log output and some UUIDs after a few seconds:

2021-09-30T20:19:44,147 [main] INFO - Data Prepper server running at :4900
2021-09-30T20:19:44,681 [random-source-pool-0] INFO - Writing to buffer
2021-09-30T20:19:45,183 [random-source-pool-0] INFO - Writing to buffer
2021-09-30T20:19:45,687 [random-source-pool-0] INFO - Writing to buffer
2021-09-30T20:19:46,191 [random-source-pool-0] INFO - Writing to buffer
2021-09-30T20:19:46,694 [random-source-pool-0] INFO - Writing to buffer
2021-09-30T20:19:47,200 [random-source-pool-0] INFO - Writing to buffer
2021-09-30T20:19:49,181 [simple-test-pipeline-processor-worker-1-thread-1] INFO -  simple-test-pipeline Worker: Processing 6 records from buffer

The remainder of this page provides examples for running Data Prepper from the Docker image. If you built it from source, refer to the Developer Guide for more information.

However you configure your pipeline, you’ll run Data Prepper the same way. You run the Docker image and modify both the pipelines.yaml and data-prepper-config.yaml files.

For Data Prepper 2.0 or later, use this command:

docker run --name data-prepper -p 4900:4900 -v ${PWD}/pipelines.yaml:/usr/share/data-prepper/pipelines/pipelines.yaml -v ${PWD}/data-prepper-config.yaml:/usr/share/data-prepper/config/data-prepper-config.yaml opensearchproject/data-prepper:latest

For Data Prepper versions earlier than 2.0, use this command:

docker run --name data-prepper -p 4900:4900 -v ${PWD}/pipelines.yaml:/usr/share/data-prepper/pipelines.yaml -v ${PWD}/data-prepper-config.yaml:/usr/share/data-prepper/data-prepper-config.yaml opensearchproject/data-prepper:1.x

Once Data Prepper is running, it processes data until it is shut down. Once you are done, shut it down with the following command:

POST /shutdown

Additional configurations

For Data Prepper 2.0 or later, the Log4j 2 configuration file is read from config/ in the application’s home directory. By default, it uses in the shared-config directory.

For Data Prepper 1.5 or earlier, optionally add "-Dlog4j.configurationFile=config/" to the command if you want to pass a custom log4j2 properties file. If no properties file is provided, Data Prepper defaults to the file in the shared-config directory.

Next steps

Trace analytics is an important Data Prepper use case. If you haven’t yet configured it, see Trace analytics.

Log ingestion is also an important Data Prepper use case. To learn more, see Log analytics.

To learn how to run Data Prepper with a Logstash configuration, see Migrating from Logstash.

For information on how to monitor Data Prepper, see Monitoring.

More examples

For more examples of Data Prepper, see examples in the Data Prepper repo.

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