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Agent processors [elastic-agent-processor-configuration]

{{agent}} processors are lightweight processing components that you can use to parse, filter, transform, and enrich data at the source. For example, you can use processors to:

  • reduce the number of exported fields
  • enhance events with additional metadata
  • perform additional processing and decoding
  • sanitize data

Each processor receives an event, applies a defined action to the event, and returns the event. If you define a list of processors, they are executed in the order they are defined.

event -> processor 1 -> event1 -> processor 2 -> event2 ...

::::{note} {{agent}} processors execute before ingest pipelines, which means that your processor configurations cannot refer to fields that are created by ingest pipelines or {{ls}}. For more limitations, refer to What are some limitations of using processors? ::::

Where are processors valid? [where-valid]

The processors described in this section are valid:

  • Under integration settings in the Integrations UI in {{kib}}. For example, when configuring an Nginx integration, you can define processors for a specific dataset under Advanced options. The processor in this example adds geo metadata to the Nginx access logs collected by {{agent}}:

    :::{image} images/add-processor.png :alt: Screen showing how to add a processor to an integration policy :screenshot: :::

    ::::{note} Some integrations do not currently support processors. ::::

  • Under input configuration settings for standalone {{agent}}s. For example:

    inputs:
  - type: logfile
    use_output: default
    data_stream:
      namespace: default
    streams:
      - data_stream:
          dataset: nginx.access
          type: logs
        ignore_older: 72h
        paths:
          - /var/log/nginx/access.log*
        tags:
          - nginx-access
        exclude_files:
          - .gz$
        processors:
          - add_host_metadata:
              cache.ttl: 5m
              geo:
                name: nyc-dc1-rack1
                location: '40.7128, -74.0060'
                continent_name: North America
                country_iso_code: US
                region_name: New York
                region_iso_code: NY
                city_name: New York
          - add_locale: null

You can define processors that apply to a specific input defined in the configuration. Applying a processor to all the inputs on a global basis is currently not supported.

What are some limitations of using processors? [limitations]

Processors have the following limitations.

  • Cannot enrich events with data from {{es}} or other custom data sources.
  • Cannot process data after it’s been converted to the Elastic Common Schema (ECS) because the conversion is performed by {{es}} ingest pipelines. This means that your processor configuration cannot refer to fields that are created by ingest pipelines or {{ls}} because those fields are created after the processor runs, not before.
  • May break integration ingest pipelines in {{es}} if the user-defined processing removes or alters fields expected by ingest pipelines.
  • If you create new fields using processors, you are responsible for setting up field mappings in the *-@custom component template and making sure the new mappings are aligned with ECS.

What other options are available for processing data? [processing-options]

The {{stack}} provides several options for processing data collected by {{agent}}. The option you choose depends on what you need to do:

If you need to… Do this…
Sanitize or enrich raw data at the source Use an {{agent}} processor
Convert data to ECS, normalize field data, or enrich incoming data Use ingest pipelines
Define or alter the schema at query time Use runtime fields
Do something else with your data Use Logstash plugins

How are {{agent}} processors different from {{ls}} plugins or ingest pipelines? [how-different]

Logstash plugins and ingest pipelines both require you to send data to another system for processing. Processors, on the other hand, allow you to apply processing logic at the source. This means that you can filter out data you don’t want to send across the connection, and you can spread some of the processing load across host systems running on edge nodes.