Parse data using ingest node pipelinesedit

Deprecated in 7.16.0.

Users should now use the APM integration (Elastic Agent)

You can configure APM Server to use an ingest node to pre-process documents before indexing them in Elasticsearch. A pipeline definition specifies the series of pipelines or processors that will transform each document in a specific way. For example, a pipeline might define one processor that removes a field, followed by another that renames a field.

Pipelines can be used to ensure data security by removing or obfuscating sensitive information. See data security for an example.

Default ingest pipelineedit

By default, APM Server registers the apm pipeline definition to Elasticsearch on startup. The apm pipeline defines the following inner pipelines:

apm_user_agent

Adds user_agent information for APM events

apm_user_geo

Enriches Elastic’s JavaScript RUM Agent data by adding user Geo-IP data to the client.geo field.

apm_ingest_timestamp

Adds an ingest timestamp for APM events.

apm_remove_span_metadata

[7.7] Added in 7.7. Upgrading? See upgrading to 7.7 To save storage, removes metadata fields, like host, kubernetes, and container, that are already available on the parent transaction.

In previous versions of APM Server, this functionality was hardcoded internally. Switching metadata cleanup from an internal process to a processor allows you to keep any span metadata that is important in your architecture.

apm_error_grouping_name

[7.13] Added in 7.13. Adds error.grouping_name to error documents for use in the Kibana APM UI.

apm_opentelemetry_metrics

[7.13] Added in 7.13. Copies well-known OpenTelemetry metrics to their Elastic APM counterparts, for vizualisation in the Kibana APM UI. For example, the OpenTelemetry metric field runtime.jvm.gc.time is copied to the Elastic APM metric field jvm.gc.time.

Metrics are duplicated so you can refer to them by either the OpenTelemetry or Elastic APM metric name.

See the complete pipeline definition by navigating to the APM Server’s home directory and viewing ingest/pipeline/definition.json.

To disable this, or any other pipeline, set output.elasticsearch.pipeline: _none.

Custom pipelinesedit

Using custom pipelines involves two steps:

  1. First, you need to register a pipeline in Elasticsearch.
  2. Then, the pipeline needs to be applied during data ingestion.

Register pipelines in Elasticsearchedit

To register a pipeline in Elasticsearch, you can either configure APM Server to register pipelines on startup, or you can manually upload a pipeline definition.

Register pipelines on APM Server startupedit

Automatic pipeline registration requires output.elasticsearch to be enabled and configured.

Navigate to APM Server’s home directory and find the default pipeline configuration at ingest/pipeline/definition.json. To add, change, or remove pipelines in Elasticsearch, change the definitions in this file and restart your APM Server or run apm-server setup --pipelines.

By default, pipeline registration is enabled.

Manually upload pipeline definitionsedit

You can manually upload pipeline definitions by describing them in a file. Consider the following sample pipeline in a file named pipeline.json. This pipeline definition converts the value of beat.name to lowercase before indexing each document.

{
    "description": "Test pipeline",
    "processors": [
        {
            "lowercase": {
                "field": "beat.name"
            }
        }
    ]
}

To register this pipeline, run:

curl -H 'Content-Type: application/json' -XPUT 'http://localhost:9200/_ingest/pipeline/test-pipeline' -d @pipeline.json

Apply pipelines during data ingestionedit

To specify which pipelines to apply during data ingestion, add the pipeline IDs to the pipelines option under output.elasticsearch in the apm-server.yml file:

output.elasticsearch:
  pipelines:
  - pipeline: "test-pipeline"

More information and examples for applying pipelines is available in the Elasticsearch output pipeline documentation.