- Metricbeat Reference: other versions:
- Overview
- Contributing to Beats
- Getting started with Metricbeat
- Setting up and running Metricbeat
- Upgrading Metricbeat
- How Metricbeat works
- Configuring Metricbeat
- Specify which modules to run
- Specify general settings
- Load external configuration files
- Configure the internal queue
- Configure the output
- Specify SSL settings
- Filter and enhance the exported data
- Parse logs by using ingest node
- Set up project paths
- Set up the Kibana endpoint
- Load the Kibana dashboards
- Load the Elasticsearch index template
- Set up logging
- Use environment variables in the configuration
- YAML tips and gotchas
- Regular expression support
- metricbeat.reference.yml
- Modules
- Aerospike module
- Apache module
- Ceph module
- Couchbase module
- Docker module
- Dropwizard module
- Elasticsearch module
- Golang module
- HAProxy module
- HTTP module
- Jolokia module
- Kafka module
- Kibana module
- Kubernetes module
- Kubernetes container metricset
- Kubernetes event metricset
- Kubernetes node metricset
- Kubernetes pod metricset
- Kubernetes state_container metricset
- Kubernetes state_deployment metricset
- Kubernetes state_node metricset
- Kubernetes state_pod metricset
- Kubernetes state_replicaset metricset
- Kubernetes system metricset
- Kubernetes volume metricset
- Memcached module
- MongoDB module
- MySQL module
- Nginx module
- PHP-FPM module
- PostgreSQL Module
- Prometheus module
- RabbitMQ module
- Redis module
- System module
- vSphere module
- Windows module
- ZooKeeper module
- Exported Fields
- Aerospike Fields
- Apache Fields
- Beat Fields
- Ceph Fields
- Cloud Provider Metadata Fields
- Common Fields
- Couchbase Fields
- docker Fields
- Docker Fields
- Dropwizard Fields
- Elasticsearch Fields
- Golang Fields
- HAProxy Fields
- HTTP Fields
- Jolokia Fields
- Kafka Fields
- Kibana Fields
- kubernetes Fields
- Kubernetes Fields
- Memcached Fields
- MongoDB Fields
- MySQL Fields
- Nginx Fields
- PHP-FPM Fields
- PostgreSQL Fields
- Prometheus Fields
- RabbitMQ Fields
- Redis Fields
- System Fields
- vSphere Fields
- Windows Fields
- ZooKeeper Fields
- Securing Metricbeat
- Troubleshooting
WARNING: Version 6.0 of Metricbeat has passed its EOL date.
This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.
Parse logs by using ingest node
editParse logs by using ingest node
editWhen you use Elasticsearch for output, you can configure Metricbeat to use ingest node to pre-process documents before the actual indexing takes place in Elasticsearch. Ingest node is a convenient processing option when you want to do some extra processing on your data, but you do not require the full power of Logstash. For example, you can create an ingest node pipeline in Elasticsearch that consists of one processor that removes a field in a document followed by another processor that renames a field.
After defining the pipeline in Elasticsearch, you simply configure your Beat to use the pipeline. To configure
Metricbeat, you specify the pipeline ID in the parameters
option under elasticsearch
in the
metricbeat.yml
file:
output.elasticsearch: hosts: ["localhost:9200"] pipeline: my_pipeline_id
For example, let’s say that you’ve defined the following pipeline in a file named pipeline.json
:
{ "description": "Test pipeline", "processors": [ { "lowercase": { "field": "beat.name" } } ] }
To add the pipeline in Elasticsearch, you would run:
curl -H 'Content-Type: application/json' -XPUT 'http://localhost:9200/_ingest/pipeline/test-pipeline' -d@pipeline.json
Then in the metricbeat.yml
file, you would specify:
output.elasticsearch: hosts: ["localhost:9200"] pipeline: "test-pipeline"
When you run Metricbeat, the value of beat.name
is converted to lowercase before indexing.
For more information about defining a pre-processing pipeline, see the Ingest Node documentation.