The pipeline management feature centralizes the creation andmanagement of Logstash configuration pipelines in Kibana.
Centralized pipeline management is an X-Pack feature that is not includedwith the basic license. If you want to try all of the features, you can start a30-day trial. At the end of the trial period, you can purchase a subscription tokeep using the full functionality of the X-Pack components. For moreinformation, see https://www.elastic.co/subscriptions andLicenseManagement.
You can control multiple Logstash instances from the pipeline management UI inKibana. You can add, edit, and delete pipeline configurations. On the Logstashside, you simply need to enable configuration management and register Logstashto use the centrally managed pipeline configurations.
After you configure Logstash to use centralized pipeline management, you canno longer specify local pipeline configurations. The pipelines.yml file andsettings such as path.config and config.string are inactive when centralizedpipeline management is enabled.
Before using the pipeline management UI, you must:
- Configure centralized pipeline management.
- If Kibana is protected with basic authentication, make sure your Kibana user hasthe
logstash_adminrole as well as thelogstash_writerrole that you createdwhen you configured Logstash to use basic authentication. Additionally,in order to view (as read-only) non-centrally-managed pipelines in the pipeline managementUI, make sure your Kibana user has themonitoring_userrole as well.
To manage Logstash pipelines in Kibana:
Open Kibana in your browser and go to the Management tab. If you’ve set upconfiguration management correctly, you’ll see an area for managing Logstash.
- Click the Pipelines link.
To add a new pipeline, click Create pipeline and specify values.
Pipeline ID
A name that uniquely identifies the pipeline. This is the ID that you used whenyouconfigured centralized pipeline managementand specified a list of pipeline IDs in the
xpack.management.pipeline.idsetting.Description
A description of the pipeline configuration. This information is for your use.
Pipeline
The pipeline configuration. You can treat the editor in the pipeline managementUI like any other editor. You don’t have to worry about whitespace or indentation.
Pipeline workers
The number of parallel workers used to run the filter and output stages of the pipeline.
Pipeline batch size
The maximum number of events an individual worker thread collects beforeexecuting filters and outputs.
Pipeline batch delay
Time in milliseconds to wait for each event before sending an undersizedbatch to pipeline workers.
Queue type
The internal queueing model for event buffering. Options are memory forin-memory queueing, or persisted for disk-based acknowledged queueing.
Queue max bytes
The total capacity of the queue.
Queue checkpoint writes
The maximum number of events written before a checkpoint is forced whenpersistent queues are enabled.
- The pipeline configurations and metadata are stored in Elasticsearch. Anychanges that you make to a pipeline definition are picked up and loadedautomatically by all Logstash instances registered to use the pipeline. Thechanges are applied immediately. If Logstash is registered to use the pipeline,you do not have to restart Logstash to pick up the changes.
- The pipeline runs on all Logstash instances that are registered to use thepipeline. Kibana saves the new configuration, and Logstash will attempt to loadit. There is no validation done at the UI level.
- You need to check the local Logstash logs for configuration errors. If you’reusing the Logstash monitoring feature in X-Pack, use the Monitoring tab tocheck the status of your Logstash nodes.
- You can specify multiple pipeline configurations that run in parallel on thesame Logstash node.
- If you edit and save a pipeline configuration, Logstash reloadsthe configuration in the background and continues processing events.
- If you try to delete a pipeline that is running (for example,
apache) in Kibana, Logstash willattempt to stop the pipeline. Logstash waits until allevents have been fully processed by the pipeline. Before you delete a pipeline,make sure you understand your data sources. Stopping a pipeline maylead to data loss.