Available on: Enterprise Edition

Configure Kestra to use Elasticsearch as a repository and indexer.

Elasticsearch is an Enterprise Edition functionality.

The most important thing is to configure the way Kestra connects to the Elasticsearch cluster.

Here is a minimal configuration example:

yaml
kestra:
  elasticsearch:
    client:
      http-hosts: "http://localhost:9200"
  repository:
    type: elasticsearch

Here is another example with a secured Elasticsearch cluster with basic authentication:

yaml
kestra:
  elasticsearch:
    client:
      http-hosts:
        - "http://node-1:9200"
        - "http://node-2:9200"
        - "http://node-3:9200"
      basic-auth:
        username: "<your-user>"
        password: "<your-password>"
  repository:
    type: elasticsearch

kestra.elasticsearch.client.trust-all-ssl

Default false, if you enable this option, we trust all certificate during connection. Useful for development server with self-signed certificate.

yaml
kestra:
  elasticsearch:
    client:
      http-hosts: "https://localhost:9200"
      trust-all-ssl: true

kestra.elasticsearch.defaults.indice-prefix

This configuration allows to change the indices prefix. By default, the prefix will be kestra_.

For example, if you want to share a common Elasticsearch cluster for multiple instances of Kestra, add a different prefix for each instance like this:

yaml
kestra:
  elasticsearch:
    defaults:
      indice-prefix: "uat_kestra"

kestra.elasticsearch.indices

By default, a unique indices is used for all different datas, it could be useful to split index by day / week / month to avoid having large indices in ElasticSearch. For now, executions, logs & metrics can be split, and we support all this split type:

  • DAILY
  • WEEKLY
  • MONTHLY
  • YEARLY
yaml
kestra:
  elasticsearch:
    indices:
      executions:
        alias: daily
      logs:
        alias: daily
      metrics:
        alias: daily

kestra.elasticsearch.client.trust-all-ssl

kestra.indexer

Indexer send data from Kafka to Elasticsearch using Bulk Request. You can control the batch size and frequency to reduce the load on ElasticSearch. This will delay some information on the UI raising that values, example:

yaml
kestra:
  indexer:
    batch-size: 500 # (default value, any integer > 0)
    batch-duration: PT1S # (default value, any duration)

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