Delete anomaly detection jobs APIedit

Deletes an existing anomaly detection job.


DELETE _ml/anomaly_detectors/<job_id>


  • Requires the manage_ml cluster privilege. This privilege is included in the machine_learning_admin built-in role.
  • Before you can delete a job, you must delete the datafeeds that are associated with it. See Delete datafeeds.
  • Before you can delete a job, you must close it (unless you specify the force parameter). See Close jobs.


All job configuration, model state and results are deleted.

Deleting an anomaly detection job must be done via this API only. Do not delete the job directly from the .ml-* indices using the Elasticsearch delete document API. When Elasticsearch security features are enabled, make sure no write privileges are granted to anyone over the .ml-* indices.

It is not currently possible to delete multiple jobs using wildcards or a comma separated list.

Path parametersedit

(Required, string) Identifier for the anomaly detection job.

Query parametersedit

(Optional, Boolean) Use to forcefully delete an opened job; this method is quicker than closing and deleting the job.
(Optional, boolean) Specifies whether the request should return immediately or wait until the job deletion completes. Defaults to true.


DELETE _ml/anomaly_detectors/total-requests

When the job is deleted, you receive the following results:

  "acknowledged": true

In the next example we delete the total-requests job asynchronously:

DELETE _ml/anomaly_detectors/total-requests?wait_for_completion=false

When wait_for_completion is set to false, the response contains the id of the job deletion task:

  "task": "oTUltX4IQMOUUVeiohTt8A:39"