elasticsearch/docs/reference/autoscaling/deciders/machine-learning-decider.asciidoc

[role="xpack"]
[testenv="enterprise"]
[[autoscaling-machine-learning-decider]]
=== Machine learning decider

The {ml} decider (`ml`) calculates the memory required to run
{ml} jobs created by users.

The {ml} decider is enabled for policies governing `ml` nodes.

[[autoscaling-machine-learning-decider-settings]]
==== Configuration settings

`num_anomaly_jobs_in_queue`::
(Optional, integer)
Number of queued anomaly jobs to allow. Defaults to `0`.

`num_analytics_jobs_in_queue`::
(Optional, integer)
Number of queued analytics jobs to allow. Defaults to `0`.

`down_scale_delay`::
(Optional, <<time-units,time value>>)
Delay before scaling down. Defaults to 1 hour.

[[autoscaling-machine-learning-decider-examples]]
==== {api-examples-title}

This example puts an autoscaling policy named `my_autoscaling_policy`,
overriding the machine learning decider's configuration.

[source,console]
--------------------------------------------------
PUT /_autoscaling/policy/my_autoscaling_policy
{
  "roles" : [ "ml" ],
  "deciders": {
    "ml": {
      "num_anomaly_jobs_in_queue": 5,
      "num_analytics_jobs_in_queue": 3,
      "down_scale_delay": "30m"
    }
  }
}
--------------------------------------------------
// TEST

The API returns the following result:

[source,console-result]
--------------------------------------------------
{
  "acknowledged": true
}
--------------------------------------------------

//////////////////////////

[source,console]
--------------------------------------------------
DELETE /_autoscaling/policy/my_autoscaling_policy
--------------------------------------------------
// TEST[continued]

//////////////////////////