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[8.6] [DOCS] Updates ML decider docs by mentioning CPU as scaling criterion (#92018) #92020

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Nov 30, 2022
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[8.6] [DOCS] Updates ML decider docs by mentioning CPU as scaling criterion (#92018) #92020

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21 changes: 11 additions & 10 deletions docs/reference/autoscaling/deciders/machine-learning-decider.asciidoc
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[[autoscaling-machine-learning-decider]]
=== Machine learning decider

The {ml} decider (`ml`) calculates the memory required to run {ml} jobs.
The {ml} decider (`ml`) calculates the memory and CPU requirements to run {ml}
jobs and trained models.

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

NOTE: For {ml} jobs to open when the cluster is not appropriately
scaled, set `xpack.ml.max_lazy_ml_nodes` to the largest number of possible {ml}
jobs (refer to <<advanced-ml-settings>> for more information). In {ess}, this is
NOTE: For {ml} jobs to open when the cluster is not appropriately scaled, set
`xpack.ml.max_lazy_ml_nodes` to the largest number of possible {ml} nodes (refer
to <<advanced-ml-settings>> for more information). In {ess}, this is
automatically set.

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

Both `num_anomaly_jobs_in_queue` and `num_analytics_jobs_in_queue` are designed
to delay a scale-up event. If the cluster is too small, these settings indicate how many jobs of each type can be
unassigned from a node. Both settings are
only considered for jobs that can be opened given the current scale. If a job is
too large for any node size or if a job can't be assigned without user
intervention (for example, a user calling `_stop` against a real-time
{anomaly-job}), the numbers are ignored for that particular job.
to delay a scale-up event. If the cluster is too small, these settings indicate
how many jobs of each type can be unassigned from a node. Both settings are only
considered for jobs that can be opened given the current scale. If a job is too
large for any node size or if a job can't be assigned without user intervention
(for example, a user calling `_stop` against a real-time {anomaly-job}), the
numbers are ignored for that particular job.

`num_anomaly_jobs_in_queue`::
(Optional, integer)
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