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[DOCS] Updates ML decider docs by mentioning CPU as scaling criterion (#92018) (#92020)
Co-authored-by: Abdon Pijpelink <[email protected]> (cherry picked from commit 26bc894)
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docs/reference/autoscaling/deciders/machine-learning-decider.asciidoc

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[[autoscaling-machine-learning-decider]]
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=== Machine learning decider
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The {ml} decider (`ml`) calculates the memory required to run {ml} jobs.
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The {ml} decider (`ml`) calculates the memory and CPU requirements to run {ml}
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jobs and trained models.
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The {ml} decider is enabled for policies governing `ml` nodes.
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NOTE: For {ml} jobs to open when the cluster is not appropriately
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scaled, set `xpack.ml.max_lazy_ml_nodes` to the largest number of possible {ml}
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jobs (refer to <<advanced-ml-settings>> for more information). In {ess}, this is
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NOTE: For {ml} jobs to open when the cluster is not appropriately scaled, set
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`xpack.ml.max_lazy_ml_nodes` to the largest number of possible {ml} nodes (refer
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to <<advanced-ml-settings>> for more information). In {ess}, this is
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automatically set.
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[[autoscaling-machine-learning-decider-settings]]
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==== Configuration settings
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Both `num_anomaly_jobs_in_queue` and `num_analytics_jobs_in_queue` are designed
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to delay a scale-up event. If the cluster is too small, these settings indicate how many jobs of each type can be
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unassigned from a node. Both settings are
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only considered for jobs that can be opened given the current scale. If a job is
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too large for any node size or if a job can't be assigned without user
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intervention (for example, a user calling `_stop` against a real-time
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{anomaly-job}), the numbers are ignored for that particular job.
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to delay a scale-up event. If the cluster is too small, these settings indicate
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how many jobs of each type can be unassigned from a node. Both settings are only
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considered for jobs that can be opened given the current scale. If a job is too
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large for any node size or if a job can't be assigned without user intervention
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(for example, a user calling `_stop` against a real-time {anomaly-job}), the
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numbers are ignored for that particular job.
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`num_anomaly_jobs_in_queue`::
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(Optional, integer)

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