Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[DOCS] Updates ML decider docs by mentioning CPU as scaling criterion #92018

Merged
merged 2 commits into from
Nov 30, 2022
Merged

[DOCS] Updates ML decider docs by mentioning CPU as scaling criterion #92018

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
453e5ec
[DOCS] Updates ML decider docs by mentioning CPU as scaling criterion.
szabosteve Nov 30, 2022
e3fcf41
Update docs/reference/autoscaling/deciders/machine-learning-decider.a…
szabosteve Nov 30, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
21 changes: 11 additions & 10 deletions docs/reference/autoscaling/deciders/machine-learning-decider.asciidoc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,25 +2,26 @@
[[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)
Expand Down