From 88bc27592d2800d27fa3f14c2a9e98edadb3b1a7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Istv=C3=A1n=20Zolt=C3=A1n=20Szab=C3=B3?= Date: Mon, 1 Mar 2021 09:56:39 +0100 Subject: [PATCH] [DOCS] Reviews ML decider conceptual docs (#69524) Co-authored-by: Lisa Cawley --- .../machine-learning-decider.asciidoc | 39 ++++++++++--------- 1 file changed, 20 insertions(+), 19 deletions(-) diff --git a/docs/reference/autoscaling/deciders/machine-learning-decider.asciidoc b/docs/reference/autoscaling/deciders/machine-learning-decider.asciidoc index 1b696f6a2cee7..c7236f40c4cea 100644 --- a/docs/reference/autoscaling/deciders/machine-learning-decider.asciidoc +++ b/docs/reference/autoscaling/deciders/machine-learning-decider.asciidoc @@ -3,47 +3,46 @@ [[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 (`ml`) calculates the memory required to run {ml} jobs. The {ml} decider is enabled for policies governing `ml` nodes. NOTE: For {ml} jobs to open when the cluster is not appropriately -scaled, `xpack.ml.max_lazy_ml_nodes` should be set to the largest -number of possible {ml} jobs (see <>). In -{ess} this is already handled. +scaled, set `xpack.ml.max_lazy_ml_nodes` to the largest number of possible {ml} +jobs (refer to <> 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 be used to delay a scale-up event. They indicate how many jobs -of that type can be unassigned from a node due to the cluster being -too small. Both settings are only considered for jobs that could -eventually be fully opened given the current scale. If a job is too -large for any node size or if a job couldn't ever be assigned without -user intervention (for example, a user calling `_stop` against a real-time +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. `num_anomaly_jobs_in_queue`:: (Optional, integer) -Number of queued anomaly jobs to allow. Defaults to `0`. +Specifies the 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`. +Specifies the number of queued {dfanalytics-jobs} to allow. Defaults to `0`. `down_scale_delay`:: (Optional, <>) -Delay before scaling down. Defaults to 1 hour. If a scale down is possible -for the entire time window, then a scale down is requested. If the cluster -requires a scale up during the window, the window is reset. +Specifies the time to delay before scaling down. Defaults to 1 hour. If a scale +down is possible for the entire time window, then a scale down is requested. If +the cluster requires a scale up during the window, the window is reset. + [[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. +This example creates an autoscaling policy named `my_autoscaling_policy` that +overrides the default configuration of the {ml} decider. [source,console] -------------------------------------------------- @@ -61,6 +60,7 @@ PUT /_autoscaling/policy/my_autoscaling_policy -------------------------------------------------- // TEST + The API returns the following result: [source,console-result] @@ -70,6 +70,7 @@ The API returns the following result: } -------------------------------------------------- + ////////////////////////// [source,console]