Machine Learning Settings in Elasticsearch

You do not need to configure any settings to use machine learning. It is enabled by default.

General Machine Learning Settings

Set to true (default) to identify the node as a machine learning node.

If set to false in elasticsearch.yml, the node cannot run jobs. If set to true but is set to false, the setting is ignored and the node cannot run jobs. If you want to run jobs, there must be at least one machine learning node in your cluster.

On dedicated coordinating nodes or dedicated master nodes, disable the role.

Set to true (default) to enable machine learning on the node.

If set to false in elasticsearch.yml, the machine learning APIs are disabled on the node. Therefore the node cannot open jobs, start datafeeds, or receive transport (internal) communication requests related to machine learning APIs. It also affects all Kibana instances that connect to this Elasticsearch instance; you do not need to disable machine learning in those kibana.yml files. For more information about disabling machine learning in specific Kibana instances, see Kibana Machine Learning Settings.

If you want to use machine learning features in your cluster, you must have set to true on all master-eligible nodes. This is the default behavior.
The maximum number of jobs that can run on a node. Defaults to 10.
The maximum model_memory_limit property value that can be set for any job on this node. If you try to create a job with a model_memory_limit property value that is greater than this setting value, an error occurs. Existing jobs are not affected when you update this setting. For more information about the model_memory_limit property, see Analysis Limits.
The maximum number of jobs that can concurrently be in the opening state on each node. Typically, jobs spend a small amount of time in this state before they move to open state. Jobs that must restore large models when they are opening spend more time in the opening state. Defaults to 2.