Understanding operationalization

At some point on your journey with using Elastic ML, it will be helpful to understand a number of key concepts regarding how Elastic ML is operationalized within the Elastic Stack. This includes information about how the analytics run on the cluster nodes and how data that is to be analyzed by ML is retrieved and processed.

Note

Some concepts in this section may not be intuitive until you actually start using Elastic ML on some real examples. Don't worry if you feel like you prefer to skim (or even skip) this section now and return to it later following some genuine experience of using Elastic ML.

ML nodes

First and foremost, since Elasticsearch is, by nature, a distributed multi-node solution, it is only natural that the ML feature of the Elastic Stack works as a native plugin that obeys many of the same operational concepts. As described in the documentation (elastic.co/guide/en/elasticsearch/reference/current/ml-settings.html),...