Elastic, the commercial company supporting the Elasticsearch stack for searches of real-time data, has added machine learning functionality to all the pieces of the Elastic stack.
Unlike some other companies, Elastic isn’t claiming this addition is cure-all magic dust. Rather, it’s for performing specific analysis for explicitly defined use cases.
In a blog post that went live yesterday, Elastic outlined examples of Elasticsearch’s anomaly detection in action, such as detecting changes to a performance metric or analyzing many metrics together to determine when one is out of gamut.
This addition is still considered a beta, and the machine learning features are not open source like the other elements in the Elastic stack—they’re only available through the X-Pack commercial add-on. The features were themselves added when Elastic picked up a company called Prelert late last year.
