While this chapter was not intended to be a full demonstration of the powerful features of Watcher, it is important to see that alerts can be created with ML's detailed results—both using built-in mechanisms and via custom definitions. And, if Elastic chooses to provide a different or updated Alerting platform in lieu of Watcher in the future, the fundamentals of what ML provides are unlikely to change much over time. The ultimate key take-away is that Elastic ML provides detailed results, stored in an Elasticsearch index, that can be queried and reported upon for the purposes of Alerting.
In the next chapter, Chapter 7, Using Elastic ML Data in Kibana Dashboards, we will also learn how to leverage ML's detailed results for custom visualizations and dashboards in Kibana.
