Chapter 6: Alerting on ML Analysis
The previous chapter (Chapter 5, Interpreting Results) explained in depth how anomaly detection and forecasting results are stored in Elasticsearch indices. This gives us the proper background to now create proactive, actionable, and informative alerts on those results.
At the time of writing this book, we find ourselves at an inflection point. For several years, Elastic ML has relied on the alerting capabilities of Watcher (a component of Elasticsearch) as this was the exclusive mechanism to alert on data. However, a new platform of alerting has been designed as part of Kibana (and was deemed GA in v7.11) and this new approach will be the primary mechanism of alerting moving forward.
There are still some ...
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