Finding anomalies
Elastic Cloud Serverless projects are autoscaled environments, fully managed by Elastic and available on Elastic Cloud. Availability This functionality is generally available and ready for production usage. Serverless interfaces and procedures might differ from classic Elastic Stack deployments. The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats. Availability This functionality is generally available and ready for production usage. Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments. This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes.
Serverless
Generally available
Stack
Generally available
The machine learning anomaly detection features automate the analysis of time series data by creating accurate baselines of normal behavior in your data. These baselines then enable you to identify anomalous events or patterns. Data is pulled from Elasticsearch for analysis and anomaly results are displayed in Kibana dashboards. For example, the Machine Learning app provides charts that illustrate the actual data values, the bounds for the expected values, and the anomalies that occur outside these bounds.
The typical workflow for performing anomaly detection is as follows: