Supplied anomaly detection configurations

Anomaly detection jobs contain the configuration information and metadata necessary to perform an analytics task. Kibana can recognize certain types of data and provide specialized wizards for that context. This page lists the categories of the anomaly detection jobs that are ready to use via Kibana in Machine learning. Refer to Create anomaly detection jobs to learn more about creating a job by using supplied configurations. Logs and Metrics supplied configurations are available and can be created via the related solution UI in Kibana.

By default, these jobs have model_memory_limit values that are deemed appropriate for typical user environments and data characteristics. If your environment or your data is atypical and your jobs reach a memory status value of soft_limit or hard_limit, you might need to update the model memory limits. For more information, see Working with anomaly detection at scale.