An outlier detector monitors the results of a query and reports when its values are outside normal bands.
The normal band is configured by choice of algorithm, its sensitivity and other configuration.
Visit https://grafana.com/docs/grafana-cloud/machine-learning/outlier-detection/ for more details.
algorithm
(Block Set, Min: 1, Max: 1) The algorithm to use and its configuration. See https://grafana.com/docs/grafana-cloud/machine-learning/outlier-detection/ for details. (see below for nested schema)datasource_type
(String) The type of datasource being queried. Currently allowed values are prometheus, graphite, loki, postgres, and datadog.metric
(String) The metric used to query the outlier detector results.name
(String) The name of the outlier detector.query_params
(Map of String) An object representing the query params to query Grafana with.datasource_id
(Number, Deprecated) The id of the datasource to query.datasource_uid
(String) The uid of the datasource to query.description
(String) A description of the outlier detector.interval
(Number) The data interval in seconds to monitor. Defaults to 300
.id
(String) The ID of the outlier detector.algorithm
Required:
name
(String) The name of the algorithm to use ('mad' or 'dbscan').sensitivity
(Number) Specify the sensitivity of the detector (in range [0,1]).Optional:
config
(Block Set, Max: 1) For DBSCAN only, specify the configuration map (see below for nested schema)algorithm.config
Required:
epsilon
(Number) Specify the epsilon parameter (positive float)Import is supported using the following syntax:
terraform import grafana_machine_learning_outlier_detector.name "{{ id }}"