@lbrlabs/pulumi-grafana/machineLearningOutlierDetector.d.ts

A Pulumi package for creating and managing grafana.

import * as pulumi from "@pulumi/pulumi";
import * as inputs from "./types/input";
import * as outputs from "./types/output";
/**
 * 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.
 */
export declare class MachineLearningOutlierDetector extends pulumi.CustomResource {
    /**
     * Get an existing MachineLearningOutlierDetector resource's state with the given name, ID, and optional extra
     * properties used to qualify the lookup.
     *
     * @param name The _unique_ name of the resulting resource.
     * @param id The _unique_ provider ID of the resource to lookup.
     * @param state Any extra arguments used during the lookup.
     * @param opts Optional settings to control the behavior of the CustomResource.
     */
    static get(name: string, id: pulumi.Input<pulumi.ID>, state?: MachineLearningOutlierDetectorState, opts?: pulumi.CustomResourceOptions): MachineLearningOutlierDetector;
    /**
     * Returns true if the given object is an instance of MachineLearningOutlierDetector.  This is designed to work even
     * when multiple copies of the Pulumi SDK have been loaded into the same process.
     */
    static isInstance(obj: any): obj is MachineLearningOutlierDetector;
    /**
     * The algorithm to use and its configuration. See https://grafana.com/docs/grafana-cloud/machine-learning/outlier-detection/ for details.
     */
    readonly algorithm: pulumi.Output<outputs.MachineLearningOutlierDetectorAlgorithm>;
    /**
     * The id of the datasource to query.
     */
    readonly datasourceId: pulumi.Output<number | undefined>;
    /**
     * The type of datasource being queried. Currently allowed values are prometheus, graphite, loki, postgres, and datadog.
     */
    readonly datasourceType: pulumi.Output<string>;
    /**
     * The uid of the datasource to query.
     */
    readonly datasourceUid: pulumi.Output<string | undefined>;
    /**
     * A description of the outlier detector.
     */
    readonly description: pulumi.Output<string | undefined>;
    /**
     * The data interval in seconds to monitor. Defaults to `300`.
     */
    readonly interval: pulumi.Output<number | undefined>;
    /**
     * The metric used to query the outlier detector results.
     */
    readonly metric: pulumi.Output<string>;
    /**
     * The name of the algorithm to use ('mad' or 'dbscan').
     */
    readonly name: pulumi.Output<string>;
    /**
     * An object representing the query params to query Grafana with.
     */
    readonly queryParams: pulumi.Output<{
        [key: string]: any;
    }>;
    /**
     * Create a MachineLearningOutlierDetector resource with the given unique name, arguments, and options.
     *
     * @param name The _unique_ name of the resource.
     * @param args The arguments to use to populate this resource's properties.
     * @param opts A bag of options that control this resource's behavior.
     */
    constructor(name: string, args: MachineLearningOutlierDetectorArgs, opts?: pulumi.CustomResourceOptions);
}
/**
 * Input properties used for looking up and filtering MachineLearningOutlierDetector resources.
 */
export interface MachineLearningOutlierDetectorState {
    /**
     * The algorithm to use and its configuration. See https://grafana.com/docs/grafana-cloud/machine-learning/outlier-detection/ for details.
     */
    algorithm?: pulumi.Input<inputs.MachineLearningOutlierDetectorAlgorithm>;
    /**
     * The id of the datasource to query.
     */
    datasourceId?: pulumi.Input<number>;
    /**
     * The type of datasource being queried. Currently allowed values are prometheus, graphite, loki, postgres, and datadog.
     */
    datasourceType?: pulumi.Input<string>;
    /**
     * The uid of the datasource to query.
     */
    datasourceUid?: pulumi.Input<string>;
    /**
     * A description of the outlier detector.
     */
    description?: pulumi.Input<string>;
    /**
     * The data interval in seconds to monitor. Defaults to `300`.
     */
    interval?: pulumi.Input<number>;
    /**
     * The metric used to query the outlier detector results.
     */
    metric?: pulumi.Input<string>;
    /**
     * The name of the algorithm to use ('mad' or 'dbscan').
     */
    name?: pulumi.Input<string>;
    /**
     * An object representing the query params to query Grafana with.
     */
    queryParams?: pulumi.Input<{
        [key: string]: any;
    }>;
}
/**
 * The set of arguments for constructing a MachineLearningOutlierDetector resource.
 */
export interface MachineLearningOutlierDetectorArgs {
    /**
     * The algorithm to use and its configuration. See https://grafana.com/docs/grafana-cloud/machine-learning/outlier-detection/ for details.
     */
    algorithm: pulumi.Input<inputs.MachineLearningOutlierDetectorAlgorithm>;
    /**
     * The id of the datasource to query.
     */
    datasourceId?: pulumi.Input<number>;
    /**
     * The type of datasource being queried. Currently allowed values are prometheus, graphite, loki, postgres, and datadog.
     */
    datasourceType: pulumi.Input<string>;
    /**
     * The uid of the datasource to query.
     */
    datasourceUid?: pulumi.Input<string>;
    /**
     * A description of the outlier detector.
     */
    description?: pulumi.Input<string>;
    /**
     * The data interval in seconds to monitor. Defaults to `300`.
     */
    interval?: pulumi.Input<number>;
    /**
     * The metric used to query the outlier detector results.
     */
    metric: pulumi.Input<string>;
    /**
     * The name of the algorithm to use ('mad' or 'dbscan').
     */
    name?: pulumi.Input<string>;
    /**
     * An object representing the query params to query Grafana with.
     */
    queryParams: pulumi.Input<{
        [key: string]: any;
    }>;
}