import { IObjectMeta } from "@kubernetes-models/apimachinery/apis/meta/v1/ObjectMeta";
import { Model, ModelData } from "@kubernetes-models/base";
export interface IVertexAIFeaturestoreEntityType {
    /**
     * apiVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#resources
     */
    "apiVersion": "vertexai.cnrm.cloud.google.com/v1alpha1";
    /**
     * kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#types-kinds
     */
    "kind": "VertexAIFeaturestoreEntityType";
    "metadata"?: IObjectMeta;
    "spec": {
        /**
         * Optional. Description of the EntityType.
         */
        "description"?: string;
        /**
         * Immutable. The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}.
         */
        "featurestore": string;
        /**
         * The default monitoring configuration for all Features under this EntityType.
         *
         * If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
         */
        "monitoringConfig"?: {
            /**
             * Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
             */
            "categoricalThresholdConfig"?: {
                /**
                 * Specify a threshold value that can trigger the alert. For categorical feature, the distribution distance is calculated by L-inifinity norm. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature. The default value is 0.3.
                 */
                "value": number;
            };
            /**
             * The config for ImportFeatures Analysis Based Feature Monitoring.
             */
            "importFeaturesAnalysis"?: {
                /**
                 * Defines the baseline to do anomaly detection for feature values imported by each [entityTypes.importFeatureValues][] operation. The value must be one of the values below:
                 * \* LATEST_STATS: Choose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
                 * \* MOST_RECENT_SNAPSHOT_STATS: Use the statistics generated by the most recent snapshot analysis if exists.
                 * \* PREVIOUS_IMPORT_FEATURES_STATS: Use the statistics generated by the previous import features analysis if exists.
                 */
                "anomalyDetectionBaseline"?: string;
                /**
                 * Whether to enable / disable / inherite default hebavior for import features analysis. The value must be one of the values below:
                 * \* DEFAULT: The default behavior of whether to enable the monitoring. EntityType-level config: disabled.
                 * \* ENABLED: Explicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it.
                 * \* DISABLED: Explicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it.
                 */
                "state"?: string;
            };
            /**
             * Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
             */
            "numericalThresholdConfig"?: {
                /**
                 * Specify a threshold value that can trigger the alert. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature. The default value is 0.3.
                 */
                "value": number;
            };
            /**
             * The config for Snapshot Analysis Based Feature Monitoring.
             */
            "snapshotAnalysis"?: {
                /**
                 * The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoringInterval for Features under it.
                 */
                "disabled"?: boolean;
                /**
                 * DEPRECATED. `monitoring_interval` is deprecated and will be removed in a future release. Configuration of the snapshot analysis based monitoring pipeline running interval. The value is rolled up to full day.
                 *
                 * A duration in seconds with up to nine fractional digits, terminated by 's'. Example: "3.5s".
                 */
                "monitoringInterval"?: string;
                /**
                 * Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days. The default value is 1.
                 * If both FeaturestoreMonitoringConfig.SnapshotAnalysis.monitoring_interval_days and [FeaturestoreMonitoringConfig.SnapshotAnalysis.monitoring_interval][] are set when creating/updating EntityTypes/Features, FeaturestoreMonitoringConfig.SnapshotAnalysis.monitoring_interval_days will be used.
                 */
                "monitoringIntervalDays"?: number;
                /**
                 * Customized export features time window for snapshot analysis. Unit is one day. The default value is 21 days. Minimum value is 1 day. Maximum value is 4000 days.
                 */
                "stalenessDays"?: number;
            };
        };
        /**
         * Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offlineStorageTtlDays since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
         */
        "offlineStorageTtlDays"?: number;
        /**
         * Immutable. Optional. The name of the resource. Used for creation and acquisition. When unset, the value of `metadata.name` is used as the default.
         */
        "resourceID"?: string;
    };
    "status"?: {
        /**
         * Conditions represent the latest available observation of the resource's current state.
         */
        "conditions"?: Array<{
            /**
             * Last time the condition transitioned from one status to another.
             */
            "lastTransitionTime"?: string;
            /**
             * Human-readable message indicating details about last transition.
             */
            "message"?: string;
            /**
             * Unique, one-word, CamelCase reason for the condition's last transition.
             */
            "reason"?: string;
            /**
             * Status is the status of the condition. Can be True, False, Unknown.
             */
            "status"?: string;
            /**
             * Type is the type of the condition.
             */
            "type"?: string;
        }>;
        /**
         * The timestamp of when the featurestore was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
         */
        "createTime"?: string;
        /**
         * Used to perform consistent read-modify-write updates.
         */
        "etag"?: string;
        /**
         * ObservedGeneration is the generation of the resource that was most recently observed by the Config Connector controller. If this is equal to metadata.generation, then that means that the current reported status reflects the most recent desired state of the resource.
         */
        "observedGeneration"?: number;
        /**
         * The region of the EntityType.
         */
        "region"?: string;
        /**
         * The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
         */
        "updateTime"?: string;
    };
}
export declare class VertexAIFeaturestoreEntityType extends Model<IVertexAIFeaturestoreEntityType> implements IVertexAIFeaturestoreEntityType {
    "apiVersion": IVertexAIFeaturestoreEntityType["apiVersion"];
    "kind": IVertexAIFeaturestoreEntityType["kind"];
    "metadata"?: IVertexAIFeaturestoreEntityType["metadata"];
    "spec": IVertexAIFeaturestoreEntityType["spec"];
    "status"?: IVertexAIFeaturestoreEntityType["status"];
    static apiVersion: IVertexAIFeaturestoreEntityType["apiVersion"];
    static kind: IVertexAIFeaturestoreEntityType["kind"];
    static is: import("@kubernetes-models/base").TypeMetaGuard<IVertexAIFeaturestoreEntityType>;
    constructor(data?: ModelData<IVertexAIFeaturestoreEntityType>);
}