// Copyright 2023 Google LLC // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. syntax = "proto3"; package google.cloud.aiplatform.v1beta1; import "google/protobuf/duration.proto"; option csharp_namespace = "Google.Cloud.AIPlatform.V1Beta1"; option go_package = "cloud.google.com/go/aiplatform/apiv1beta1/aiplatformpb;aiplatformpb"; option java_multiple_files = true; option java_outer_classname = "FeaturestoreMonitoringProto"; option java_package = "com.google.cloud.aiplatform.v1beta1"; option php_namespace = "Google\\Cloud\\AIPlatform\\V1beta1"; option ruby_package = "Google::Cloud::AIPlatform::V1beta1"; // Configuration of how features in Featurestore are monitored. message FeaturestoreMonitoringConfig { // Configuration of the Featurestore's Snapshot Analysis Based Monitoring. // This type of analysis generates statistics for each Feature based on a // snapshot of the latest feature value of each entities every // monitoring_interval. message 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 monitoring_interval for Features under it. // Feature-level config: // disabled = true indicates disabled regardless of the EntityType-level // config; unset monitoring_interval indicates going with EntityType-level // config; otherwise run snapshot analysis monitoring with // monitoring_interval regardless of the EntityType-level config. // Explicitly Disable the snapshot analysis based monitoring. bool disabled = 1; // Configuration of the snapshot analysis based monitoring pipeline running // interval. The value is rolled up to full day. // If both // [monitoring_interval_days][google.cloud.aiplatform.v1beta1.FeaturestoreMonitoringConfig.SnapshotAnalysis.monitoring_interval_days] // and the deprecated `monitoring_interval` field // are set when creating/updating EntityTypes/Features, // [monitoring_interval_days][google.cloud.aiplatform.v1beta1.FeaturestoreMonitoringConfig.SnapshotAnalysis.monitoring_interval_days] // will be used. google.protobuf.Duration monitoring_interval = 2 [deprecated = true]; // Configuration of the snapshot analysis based monitoring pipeline // running interval. The value indicates number of days. int32 monitoring_interval_days = 3; // Customized export features time window for snapshot analysis. Unit is one // day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is // 4000 days. int32 staleness_days = 4; } // Configuration of the Featurestore's ImportFeature Analysis Based // Monitoring. This type of analysis generates statistics for values of each // Feature imported by every // [ImportFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.ImportFeatureValues] // operation. message ImportFeaturesAnalysis { // The state defines whether to enable ImportFeature analysis. enum State { // Should not be used. STATE_UNSPECIFIED = 0; // The default behavior of whether to enable the monitoring. // EntityType-level config: disabled. // Feature-level config: inherited from the configuration of EntityType // this Feature belongs to. DEFAULT = 1; // Explicitly enables import features analysis. // EntityType-level config: by default enables import features analysis // for all Features under it. Feature-level config: enables import // features analysis regardless of the EntityType-level config. ENABLED = 2; // Explicitly disables import features analysis. // EntityType-level config: by default disables import features analysis // for all Features under it. Feature-level config: disables import // features analysis regardless of the EntityType-level config. DISABLED = 3; } // Defines the baseline to do anomaly detection for feature values imported // by each // [ImportFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.ImportFeatureValues] // operation. enum Baseline { // Should not be used. BASELINE_UNSPECIFIED = 0; // 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. LATEST_STATS = 1; // Use the statistics generated by the most recent snapshot analysis if // exists. MOST_RECENT_SNAPSHOT_STATS = 2; // Use the statistics generated by the previous import features analysis // if exists. PREVIOUS_IMPORT_FEATURES_STATS = 3; } // Whether to enable / disable / inherite default hebavior for import // features analysis. State state = 1; // The baseline used to do anomaly detection for the statistics generated by // import features analysis. Baseline anomaly_detection_baseline = 2; } // The config for Featurestore Monitoring threshold. message ThresholdConfig { oneof threshold { // Specify a threshold value that can trigger the alert. // 1. For categorical feature, the distribution distance is calculated by // L-inifinity norm. // 2. 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. double value = 1; } } // The config for Snapshot Analysis Based Feature Monitoring. SnapshotAnalysis snapshot_analysis = 1; // The config for ImportFeatures Analysis Based Feature Monitoring. ImportFeaturesAnalysis import_features_analysis = 2; // 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][google.cloud.aiplatform.v1beta1.Feature.ValueType]) // DOUBLE or INT64). ThresholdConfig numerical_threshold_config = 3; // 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][google.cloud.aiplatform.v1beta1.Feature.ValueType]) // BOOL or STRING). ThresholdConfig categorical_threshold_config = 4; }