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).
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).
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 monitoringInterval.
Fields
disabled
boolean
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. feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoringInterval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoringInterval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
Configuration of the snapshot analysis based monitoring pipeline running interval. The value is rolled up to full day. If both monitoringIntervalDays and the deprecated monitoringInterval field are set when creating/updating EntityTypes/Features, monitoringIntervalDays will be used.
A duration in seconds with up to nine fractional digits, ending with 's'. Example: "3.5s".
monitoringIntervalDays
integer
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
stalenessDays
integer
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.
Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each feature imported by every ImportFeatureValues operation.
The state defines whether to enable ImportFeature analysis.
Enums
STATE_UNSPECIFIED
Should not be used.
DEFAULT
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.
ENABLED
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.
DISABLED
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.
Baseline
Defines the baseline to do anomaly detection for feature values imported by each ImportFeatureValues operation.
Enums
BASELINE_UNSPECIFIED
Should not be used.
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.
ThresholdConfig
The config for Featurestore Monitoring threshold.
Fields
threshold
Union type
threshold can be only one of the following:
value
number
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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-06-27 UTC."],[],[],null,["# FeaturestoreMonitoringConfig\n\nConfiguration of how features in Featurestore are monitored.\nFields `snapshotAnalysis` `object (`[SnapshotAnalysis](/vertex-ai/docs/reference/rest/v1beta1/FeaturestoreMonitoringConfig#SnapshotAnalysis)`)` \nThe config for Snapshot Analysis Based feature Monitoring.\n`importFeaturesAnalysis` `object (`[ImportFeaturesAnalysis](/vertex-ai/docs/reference/rest/v1beta1/FeaturestoreMonitoringConfig#ImportFeaturesAnalysis)`)` \nThe config for ImportFeatures Analysis Based feature Monitoring.\n`numericalThresholdConfig` `object (`[ThresholdConfig](/vertex-ai/docs/reference/rest/v1beta1/FeaturestoreMonitoringConfig#ThresholdConfig)`)` \nThreshold 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](/vertex-ai/docs/reference/rest/v1beta1/projects.locations.featureGroups.features#Feature.ValueType)) DOUBLE or INT64).\n`categoricalThresholdConfig` `object (`[ThresholdConfig](/vertex-ai/docs/reference/rest/v1beta1/FeaturestoreMonitoringConfig#ThresholdConfig)`)` \nThreshold 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](/vertex-ai/docs/reference/rest/v1beta1/projects.locations.featureGroups.features#Feature.ValueType)) BOOL or STRING). \n\nSnapshotAnalysis\n----------------\n\nConfiguration 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 monitoringInterval.\nFields `disabled` `boolean` \nThe 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. feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoringInterval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoringInterval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.\n`monitoringInterval` \n**(deprecated)** `string (`[Duration](https://protobuf.dev/reference/protobuf/google.protobuf/#duration)` format)` \n| This item is deprecated!\n\nConfiguration of the snapshot analysis based monitoring pipeline running interval. The value is rolled up to full day. If both [monitoringIntervalDays](/vertex-ai/docs/reference/rest/v1beta1/FeaturestoreMonitoringConfig#SnapshotAnalysis.FIELDS.monitoring_interval_days) and the deprecated `monitoringInterval` field are set when creating/updating EntityTypes/Features, [monitoringIntervalDays](/vertex-ai/docs/reference/rest/v1beta1/FeaturestoreMonitoringConfig#SnapshotAnalysis.FIELDS.monitoring_interval_days) will be used.\n\nA duration in seconds with up to nine fractional digits, ending with '`s`'. Example: `\"3.5s\"`.\n`monitoringIntervalDays` `integer` \nConfiguration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.\n`stalenessDays` `integer` \nCustomized 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. \n\nImportFeaturesAnalysis\n----------------------\n\nConfiguration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each feature imported by every [ImportFeatureValues](/vertex-ai/docs/reference/rest/v1beta1/projects.locations.featurestores.entityTypes/importFeatureValues#google.cloud.aiplatform.v1beta1.FeaturestoreService.ImportFeatureValues) operation.\nFields `state` `enum (`[State](/vertex-ai/docs/reference/rest/v1beta1/FeaturestoreMonitoringConfig#State)`)` \nWhether to enable / disable / inherite default hebavior for import features analysis.\n`anomalyDetectionBaseline` `enum (`[Baseline](/vertex-ai/docs/reference/rest/v1beta1/FeaturestoreMonitoringConfig#Baseline)`)` \nThe baseline used to do anomaly detection for the statistics generated by import features analysis. \n\nState\n-----\n\nThe state defines whether to enable ImportFeature analysis.\n\nBaseline\n--------\n\nDefines the baseline to do anomaly detection for feature values imported by each [ImportFeatureValues](/vertex-ai/docs/reference/rest/v1beta1/projects.locations.featurestores.entityTypes/importFeatureValues#google.cloud.aiplatform.v1beta1.FeaturestoreService.ImportFeatureValues) operation.\n\nThresholdConfig\n---------------\n\nThe config for Featurestore Monitoring threshold.\nFields \n`threshold` `Union type` \n`threshold` can be only one of the following:\n`value` `number` \nSpecify 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."]]