feat(vertexai): Add fields to Vertex AI FeatureStore EntityType for Feature Value Monitoring

mmv1/products/vertexai/api.yaml

@@ -262,7 +262,7 @@ objects:
           - !ruby/object:Api::Type::NestedObject
             name: 'snapshotAnalysis'
             description: |
-              Configuration of how features in Featurestore are monitored.
+              The config for Snapshot Analysis Based Feature Monitoring.
             properties:
               - !ruby/object:Api::Type::Boolean
                 name: 'disabled'
@@ -277,6 +277,57 @@ objects:
                   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".
+              - !ruby/object:Api::Type::Integer
+                name: 'monitoringIntervalDays'
+                description: |
+                  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.
+                default_value: 1
+              - !ruby/object:Api::Type::Integer
+                name: 'stalenessDays'
+                description: |
+                  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.
+                default_value: 21
+          - !ruby/object:Api::Type::NestedObject
+            name: 'importFeaturesAnalysis'
+            description: |
+              The config for ImportFeatures Analysis Based Feature Monitoring.
+            properties:
+              - !ruby/object:Api::Type::String
+                name: state
+                description: |
+                  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.
+              - !ruby/object:Api::Type::String
+                name: 'anomalyDetectionBaseline'
+                description: |
+                  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.
+          - !ruby/object:Api::Type::NestedObject
+            name: 'numericalThresholdConfig'
+            description: |
+              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).
+            properties:
+              - !ruby/object:Api::Type::Double
+                name: 'value'
+                description: |
+                  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.
+                required: true
+          - !ruby/object:Api::Type::NestedObject
+            name: 'categoricalThresholdConfig'
+            description: |
+              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).
+            properties:
+              - !ruby/object:Api::Type::Double
+                name: 'value'
+                description: |
+                  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.
+                required: true
+
 
 # Vertex AI Featurestore Entity Type Feature
   - !ruby/object:Api::Resource

mmv1/products/vertexai/terraform.yaml

@@ -97,6 +97,8 @@ overrides: !ruby/object:Overrides::ResourceOverrides
         ignore_read: true
       name: !ruby/object:Overrides::Terraform::PropertyOverride
         custom_flatten: templates/terraform/custom_flatten/name_from_self_link.erb
+      monitoringConfig.snapshotAnalysis.monitoringInterval: !ruby/object:Overrides::Terraform::PropertyOverride
+        default_from_api: true
     custom_code: !ruby/object:Provider::Terraform::CustomCode
       pre_create: templates/terraform/constants/vertex_ai_featurestore_entitytype.go.erb
       pre_update: templates/terraform/constants/vertex_ai_featurestore_entitytype.go.erb

mmv1/templates/terraform/examples/vertex_ai_featurestore_entitytype.tf.erb

@@ -18,4 +18,21 @@ resource "google_vertex_ai_featurestore_entitytype" "entity" {
     foo = "bar"
   }
   featurestore = google_vertex_ai_featurestore.featurestore.id
+  monitoring_config {
+    snapshot_analysis {
+      disabled = false
+      monitoring_interval_days = 1
+      staleness_days = 21
+    }
+    numerical_threshold_config {
+      value = 0.8
+    }
+    categorical_threshold_config {
+      value = 10.0
+    }
+    import_features_analysis {
+      state = "ENABLED"
+      anomaly_detection_baseline = "PREVIOUS_IMPORT_FEATURES_STATS"
+    }
+  }
 }

mmv1/templates/terraform/examples/vertex_ai_featurestore_entitytype_feature_with_beta_fields.tf.erb

@@ -22,6 +22,14 @@ resource "google_vertex_ai_featurestore_entitytype" "entity" {
       disabled = false
       monitoring_interval = "86400s"
     }
+
+    categorical_threshold_config {
+      value = 0.3
+    }
+
+    numerical_threshold_config {
+      value = 0.3
+    }
   }
 }
 

mmv1/templates/terraform/examples/vertex_ai_featurestore_entitytype_with_beta_fields.tf.erb

@@ -25,5 +25,13 @@ resource "google_vertex_ai_featurestore_entitytype" "entity" {
       disabled = false
       monitoring_interval = "86400s"
     }
+
+    categorical_threshold_config {
+      value = 0.3
+    }
+
+    numerical_threshold_config {
+      value = 0.3
+    }
   }
 }