zz_featurestoreentitytype_types.go

/*
Copyright 2021 The Crossplane Authors.

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.
*/

// Code generated by upjet. DO NOT EDIT.

package v1beta1

import (
	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
	"k8s.io/apimachinery/pkg/runtime/schema"

	v1 "github.com/crossplane/crossplane-runtime/apis/common/v1"
)

type CategoricalThresholdConfigObservation struct {

	// 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 *float64 `json:"value,omitempty" tf:"value,omitempty"`
}

type CategoricalThresholdConfigParameters struct {

	// 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.
	// +kubebuilder:validation:Required
	Value *float64 `json:"value" tf:"value,omitempty"`
}

type FeaturestoreEntitytypeObservation struct {

	// The timestamp of when the featurestore was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
	CreateTime *string `json:"createTime,omitempty" tf:"create_time,omitempty"`

	// Optional. Description of the EntityType.
	Description *string `json:"description,omitempty" tf:"description,omitempty"`

	// Used to perform consistent read-modify-write updates.
	Etag *string `json:"etag,omitempty" tf:"etag,omitempty"`

	// The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}.
	Featurestore *string `json:"featurestore,omitempty" tf:"featurestore,omitempty"`

	// an identifier for the resource with format {{featurestore}}/entityTypes/{{name}}
	ID *string `json:"id,omitempty" tf:"id,omitempty"`

	// A set of key/value label pairs to assign to this EntityType.
	Labels map[string]*string `json:"labels,omitempty" tf:"labels,omitempty"`

	// 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.
	// Structure is documented below.
	MonitoringConfig []MonitoringConfigObservation `json:"monitoringConfig,omitempty" tf:"monitoring_config,omitempty"`

	// The name of the EntityType. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
	Name *string `json:"name,omitempty" tf:"name,omitempty"`

	Region *string `json:"region,omitempty" tf:"region,omitempty"`

	// 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 `json:"updateTime,omitempty" tf:"update_time,omitempty"`
}

type FeaturestoreEntitytypeParameters struct {

	// Optional. Description of the EntityType.
	// +kubebuilder:validation:Optional
	Description *string `json:"description,omitempty" tf:"description,omitempty"`

	// The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}.
	// +crossplane:generate:reference:type=github.com/upbound/provider-gcp/apis/vertexai/v1beta1.Featurestore
	// +crossplane:generate:reference:extractor=github.com/upbound/upjet/pkg/resource.ExtractResourceID()
	// +kubebuilder:validation:Optional
	Featurestore *string `json:"featurestore,omitempty" tf:"featurestore,omitempty"`

	// Reference to a Featurestore in vertexai to populate featurestore.
	// +kubebuilder:validation:Optional
	FeaturestoreRef *v1.Reference `json:"featurestoreRef,omitempty" tf:"-"`

	// Selector for a Featurestore in vertexai to populate featurestore.
	// +kubebuilder:validation:Optional
	FeaturestoreSelector *v1.Selector `json:"featurestoreSelector,omitempty" tf:"-"`

	// A set of key/value label pairs to assign to this EntityType.
	// +kubebuilder:validation:Optional
	Labels map[string]*string `json:"labels,omitempty" tf:"labels,omitempty"`

	// 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.
	// Structure is documented below.
	// +kubebuilder:validation:Optional
	MonitoringConfig []MonitoringConfigParameters `json:"monitoringConfig,omitempty" tf:"monitoring_config,omitempty"`

	// The name of the EntityType. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
	// +kubebuilder:validation:Optional
	Name *string `json:"name,omitempty" tf:"name,omitempty"`
}

type ImportFeaturesAnalysisObservation struct {

	// 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:
	AnomalyDetectionBaseline *string `json:"anomalyDetectionBaseline,omitempty" tf:"anomaly_detection_baseline,omitempty"`

	// Whether to enable / disable / inherite default hebavior for import features analysis. The value must be one of the values below:
	State *string `json:"state,omitempty" tf:"state,omitempty"`
}

type ImportFeaturesAnalysisParameters struct {

	// 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:
	// +kubebuilder:validation:Optional
	AnomalyDetectionBaseline *string `json:"anomalyDetectionBaseline,omitempty" tf:"anomaly_detection_baseline,omitempty"`

	// Whether to enable / disable / inherite default hebavior for import features analysis. The value must be one of the values below:
	// +kubebuilder:validation:Optional
	State *string `json:"state,omitempty" tf:"state,omitempty"`
}

type MonitoringConfigObservation struct {

	// 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).
	// Structure is documented below.
	CategoricalThresholdConfig []CategoricalThresholdConfigObservation `json:"categoricalThresholdConfig,omitempty" tf:"categorical_threshold_config,omitempty"`

	// The config for ImportFeatures Analysis Based Feature Monitoring.
	// Structure is documented below.
	ImportFeaturesAnalysis []ImportFeaturesAnalysisObservation `json:"importFeaturesAnalysis,omitempty" tf:"import_features_analysis,omitempty"`

	// 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).
	// Structure is documented below.
	NumericalThresholdConfig []NumericalThresholdConfigObservation `json:"numericalThresholdConfig,omitempty" tf:"numerical_threshold_config,omitempty"`

	// The config for Snapshot Analysis Based Feature Monitoring.
	// Structure is documented below.
	SnapshotAnalysis []SnapshotAnalysisObservation `json:"snapshotAnalysis,omitempty" tf:"snapshot_analysis,omitempty"`
}

type MonitoringConfigParameters struct {

	// 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).
	// Structure is documented below.
	// +kubebuilder:validation:Optional
	CategoricalThresholdConfig []CategoricalThresholdConfigParameters `json:"categoricalThresholdConfig,omitempty" tf:"categorical_threshold_config,omitempty"`

	// The config for ImportFeatures Analysis Based Feature Monitoring.
	// Structure is documented below.
	// +kubebuilder:validation:Optional
	ImportFeaturesAnalysis []ImportFeaturesAnalysisParameters `json:"importFeaturesAnalysis,omitempty" tf:"import_features_analysis,omitempty"`

	// 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).
	// Structure is documented below.
	// +kubebuilder:validation:Optional
	NumericalThresholdConfig []NumericalThresholdConfigParameters `json:"numericalThresholdConfig,omitempty" tf:"numerical_threshold_config,omitempty"`

	// The config for Snapshot Analysis Based Feature Monitoring.
	// Structure is documented below.
	// +kubebuilder:validation:Optional
	SnapshotAnalysis []SnapshotAnalysisParameters `json:"snapshotAnalysis,omitempty" tf:"snapshot_analysis,omitempty"`
}

type NumericalThresholdConfigObservation struct {

	// 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 *float64 `json:"value,omitempty" tf:"value,omitempty"`
}

type NumericalThresholdConfigParameters struct {

	// 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.
	// +kubebuilder:validation:Required
	Value *float64 `json:"value" tf:"value,omitempty"`
}

type SnapshotAnalysisObservation struct {

	// 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 *bool `json:"disabled,omitempty" tf:"disabled,omitempty"`

	// 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 *float64 `json:"monitoringIntervalDays,omitempty" tf:"monitoring_interval_days,omitempty"`

	// 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 *float64 `json:"stalenessDays,omitempty" tf:"staleness_days,omitempty"`
}

type SnapshotAnalysisParameters struct {

	// 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.
	// +kubebuilder:validation:Optional
	Disabled *bool `json:"disabled,omitempty" tf:"disabled,omitempty"`

	// 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.
	// +kubebuilder:validation:Optional
	MonitoringIntervalDays *float64 `json:"monitoringIntervalDays,omitempty" tf:"monitoring_interval_days,omitempty"`

	// 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.
	// +kubebuilder:validation:Optional
	StalenessDays *float64 `json:"stalenessDays,omitempty" tf:"staleness_days,omitempty"`
}

// FeaturestoreEntitytypeSpec defines the desired state of FeaturestoreEntitytype
type FeaturestoreEntitytypeSpec struct {
	v1.ResourceSpec `json:",inline"`
	ForProvider     FeaturestoreEntitytypeParameters `json:"forProvider"`
}

// FeaturestoreEntitytypeStatus defines the observed state of FeaturestoreEntitytype.
type FeaturestoreEntitytypeStatus struct {
	v1.ResourceStatus `json:",inline"`
	AtProvider        FeaturestoreEntitytypeObservation `json:"atProvider,omitempty"`
}

// +kubebuilder:object:root=true

// FeaturestoreEntitytype is the Schema for the FeaturestoreEntitytypes API. An entity type is a type of object in a system that needs to be modeled and have stored information about.
// +kubebuilder:printcolumn:name="READY",type="string",JSONPath=".status.conditions[?(@.type=='Ready')].status"
// +kubebuilder:printcolumn:name="SYNCED",type="string",JSONPath=".status.conditions[?(@.type=='Synced')].status"
// +kubebuilder:printcolumn:name="EXTERNAL-NAME",type="string",JSONPath=".metadata.annotations.crossplane\\.io/external-name"
// +kubebuilder:printcolumn:name="AGE",type="date",JSONPath=".metadata.creationTimestamp"
// +kubebuilder:subresource:status
// +kubebuilder:resource:scope=Cluster,categories={crossplane,managed,gcp}
type FeaturestoreEntitytype struct {
	metav1.TypeMeta   `json:",inline"`
	metav1.ObjectMeta `json:"metadata,omitempty"`
	Spec              FeaturestoreEntitytypeSpec   `json:"spec"`
	Status            FeaturestoreEntitytypeStatus `json:"status,omitempty"`
}

// +kubebuilder:object:root=true

// FeaturestoreEntitytypeList contains a list of FeaturestoreEntitytypes
type FeaturestoreEntitytypeList struct {
	metav1.TypeMeta `json:",inline"`
	metav1.ListMeta `json:"metadata,omitempty"`
	Items           []FeaturestoreEntitytype `json:"items"`
}

// Repository type metadata.
var (
	FeaturestoreEntitytype_Kind             = "FeaturestoreEntitytype"
	FeaturestoreEntitytype_GroupKind        = schema.GroupKind{Group: CRDGroup, Kind: FeaturestoreEntitytype_Kind}.String()
	FeaturestoreEntitytype_KindAPIVersion   = FeaturestoreEntitytype_Kind + "." + CRDGroupVersion.String()
	FeaturestoreEntitytype_GroupVersionKind = CRDGroupVersion.WithKind(FeaturestoreEntitytype_Kind)
)

func init() {
	SchemeBuilder.Register(&FeaturestoreEntitytype{}, &FeaturestoreEntitytypeList{})
}