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zz_autoscalingpolicy_types.go
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zz_autoscalingpolicy_types.go
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// SPDX-FileCopyrightText: 2024 The Crossplane Authors <https://crossplane.io>
//
// SPDX-License-Identifier: Apache-2.0
// Code generated by upjet. DO NOT EDIT.
package v1beta2
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 AutoscalingPolicyInitParameters struct {
// Basic algorithm for autoscaling.
// Structure is documented below.
BasicAlgorithm *BasicAlgorithmInitParameters `json:"basicAlgorithm,omitempty" tf:"basic_algorithm,omitempty"`
// The ID of the project in which the resource belongs.
// If it is not provided, the provider project is used.
Project *string `json:"project,omitempty" tf:"project,omitempty"`
// Describes how the autoscaler will operate for secondary workers.
// Structure is documented below.
SecondaryWorkerConfig *SecondaryWorkerConfigInitParameters `json:"secondaryWorkerConfig,omitempty" tf:"secondary_worker_config,omitempty"`
// Describes how the autoscaler will operate for primary workers.
// Structure is documented below.
WorkerConfig *WorkerConfigInitParameters `json:"workerConfig,omitempty" tf:"worker_config,omitempty"`
}
type AutoscalingPolicyObservation struct {
// Basic algorithm for autoscaling.
// Structure is documented below.
BasicAlgorithm *BasicAlgorithmObservation `json:"basicAlgorithm,omitempty" tf:"basic_algorithm,omitempty"`
// an identifier for the resource with format projects/{{project}}/locations/{{location}}/autoscalingPolicies/{{policy_id}}
ID *string `json:"id,omitempty" tf:"id,omitempty"`
// The location where the autoscaling policy should reside.
// The default value is global.
Location *string `json:"location,omitempty" tf:"location,omitempty"`
// The "resource name" of the autoscaling policy.
Name *string `json:"name,omitempty" tf:"name,omitempty"`
// The ID of the project in which the resource belongs.
// If it is not provided, the provider project is used.
Project *string `json:"project,omitempty" tf:"project,omitempty"`
// Describes how the autoscaler will operate for secondary workers.
// Structure is documented below.
SecondaryWorkerConfig *SecondaryWorkerConfigObservation `json:"secondaryWorkerConfig,omitempty" tf:"secondary_worker_config,omitempty"`
// Describes how the autoscaler will operate for primary workers.
// Structure is documented below.
WorkerConfig *WorkerConfigObservation `json:"workerConfig,omitempty" tf:"worker_config,omitempty"`
}
type AutoscalingPolicyParameters struct {
// Basic algorithm for autoscaling.
// Structure is documented below.
// +kubebuilder:validation:Optional
BasicAlgorithm *BasicAlgorithmParameters `json:"basicAlgorithm,omitempty" tf:"basic_algorithm,omitempty"`
// The location where the autoscaling policy should reside.
// The default value is global.
// +kubebuilder:validation:Optional
Location *string `json:"location,omitempty" tf:"location,omitempty"`
// The ID of the project in which the resource belongs.
// If it is not provided, the provider project is used.
// +kubebuilder:validation:Optional
Project *string `json:"project,omitempty" tf:"project,omitempty"`
// Describes how the autoscaler will operate for secondary workers.
// Structure is documented below.
// +kubebuilder:validation:Optional
SecondaryWorkerConfig *SecondaryWorkerConfigParameters `json:"secondaryWorkerConfig,omitempty" tf:"secondary_worker_config,omitempty"`
// Describes how the autoscaler will operate for primary workers.
// Structure is documented below.
// +kubebuilder:validation:Optional
WorkerConfig *WorkerConfigParameters `json:"workerConfig,omitempty" tf:"worker_config,omitempty"`
}
type BasicAlgorithmInitParameters struct {
// Duration between scaling events. A scaling period starts after the
// update operation from the previous event has completed.
// Bounds: [2m, 1d]. Default: 2m.
CooldownPeriod *string `json:"cooldownPeriod,omitempty" tf:"cooldown_period,omitempty"`
// YARN autoscaling configuration.
// Structure is documented below.
YarnConfig *YarnConfigInitParameters `json:"yarnConfig,omitempty" tf:"yarn_config,omitempty"`
}
type BasicAlgorithmObservation struct {
// Duration between scaling events. A scaling period starts after the
// update operation from the previous event has completed.
// Bounds: [2m, 1d]. Default: 2m.
CooldownPeriod *string `json:"cooldownPeriod,omitempty" tf:"cooldown_period,omitempty"`
// YARN autoscaling configuration.
// Structure is documented below.
YarnConfig *YarnConfigObservation `json:"yarnConfig,omitempty" tf:"yarn_config,omitempty"`
}
type BasicAlgorithmParameters struct {
// Duration between scaling events. A scaling period starts after the
// update operation from the previous event has completed.
// Bounds: [2m, 1d]. Default: 2m.
// +kubebuilder:validation:Optional
CooldownPeriod *string `json:"cooldownPeriod,omitempty" tf:"cooldown_period,omitempty"`
// YARN autoscaling configuration.
// Structure is documented below.
// +kubebuilder:validation:Optional
YarnConfig *YarnConfigParameters `json:"yarnConfig" tf:"yarn_config,omitempty"`
}
type SecondaryWorkerConfigInitParameters struct {
// Maximum number of instances for this group. Note that by default, clusters will not use
// secondary workers. Required for secondary workers if the minimum secondary instances is set.
// Bounds: [minInstances, ). Defaults to 0.
MaxInstances *float64 `json:"maxInstances,omitempty" tf:"max_instances,omitempty"`
// Minimum number of instances for this group. Bounds: [0, maxInstances]. Defaults to 0.
MinInstances *float64 `json:"minInstances,omitempty" tf:"min_instances,omitempty"`
// Weight for the instance group, which is used to determine the fraction of total workers
// in the cluster from this instance group. For example, if primary workers have weight 2,
// and secondary workers have weight 1, the cluster will have approximately 2 primary workers
// for each secondary worker.
// The cluster may not reach the specified balance if constrained by min/max bounds or other
// autoscaling settings. For example, if maxInstances for secondary workers is 0, then only
// primary workers will be added. The cluster can also be out of balance when created.
// If weight is not set on any instance group, the cluster will default to equal weight for
// all groups: the cluster will attempt to maintain an equal number of workers in each group
// within the configured size bounds for each group. If weight is set for one group only,
// the cluster will default to zero weight on the unset group. For example if weight is set
// only on primary workers, the cluster will use primary workers only and no secondary workers.
Weight *float64 `json:"weight,omitempty" tf:"weight,omitempty"`
}
type SecondaryWorkerConfigObservation struct {
// Maximum number of instances for this group. Note that by default, clusters will not use
// secondary workers. Required for secondary workers if the minimum secondary instances is set.
// Bounds: [minInstances, ). Defaults to 0.
MaxInstances *float64 `json:"maxInstances,omitempty" tf:"max_instances,omitempty"`
// Minimum number of instances for this group. Bounds: [0, maxInstances]. Defaults to 0.
MinInstances *float64 `json:"minInstances,omitempty" tf:"min_instances,omitempty"`
// Weight for the instance group, which is used to determine the fraction of total workers
// in the cluster from this instance group. For example, if primary workers have weight 2,
// and secondary workers have weight 1, the cluster will have approximately 2 primary workers
// for each secondary worker.
// The cluster may not reach the specified balance if constrained by min/max bounds or other
// autoscaling settings. For example, if maxInstances for secondary workers is 0, then only
// primary workers will be added. The cluster can also be out of balance when created.
// If weight is not set on any instance group, the cluster will default to equal weight for
// all groups: the cluster will attempt to maintain an equal number of workers in each group
// within the configured size bounds for each group. If weight is set for one group only,
// the cluster will default to zero weight on the unset group. For example if weight is set
// only on primary workers, the cluster will use primary workers only and no secondary workers.
Weight *float64 `json:"weight,omitempty" tf:"weight,omitempty"`
}
type SecondaryWorkerConfigParameters struct {
// Maximum number of instances for this group. Note that by default, clusters will not use
// secondary workers. Required for secondary workers if the minimum secondary instances is set.
// Bounds: [minInstances, ). Defaults to 0.
// +kubebuilder:validation:Optional
MaxInstances *float64 `json:"maxInstances,omitempty" tf:"max_instances,omitempty"`
// Minimum number of instances for this group. Bounds: [0, maxInstances]. Defaults to 0.
// +kubebuilder:validation:Optional
MinInstances *float64 `json:"minInstances,omitempty" tf:"min_instances,omitempty"`
// Weight for the instance group, which is used to determine the fraction of total workers
// in the cluster from this instance group. For example, if primary workers have weight 2,
// and secondary workers have weight 1, the cluster will have approximately 2 primary workers
// for each secondary worker.
// The cluster may not reach the specified balance if constrained by min/max bounds or other
// autoscaling settings. For example, if maxInstances for secondary workers is 0, then only
// primary workers will be added. The cluster can also be out of balance when created.
// If weight is not set on any instance group, the cluster will default to equal weight for
// all groups: the cluster will attempt to maintain an equal number of workers in each group
// within the configured size bounds for each group. If weight is set for one group only,
// the cluster will default to zero weight on the unset group. For example if weight is set
// only on primary workers, the cluster will use primary workers only and no secondary workers.
// +kubebuilder:validation:Optional
Weight *float64 `json:"weight,omitempty" tf:"weight,omitempty"`
}
type WorkerConfigInitParameters struct {
// Maximum number of instances for this group.
MaxInstances *float64 `json:"maxInstances,omitempty" tf:"max_instances,omitempty"`
// Minimum number of instances for this group. Bounds: [2, maxInstances]. Defaults to 2.
MinInstances *float64 `json:"minInstances,omitempty" tf:"min_instances,omitempty"`
// Weight for the instance group, which is used to determine the fraction of total workers
// in the cluster from this instance group. For example, if primary workers have weight 2,
// and secondary workers have weight 1, the cluster will have approximately 2 primary workers
// for each secondary worker.
// The cluster may not reach the specified balance if constrained by min/max bounds or other
// autoscaling settings. For example, if maxInstances for secondary workers is 0, then only
// primary workers will be added. The cluster can also be out of balance when created.
// If weight is not set on any instance group, the cluster will default to equal weight for
// all groups: the cluster will attempt to maintain an equal number of workers in each group
// within the configured size bounds for each group. If weight is set for one group only,
// the cluster will default to zero weight on the unset group. For example if weight is set
// only on primary workers, the cluster will use primary workers only and no secondary workers.
Weight *float64 `json:"weight,omitempty" tf:"weight,omitempty"`
}
type WorkerConfigObservation struct {
// Maximum number of instances for this group.
MaxInstances *float64 `json:"maxInstances,omitempty" tf:"max_instances,omitempty"`
// Minimum number of instances for this group. Bounds: [2, maxInstances]. Defaults to 2.
MinInstances *float64 `json:"minInstances,omitempty" tf:"min_instances,omitempty"`
// Weight for the instance group, which is used to determine the fraction of total workers
// in the cluster from this instance group. For example, if primary workers have weight 2,
// and secondary workers have weight 1, the cluster will have approximately 2 primary workers
// for each secondary worker.
// The cluster may not reach the specified balance if constrained by min/max bounds or other
// autoscaling settings. For example, if maxInstances for secondary workers is 0, then only
// primary workers will be added. The cluster can also be out of balance when created.
// If weight is not set on any instance group, the cluster will default to equal weight for
// all groups: the cluster will attempt to maintain an equal number of workers in each group
// within the configured size bounds for each group. If weight is set for one group only,
// the cluster will default to zero weight on the unset group. For example if weight is set
// only on primary workers, the cluster will use primary workers only and no secondary workers.
Weight *float64 `json:"weight,omitempty" tf:"weight,omitempty"`
}
type WorkerConfigParameters struct {
// Maximum number of instances for this group.
// +kubebuilder:validation:Optional
MaxInstances *float64 `json:"maxInstances" tf:"max_instances,omitempty"`
// Minimum number of instances for this group. Bounds: [2, maxInstances]. Defaults to 2.
// +kubebuilder:validation:Optional
MinInstances *float64 `json:"minInstances,omitempty" tf:"min_instances,omitempty"`
// Weight for the instance group, which is used to determine the fraction of total workers
// in the cluster from this instance group. For example, if primary workers have weight 2,
// and secondary workers have weight 1, the cluster will have approximately 2 primary workers
// for each secondary worker.
// The cluster may not reach the specified balance if constrained by min/max bounds or other
// autoscaling settings. For example, if maxInstances for secondary workers is 0, then only
// primary workers will be added. The cluster can also be out of balance when created.
// If weight is not set on any instance group, the cluster will default to equal weight for
// all groups: the cluster will attempt to maintain an equal number of workers in each group
// within the configured size bounds for each group. If weight is set for one group only,
// the cluster will default to zero weight on the unset group. For example if weight is set
// only on primary workers, the cluster will use primary workers only and no secondary workers.
// +kubebuilder:validation:Optional
Weight *float64 `json:"weight,omitempty" tf:"weight,omitempty"`
}
type YarnConfigInitParameters struct {
// Timeout for YARN graceful decommissioning of Node Managers. Specifies the
// duration to wait for jobs to complete before forcefully removing workers
// (and potentially interrupting jobs). Only applicable to downscaling operations.
// Bounds: [0s, 1d].
GracefulDecommissionTimeout *string `json:"gracefulDecommissionTimeout,omitempty" tf:"graceful_decommission_timeout,omitempty"`
// Fraction of average pending memory in the last cooldown period for which to
// remove workers. A scale-down factor of 1 will result in scaling down so that there
// is no available memory remaining after the update (more aggressive scaling).
// A scale-down factor of 0 disables removing workers, which can be beneficial for
// autoscaling a single job.
// Bounds: [0.0, 1.0].
ScaleDownFactor *float64 `json:"scaleDownFactor,omitempty" tf:"scale_down_factor,omitempty"`
// Minimum scale-down threshold as a fraction of total cluster size before scaling occurs.
// For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must
// recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0
// means the autoscaler will scale down on any recommended change.
// Bounds: [0.0, 1.0]. Default: 0.0.
ScaleDownMinWorkerFraction *float64 `json:"scaleDownMinWorkerFraction,omitempty" tf:"scale_down_min_worker_fraction,omitempty"`
// Fraction of average pending memory in the last cooldown period for which to
// add workers. A scale-up factor of 1.0 will result in scaling up so that there
// is no pending memory remaining after the update (more aggressive scaling).
// A scale-up factor closer to 0 will result in a smaller magnitude of scaling up
// (less aggressive scaling).
// Bounds: [0.0, 1.0].
ScaleUpFactor *float64 `json:"scaleUpFactor,omitempty" tf:"scale_up_factor,omitempty"`
// Minimum scale-up threshold as a fraction of total cluster size before scaling
// occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler
// must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of
// 0 means the autoscaler will scale up on any recommended change.
// Bounds: [0.0, 1.0]. Default: 0.0.
ScaleUpMinWorkerFraction *float64 `json:"scaleUpMinWorkerFraction,omitempty" tf:"scale_up_min_worker_fraction,omitempty"`
}
type YarnConfigObservation struct {
// Timeout for YARN graceful decommissioning of Node Managers. Specifies the
// duration to wait for jobs to complete before forcefully removing workers
// (and potentially interrupting jobs). Only applicable to downscaling operations.
// Bounds: [0s, 1d].
GracefulDecommissionTimeout *string `json:"gracefulDecommissionTimeout,omitempty" tf:"graceful_decommission_timeout,omitempty"`
// Fraction of average pending memory in the last cooldown period for which to
// remove workers. A scale-down factor of 1 will result in scaling down so that there
// is no available memory remaining after the update (more aggressive scaling).
// A scale-down factor of 0 disables removing workers, which can be beneficial for
// autoscaling a single job.
// Bounds: [0.0, 1.0].
ScaleDownFactor *float64 `json:"scaleDownFactor,omitempty" tf:"scale_down_factor,omitempty"`
// Minimum scale-down threshold as a fraction of total cluster size before scaling occurs.
// For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must
// recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0
// means the autoscaler will scale down on any recommended change.
// Bounds: [0.0, 1.0]. Default: 0.0.
ScaleDownMinWorkerFraction *float64 `json:"scaleDownMinWorkerFraction,omitempty" tf:"scale_down_min_worker_fraction,omitempty"`
// Fraction of average pending memory in the last cooldown period for which to
// add workers. A scale-up factor of 1.0 will result in scaling up so that there
// is no pending memory remaining after the update (more aggressive scaling).
// A scale-up factor closer to 0 will result in a smaller magnitude of scaling up
// (less aggressive scaling).
// Bounds: [0.0, 1.0].
ScaleUpFactor *float64 `json:"scaleUpFactor,omitempty" tf:"scale_up_factor,omitempty"`
// Minimum scale-up threshold as a fraction of total cluster size before scaling
// occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler
// must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of
// 0 means the autoscaler will scale up on any recommended change.
// Bounds: [0.0, 1.0]. Default: 0.0.
ScaleUpMinWorkerFraction *float64 `json:"scaleUpMinWorkerFraction,omitempty" tf:"scale_up_min_worker_fraction,omitempty"`
}
type YarnConfigParameters struct {
// Timeout for YARN graceful decommissioning of Node Managers. Specifies the
// duration to wait for jobs to complete before forcefully removing workers
// (and potentially interrupting jobs). Only applicable to downscaling operations.
// Bounds: [0s, 1d].
// +kubebuilder:validation:Optional
GracefulDecommissionTimeout *string `json:"gracefulDecommissionTimeout" tf:"graceful_decommission_timeout,omitempty"`
// Fraction of average pending memory in the last cooldown period for which to
// remove workers. A scale-down factor of 1 will result in scaling down so that there
// is no available memory remaining after the update (more aggressive scaling).
// A scale-down factor of 0 disables removing workers, which can be beneficial for
// autoscaling a single job.
// Bounds: [0.0, 1.0].
// +kubebuilder:validation:Optional
ScaleDownFactor *float64 `json:"scaleDownFactor" tf:"scale_down_factor,omitempty"`
// Minimum scale-down threshold as a fraction of total cluster size before scaling occurs.
// For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler must
// recommend at least a 2 worker scale-down for the cluster to scale. A threshold of 0
// means the autoscaler will scale down on any recommended change.
// Bounds: [0.0, 1.0]. Default: 0.0.
// +kubebuilder:validation:Optional
ScaleDownMinWorkerFraction *float64 `json:"scaleDownMinWorkerFraction,omitempty" tf:"scale_down_min_worker_fraction,omitempty"`
// Fraction of average pending memory in the last cooldown period for which to
// add workers. A scale-up factor of 1.0 will result in scaling up so that there
// is no pending memory remaining after the update (more aggressive scaling).
// A scale-up factor closer to 0 will result in a smaller magnitude of scaling up
// (less aggressive scaling).
// Bounds: [0.0, 1.0].
// +kubebuilder:validation:Optional
ScaleUpFactor *float64 `json:"scaleUpFactor" tf:"scale_up_factor,omitempty"`
// Minimum scale-up threshold as a fraction of total cluster size before scaling
// occurs. For example, in a 20-worker cluster, a threshold of 0.1 means the autoscaler
// must recommend at least a 2-worker scale-up for the cluster to scale. A threshold of
// 0 means the autoscaler will scale up on any recommended change.
// Bounds: [0.0, 1.0]. Default: 0.0.
// +kubebuilder:validation:Optional
ScaleUpMinWorkerFraction *float64 `json:"scaleUpMinWorkerFraction,omitempty" tf:"scale_up_min_worker_fraction,omitempty"`
}
// AutoscalingPolicySpec defines the desired state of AutoscalingPolicy
type AutoscalingPolicySpec struct {
v1.ResourceSpec `json:",inline"`
ForProvider AutoscalingPolicyParameters `json:"forProvider"`
// THIS IS A BETA FIELD. It will be honored
// unless the Management Policies feature flag is disabled.
// InitProvider holds the same fields as ForProvider, with the exception
// of Identifier and other resource reference fields. The fields that are
// in InitProvider are merged into ForProvider when the resource is created.
// The same fields are also added to the terraform ignore_changes hook, to
// avoid updating them after creation. This is useful for fields that are
// required on creation, but we do not desire to update them after creation,
// for example because of an external controller is managing them, like an
// autoscaler.
InitProvider AutoscalingPolicyInitParameters `json:"initProvider,omitempty"`
}
// AutoscalingPolicyStatus defines the observed state of AutoscalingPolicy.
type AutoscalingPolicyStatus struct {
v1.ResourceStatus `json:",inline"`
AtProvider AutoscalingPolicyObservation `json:"atProvider,omitempty"`
}
// +kubebuilder:object:root=true
// +kubebuilder:subresource:status
// AutoscalingPolicy is the Schema for the AutoscalingPolicys API. Describes an autoscaling policy for Dataproc cluster autoscaler.
// +kubebuilder:printcolumn:name="SYNCED",type="string",JSONPath=".status.conditions[?(@.type=='Synced')].status"
// +kubebuilder:printcolumn:name="READY",type="string",JSONPath=".status.conditions[?(@.type=='Ready')].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:resource:scope=Cluster,categories={crossplane,managed,gcp}
type AutoscalingPolicy struct {
metav1.TypeMeta `json:",inline"`
metav1.ObjectMeta `json:"metadata,omitempty"`
Spec AutoscalingPolicySpec `json:"spec"`
Status AutoscalingPolicyStatus `json:"status,omitempty"`
}
// +kubebuilder:object:root=true
// AutoscalingPolicyList contains a list of AutoscalingPolicys
type AutoscalingPolicyList struct {
metav1.TypeMeta `json:",inline"`
metav1.ListMeta `json:"metadata,omitempty"`
Items []AutoscalingPolicy `json:"items"`
}
// Repository type metadata.
var (
AutoscalingPolicy_Kind = "AutoscalingPolicy"
AutoscalingPolicy_GroupKind = schema.GroupKind{Group: CRDGroup, Kind: AutoscalingPolicy_Kind}.String()
AutoscalingPolicy_KindAPIVersion = AutoscalingPolicy_Kind + "." + CRDGroupVersion.String()
AutoscalingPolicy_GroupVersionKind = CRDGroupVersion.WithKind(AutoscalingPolicy_Kind)
)
func init() {
SchemeBuilder.Register(&AutoscalingPolicy{}, &AutoscalingPolicyList{})
}