aws_sdk_computeoptimizer::types::builders

Struct AutoScalingGroupRecommendationBuilder

#[non_exhaustive]
pub struct AutoScalingGroupRecommendationBuilder { /* private fields */ }

Expand description

A builder for AutoScalingGroupRecommendation.

Implementations§

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impl AutoScalingGroupRecommendationBuilder

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pub fn account_id(self, input: impl Into<String>) -> Self

The Amazon Web Services account ID of the Auto Scaling group.

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pub fn set_account_id(self, input: Option<String>) -> Self

The Amazon Web Services account ID of the Auto Scaling group.

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pub fn get_account_id(&self) -> &Option<String>

The Amazon Web Services account ID of the Auto Scaling group.

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pub fn auto_scaling_group_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Name (ARN) of the Auto Scaling group.

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pub fn set_auto_scaling_group_arn(self, input: Option<String>) -> Self

The Amazon Resource Name (ARN) of the Auto Scaling group.

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pub fn get_auto_scaling_group_arn(&self) -> &Option<String>

The Amazon Resource Name (ARN) of the Auto Scaling group.

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pub fn auto_scaling_group_name(self, input: impl Into<String>) -> Self

The name of the Auto Scaling group.

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pub fn set_auto_scaling_group_name(self, input: Option<String>) -> Self

The name of the Auto Scaling group.

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pub fn get_auto_scaling_group_name(&self) -> &Option<String>

The name of the Auto Scaling group.

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pub fn finding(self, input: Finding) -> Self

The finding classification of the Auto Scaling group.

Findings for Auto Scaling groups include:

NotOptimized —An Auto Scaling group is considered not optimized when Compute Optimizer identifies a recommendation that can provide better performance for your workload.
Optimized —An Auto Scaling group is considered optimized when Compute Optimizer determines that the group is correctly provisioned to run your workload based on the chosen instance type. For optimized resources, Compute Optimizer might recommend a new generation instance type.

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pub fn set_finding(self, input: Option<Finding>) -> Self

The finding classification of the Auto Scaling group.

Findings for Auto Scaling groups include:

NotOptimized —An Auto Scaling group is considered not optimized when Compute Optimizer identifies a recommendation that can provide better performance for your workload.
Optimized —An Auto Scaling group is considered optimized when Compute Optimizer determines that the group is correctly provisioned to run your workload based on the chosen instance type. For optimized resources, Compute Optimizer might recommend a new generation instance type.

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pub fn get_finding(&self) -> &Option<Finding>

The finding classification of the Auto Scaling group.

Findings for Auto Scaling groups include:

NotOptimized —An Auto Scaling group is considered not optimized when Compute Optimizer identifies a recommendation that can provide better performance for your workload.
Optimized —An Auto Scaling group is considered optimized when Compute Optimizer determines that the group is correctly provisioned to run your workload based on the chosen instance type. For optimized resources, Compute Optimizer might recommend a new generation instance type.

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pub fn utilization_metrics(self, input: UtilizationMetric) -> Self

Appends an item to utilization_metrics.

To override the contents of this collection use set_utilization_metrics.

An array of objects that describe the utilization metrics of the Auto Scaling group.

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pub fn set_utilization_metrics( self, input: Option<Vec<UtilizationMetric>>, ) -> Self

An array of objects that describe the utilization metrics of the Auto Scaling group.

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pub fn get_utilization_metrics(&self) -> &Option<Vec<UtilizationMetric>>

An array of objects that describe the utilization metrics of the Auto Scaling group.

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pub fn look_back_period_in_days(self, input: f64) -> Self

The number of days for which utilization metrics were analyzed for the Auto Scaling group.

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pub fn set_look_back_period_in_days(self, input: Option<f64>) -> Self

The number of days for which utilization metrics were analyzed for the Auto Scaling group.

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pub fn get_look_back_period_in_days(&self) -> &Option<f64>

The number of days for which utilization metrics were analyzed for the Auto Scaling group.

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pub fn current_configuration(self, input: AutoScalingGroupConfiguration) -> Self

An array of objects that describe the current configuration of the Auto Scaling group.

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pub fn set_current_configuration( self, input: Option<AutoScalingGroupConfiguration>, ) -> Self

An array of objects that describe the current configuration of the Auto Scaling group.

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pub fn get_current_configuration( &self, ) -> &Option<AutoScalingGroupConfiguration>

An array of objects that describe the current configuration of the Auto Scaling group.

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pub fn current_instance_gpu_info(self, input: GpuInfo) -> Self

Describes the GPU accelerator settings for the current instance type of the Auto Scaling group.

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pub fn set_current_instance_gpu_info(self, input: Option<GpuInfo>) -> Self

Describes the GPU accelerator settings for the current instance type of the Auto Scaling group.

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pub fn get_current_instance_gpu_info(&self) -> &Option<GpuInfo>

Describes the GPU accelerator settings for the current instance type of the Auto Scaling group.

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pub fn recommendation_options( self, input: AutoScalingGroupRecommendationOption, ) -> Self

Appends an item to recommendation_options.

To override the contents of this collection use set_recommendation_options.

An array of objects that describe the recommendation options for the Auto Scaling group.

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pub fn set_recommendation_options( self, input: Option<Vec<AutoScalingGroupRecommendationOption>>, ) -> Self

An array of objects that describe the recommendation options for the Auto Scaling group.

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pub fn get_recommendation_options( &self, ) -> &Option<Vec<AutoScalingGroupRecommendationOption>>

An array of objects that describe the recommendation options for the Auto Scaling group.

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pub fn last_refresh_timestamp(self, input: DateTime) -> Self

The timestamp of when the Auto Scaling group recommendation was last generated.

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pub fn set_last_refresh_timestamp(self, input: Option<DateTime>) -> Self

The timestamp of when the Auto Scaling group recommendation was last generated.

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pub fn get_last_refresh_timestamp(&self) -> &Option<DateTime>

The timestamp of when the Auto Scaling group recommendation was last generated.

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pub fn current_performance_risk(self, input: CurrentPerformanceRisk) -> Self

The risk of the current Auto Scaling group not meeting the performance needs of its workloads. The higher the risk, the more likely the current Auto Scaling group configuration has insufficient capacity and cannot meet workload requirements.

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pub fn set_current_performance_risk( self, input: Option<CurrentPerformanceRisk>, ) -> Self

The risk of the current Auto Scaling group not meeting the performance needs of its workloads. The higher the risk, the more likely the current Auto Scaling group configuration has insufficient capacity and cannot meet workload requirements.

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pub fn get_current_performance_risk(&self) -> &Option<CurrentPerformanceRisk>

The risk of the current Auto Scaling group not meeting the performance needs of its workloads. The higher the risk, the more likely the current Auto Scaling group configuration has insufficient capacity and cannot meet workload requirements.

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pub fn effective_recommendation_preferences( self, input: EffectiveRecommendationPreferences, ) -> Self

An object that describes the effective recommendation preferences for the Auto Scaling group.

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pub fn set_effective_recommendation_preferences( self, input: Option<EffectiveRecommendationPreferences>, ) -> Self

An object that describes the effective recommendation preferences for the Auto Scaling group.

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pub fn get_effective_recommendation_preferences( &self, ) -> &Option<EffectiveRecommendationPreferences>

An object that describes the effective recommendation preferences for the Auto Scaling group.

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pub fn inferred_workload_types(self, input: InferredWorkloadType) -> Self

Appends an item to inferred_workload_types.

To override the contents of this collection use set_inferred_workload_types.

The applications that might be running on the instances in the Auto Scaling group as inferred by Compute Optimizer.

Compute Optimizer can infer if one of the following applications might be running on the instances:

AmazonEmr - Infers that Amazon EMR might be running on the instances.
ApacheCassandra - Infers that Apache Cassandra might be running on the instances.
ApacheHadoop - Infers that Apache Hadoop might be running on the instances.
Memcached - Infers that Memcached might be running on the instances.
NGINX - Infers that NGINX might be running on the instances.
PostgreSql - Infers that PostgreSQL might be running on the instances.
Redis - Infers that Redis might be running on the instances.
Kafka - Infers that Kafka might be running on the instance.
SQLServer - Infers that SQLServer might be running on the instance.

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pub fn set_inferred_workload_types( self, input: Option<Vec<InferredWorkloadType>>, ) -> Self

The applications that might be running on the instances in the Auto Scaling group as inferred by Compute Optimizer.

Compute Optimizer can infer if one of the following applications might be running on the instances:

AmazonEmr - Infers that Amazon EMR might be running on the instances.
ApacheCassandra - Infers that Apache Cassandra might be running on the instances.
ApacheHadoop - Infers that Apache Hadoop might be running on the instances.
Memcached - Infers that Memcached might be running on the instances.
NGINX - Infers that NGINX might be running on the instances.
PostgreSql - Infers that PostgreSQL might be running on the instances.
Redis - Infers that Redis might be running on the instances.
Kafka - Infers that Kafka might be running on the instance.
SQLServer - Infers that SQLServer might be running on the instance.

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pub fn get_inferred_workload_types(&self) -> &Option<Vec<InferredWorkloadType>>

The applications that might be running on the instances in the Auto Scaling group as inferred by Compute Optimizer.

Compute Optimizer can infer if one of the following applications might be running on the instances:

AmazonEmr - Infers that Amazon EMR might be running on the instances.
ApacheCassandra - Infers that Apache Cassandra might be running on the instances.
ApacheHadoop - Infers that Apache Hadoop might be running on the instances.
Memcached - Infers that Memcached might be running on the instances.
NGINX - Infers that NGINX might be running on the instances.
PostgreSql - Infers that PostgreSQL might be running on the instances.
Redis - Infers that Redis might be running on the instances.
Kafka - Infers that Kafka might be running on the instance.
SQLServer - Infers that SQLServer might be running on the instance.

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pub fn build(self) -> AutoScalingGroupRecommendation

Consumes the builder and constructs a AutoScalingGroupRecommendation.

Trait Implementations§

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impl Clone for AutoScalingGroupRecommendationBuilder

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fn clone(&self) -> AutoScalingGroupRecommendationBuilder

Returns a duplicate of the value. Read more

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const fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more

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impl Debug for AutoScalingGroupRecommendationBuilder

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more

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impl Default for AutoScalingGroupRecommendationBuilder

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fn default() -> AutoScalingGroupRecommendationBuilder

Returns the “default value” for a type. Read more

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impl PartialEq for AutoScalingGroupRecommendationBuilder

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fn eq(&self, other: &AutoScalingGroupRecommendationBuilder) -> bool

Tests for self and other values to be equal, and is used by ==.

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const fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

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impl StructuralPartialEq for AutoScalingGroupRecommendationBuilder

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impl UnwindSafe for AutoScalingGroupRecommendationBuilder

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Struct AutoScalingGroupRecommendationBuilderCopy item path

Implementations§

impl AutoScalingGroupRecommendationBuilder

pub fn account_id(self, input: impl Into<String>) -> Self

pub fn set_account_id(self, input: Option<String>) -> Self

pub fn get_account_id(&self) -> &Option<String>

pub fn auto_scaling_group_arn(self, input: impl Into<String>) -> Self

pub fn set_auto_scaling_group_arn(self, input: Option<String>) -> Self

pub fn get_auto_scaling_group_arn(&self) -> &Option<String>

pub fn auto_scaling_group_name(self, input: impl Into<String>) -> Self

pub fn set_auto_scaling_group_name(self, input: Option<String>) -> Self

pub fn get_auto_scaling_group_name(&self) -> &Option<String>

pub fn finding(self, input: Finding) -> Self

pub fn set_finding(self, input: Option<Finding>) -> Self

pub fn get_finding(&self) -> &Option<Finding>

pub fn utilization_metrics(self, input: UtilizationMetric) -> Self

pub fn set_utilization_metrics( self, input: Option<Vec<UtilizationMetric>>, ) -> Self

pub fn get_utilization_metrics(&self) -> &Option<Vec<UtilizationMetric>>

pub fn look_back_period_in_days(self, input: f64) -> Self

pub fn set_look_back_period_in_days(self, input: Option<f64>) -> Self

pub fn get_look_back_period_in_days(&self) -> &Option<f64>

pub fn current_configuration(self, input: AutoScalingGroupConfiguration) -> Self

pub fn set_current_configuration( self, input: Option<AutoScalingGroupConfiguration>, ) -> Self

pub fn get_current_configuration( &self, ) -> &Option<AutoScalingGroupConfiguration>

pub fn current_instance_gpu_info(self, input: GpuInfo) -> Self

pub fn set_current_instance_gpu_info(self, input: Option<GpuInfo>) -> Self

pub fn get_current_instance_gpu_info(&self) -> &Option<GpuInfo>

pub fn recommendation_options( self, input: AutoScalingGroupRecommendationOption, ) -> Self

pub fn set_recommendation_options( self, input: Option<Vec<AutoScalingGroupRecommendationOption>>, ) -> Self

pub fn get_recommendation_options( &self, ) -> &Option<Vec<AutoScalingGroupRecommendationOption>>

pub fn last_refresh_timestamp(self, input: DateTime) -> Self

pub fn set_last_refresh_timestamp(self, input: Option<DateTime>) -> Self

pub fn get_last_refresh_timestamp(&self) -> &Option<DateTime>

pub fn current_performance_risk(self, input: CurrentPerformanceRisk) -> Self

pub fn set_current_performance_risk( self, input: Option<CurrentPerformanceRisk>, ) -> Self

pub fn get_current_performance_risk(&self) -> &Option<CurrentPerformanceRisk>

pub fn effective_recommendation_preferences( self, input: EffectiveRecommendationPreferences, ) -> Self

pub fn set_effective_recommendation_preferences( self, input: Option<EffectiveRecommendationPreferences>, ) -> Self

pub fn get_effective_recommendation_preferences( &self, ) -> &Option<EffectiveRecommendationPreferences>

pub fn inferred_workload_types(self, input: InferredWorkloadType) -> Self

pub fn set_inferred_workload_types( self, input: Option<Vec<InferredWorkloadType>>, ) -> Self

pub fn get_inferred_workload_types(&self) -> &Option<Vec<InferredWorkloadType>>

pub fn build(self) -> AutoScalingGroupRecommendation

Trait Implementations§

impl Clone for AutoScalingGroupRecommendationBuilder

fn clone(&self) -> AutoScalingGroupRecommendationBuilder

const fn clone_from(&mut self, source: &Self)

impl Debug for AutoScalingGroupRecommendationBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

impl Default for AutoScalingGroupRecommendationBuilder

fn default() -> AutoScalingGroupRecommendationBuilder

impl PartialEq for AutoScalingGroupRecommendationBuilder

fn eq(&self, other: &AutoScalingGroupRecommendationBuilder) -> bool

const fn ne(&self, other: &Rhs) -> bool

impl StructuralPartialEq for AutoScalingGroupRecommendationBuilder

Auto Trait Implementations§

impl Freeze for AutoScalingGroupRecommendationBuilder

impl RefUnwindSafe for AutoScalingGroupRecommendationBuilder

impl Send for AutoScalingGroupRecommendationBuilder

impl Sync for AutoScalingGroupRecommendationBuilder

impl Unpin for AutoScalingGroupRecommendationBuilder

impl UnwindSafe for AutoScalingGroupRecommendationBuilder

Blanket Implementations§

impl<T> Any for Twhere T: 'static + ?Sized,

fn type_id(&self) -> TypeId

impl<T> Borrow<T> for Twhere T: ?Sized,

fn borrow(&self) -> &T

impl<T> BorrowMut<T> for Twhere T: ?Sized,

fn borrow_mut(&mut self) -> &mut T

impl<T> CloneToUninit for Twhere T: Clone,

unsafe fn clone_to_uninit(&self, dest: *mut u8)

impl<T> From<T> for T

fn from(t: T) -> T

impl<T> Instrument for T

fn instrument(self, span: Span) -> Instrumented<Self>

fn in_current_span(self) -> Instrumented<Self>

impl<T, U> Into<U> for Twhere U: From<T>,

fn into(self) -> U

impl<T> IntoEither for T

fn into_either(self, into_left: bool) -> Either<Self, Self>

Struct AutoScalingGroupRecommendationBuilder

impl<T> Any for T
where T: 'static + ?Sized,

impl<T> Borrow<T> for T
where T: ?Sized,

impl<T> BorrowMut<T> for T
where T: ?Sized,

impl<T> CloneToUninit for T
where T: Clone,

impl<T, U> Into<U> for T
where U: From<T>,

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unshared
where Shared: FromUnshared<Unshared>,

impl<T> Paint for T
where T: ?Sized,