aws-sdk-computeoptimizer 1.102.0

AWS SDK for AWS Compute Optimizer
Documentation
// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::put_recommendation_preferences::_put_recommendation_preferences_input::PutRecommendationPreferencesInputBuilder;

pub use crate::operation::put_recommendation_preferences::_put_recommendation_preferences_output::PutRecommendationPreferencesOutputBuilder;

impl crate::operation::put_recommendation_preferences::builders::PutRecommendationPreferencesInputBuilder {
    /// Sends a request with this input using the given client.
    pub async fn send_with(
        self,
        client: &crate::Client,
    ) -> ::std::result::Result<
        crate::operation::put_recommendation_preferences::PutRecommendationPreferencesOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::put_recommendation_preferences::PutRecommendationPreferencesError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.put_recommendation_preferences();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `PutRecommendationPreferences`.
///
/// <p>Creates a new recommendation preference or updates an existing recommendation preference, such as enhanced infrastructure metrics.</p>
/// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/enhanced-infrastructure-metrics.html">Activating enhanced infrastructure metrics</a> in the <i>Compute Optimizer User Guide</i>.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct PutRecommendationPreferencesFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::put_recommendation_preferences::builders::PutRecommendationPreferencesInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::put_recommendation_preferences::PutRecommendationPreferencesOutput,
        crate::operation::put_recommendation_preferences::PutRecommendationPreferencesError,
    > for PutRecommendationPreferencesFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::put_recommendation_preferences::PutRecommendationPreferencesOutput,
            crate::operation::put_recommendation_preferences::PutRecommendationPreferencesError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl PutRecommendationPreferencesFluentBuilder {
    /// Creates a new `PutRecommendationPreferencesFluentBuilder`.
    pub(crate) fn new(handle: ::std::sync::Arc<crate::client::Handle>) -> Self {
        Self {
            handle,
            inner: ::std::default::Default::default(),
            config_override: ::std::option::Option::None,
        }
    }
    /// Access the PutRecommendationPreferences as a reference.
    pub fn as_input(&self) -> &crate::operation::put_recommendation_preferences::builders::PutRecommendationPreferencesInputBuilder {
        &self.inner
    }
    /// Sends the request and returns the response.
    ///
    /// If an error occurs, an `SdkError` will be returned with additional details that
    /// can be matched against.
    ///
    /// By default, any retryable failures will be retried twice. Retry behavior
    /// is configurable with the [RetryConfig](aws_smithy_types::retry::RetryConfig), which can be
    /// set when configuring the client.
    pub async fn send(
        self,
    ) -> ::std::result::Result<
        crate::operation::put_recommendation_preferences::PutRecommendationPreferencesOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::put_recommendation_preferences::PutRecommendationPreferencesError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let input = self
            .inner
            .build()
            .map_err(::aws_smithy_runtime_api::client::result::SdkError::construction_failure)?;
        let runtime_plugins = crate::operation::put_recommendation_preferences::PutRecommendationPreferences::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::put_recommendation_preferences::PutRecommendationPreferences::orchestrate(&runtime_plugins, input).await
    }

    /// Consumes this builder, creating a customizable operation that can be modified before being sent.
    pub fn customize(
        self,
    ) -> crate::client::customize::CustomizableOperation<
        crate::operation::put_recommendation_preferences::PutRecommendationPreferencesOutput,
        crate::operation::put_recommendation_preferences::PutRecommendationPreferencesError,
        Self,
    > {
        crate::client::customize::CustomizableOperation::new(self)
    }
    pub(crate) fn config_override(mut self, config_override: impl ::std::convert::Into<crate::config::Builder>) -> Self {
        self.set_config_override(::std::option::Option::Some(config_override.into()));
        self
    }

    pub(crate) fn set_config_override(&mut self, config_override: ::std::option::Option<crate::config::Builder>) -> &mut Self {
        self.config_override = config_override;
        self
    }
    /// <p>The target resource type of the recommendation preference to create.</p>
    /// <p>The <code>Ec2Instance</code> option encompasses standalone instances and instances that are part of Amazon EC2 Auto Scaling groups. The <code>AutoScalingGroup</code> option encompasses only instances that are part of an Amazon EC2 Auto Scaling group.</p>
    pub fn resource_type(mut self, input: crate::types::ResourceType) -> Self {
        self.inner = self.inner.resource_type(input);
        self
    }
    /// <p>The target resource type of the recommendation preference to create.</p>
    /// <p>The <code>Ec2Instance</code> option encompasses standalone instances and instances that are part of Amazon EC2 Auto Scaling groups. The <code>AutoScalingGroup</code> option encompasses only instances that are part of an Amazon EC2 Auto Scaling group.</p>
    pub fn set_resource_type(mut self, input: ::std::option::Option<crate::types::ResourceType>) -> Self {
        self.inner = self.inner.set_resource_type(input);
        self
    }
    /// <p>The target resource type of the recommendation preference to create.</p>
    /// <p>The <code>Ec2Instance</code> option encompasses standalone instances and instances that are part of Amazon EC2 Auto Scaling groups. The <code>AutoScalingGroup</code> option encompasses only instances that are part of an Amazon EC2 Auto Scaling group.</p>
    pub fn get_resource_type(&self) -> &::std::option::Option<crate::types::ResourceType> {
        self.inner.get_resource_type()
    }
    /// <p>An object that describes the scope of the recommendation preference to create.</p>
    /// <p>You can create recommendation preferences at the organization level (for management accounts of an organization only), account level, and resource level. For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/enhanced-infrastructure-metrics.html">Activating enhanced infrastructure metrics</a> in the <i>Compute Optimizer User Guide</i>.</p><note>
    /// <p>You cannot create recommendation preferences for Amazon EC2 Auto Scaling groups at the organization and account levels. You can create recommendation preferences for Amazon EC2 Auto Scaling groups only at the resource level by specifying a scope name of <code>ResourceArn</code> and a scope value of the Amazon EC2 Auto Scaling group Amazon Resource Name (ARN). This will configure the preference for all instances that are part of the specified Amazon EC2 Auto Scaling group. You also cannot create recommendation preferences at the resource level for instances that are part of an Amazon EC2 Auto Scaling group. You can create recommendation preferences at the resource level only for standalone instances.</p>
    /// </note>
    pub fn scope(mut self, input: crate::types::Scope) -> Self {
        self.inner = self.inner.scope(input);
        self
    }
    /// <p>An object that describes the scope of the recommendation preference to create.</p>
    /// <p>You can create recommendation preferences at the organization level (for management accounts of an organization only), account level, and resource level. For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/enhanced-infrastructure-metrics.html">Activating enhanced infrastructure metrics</a> in the <i>Compute Optimizer User Guide</i>.</p><note>
    /// <p>You cannot create recommendation preferences for Amazon EC2 Auto Scaling groups at the organization and account levels. You can create recommendation preferences for Amazon EC2 Auto Scaling groups only at the resource level by specifying a scope name of <code>ResourceArn</code> and a scope value of the Amazon EC2 Auto Scaling group Amazon Resource Name (ARN). This will configure the preference for all instances that are part of the specified Amazon EC2 Auto Scaling group. You also cannot create recommendation preferences at the resource level for instances that are part of an Amazon EC2 Auto Scaling group. You can create recommendation preferences at the resource level only for standalone instances.</p>
    /// </note>
    pub fn set_scope(mut self, input: ::std::option::Option<crate::types::Scope>) -> Self {
        self.inner = self.inner.set_scope(input);
        self
    }
    /// <p>An object that describes the scope of the recommendation preference to create.</p>
    /// <p>You can create recommendation preferences at the organization level (for management accounts of an organization only), account level, and resource level. For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/enhanced-infrastructure-metrics.html">Activating enhanced infrastructure metrics</a> in the <i>Compute Optimizer User Guide</i>.</p><note>
    /// <p>You cannot create recommendation preferences for Amazon EC2 Auto Scaling groups at the organization and account levels. You can create recommendation preferences for Amazon EC2 Auto Scaling groups only at the resource level by specifying a scope name of <code>ResourceArn</code> and a scope value of the Amazon EC2 Auto Scaling group Amazon Resource Name (ARN). This will configure the preference for all instances that are part of the specified Amazon EC2 Auto Scaling group. You also cannot create recommendation preferences at the resource level for instances that are part of an Amazon EC2 Auto Scaling group. You can create recommendation preferences at the resource level only for standalone instances.</p>
    /// </note>
    pub fn get_scope(&self) -> &::std::option::Option<crate::types::Scope> {
        self.inner.get_scope()
    }
    /// <p>The status of the enhanced infrastructure metrics recommendation preference to create or update.</p>
    /// <p>Specify the <code>Active</code> status to activate the preference, or specify <code>Inactive</code> to deactivate the preference.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/enhanced-infrastructure-metrics.html">Enhanced infrastructure metrics</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn enhanced_infrastructure_metrics(mut self, input: crate::types::EnhancedInfrastructureMetrics) -> Self {
        self.inner = self.inner.enhanced_infrastructure_metrics(input);
        self
    }
    /// <p>The status of the enhanced infrastructure metrics recommendation preference to create or update.</p>
    /// <p>Specify the <code>Active</code> status to activate the preference, or specify <code>Inactive</code> to deactivate the preference.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/enhanced-infrastructure-metrics.html">Enhanced infrastructure metrics</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn set_enhanced_infrastructure_metrics(mut self, input: ::std::option::Option<crate::types::EnhancedInfrastructureMetrics>) -> Self {
        self.inner = self.inner.set_enhanced_infrastructure_metrics(input);
        self
    }
    /// <p>The status of the enhanced infrastructure metrics recommendation preference to create or update.</p>
    /// <p>Specify the <code>Active</code> status to activate the preference, or specify <code>Inactive</code> to deactivate the preference.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/enhanced-infrastructure-metrics.html">Enhanced infrastructure metrics</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn get_enhanced_infrastructure_metrics(&self) -> &::std::option::Option<crate::types::EnhancedInfrastructureMetrics> {
        self.inner.get_enhanced_infrastructure_metrics()
    }
    /// <p>The status of the inferred workload types recommendation preference to create or update.</p><note>
    /// <p>The inferred workload type feature is active by default. To deactivate it, create a recommendation preference.</p>
    /// </note>
    /// <p>Specify the <code>Inactive</code> status to deactivate the feature, or specify <code>Active</code> to activate it.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/inferred-workload-types.html">Inferred workload types</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn inferred_workload_types(mut self, input: crate::types::InferredWorkloadTypesPreference) -> Self {
        self.inner = self.inner.inferred_workload_types(input);
        self
    }
    /// <p>The status of the inferred workload types recommendation preference to create or update.</p><note>
    /// <p>The inferred workload type feature is active by default. To deactivate it, create a recommendation preference.</p>
    /// </note>
    /// <p>Specify the <code>Inactive</code> status to deactivate the feature, or specify <code>Active</code> to activate it.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/inferred-workload-types.html">Inferred workload types</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn set_inferred_workload_types(mut self, input: ::std::option::Option<crate::types::InferredWorkloadTypesPreference>) -> Self {
        self.inner = self.inner.set_inferred_workload_types(input);
        self
    }
    /// <p>The status of the inferred workload types recommendation preference to create or update.</p><note>
    /// <p>The inferred workload type feature is active by default. To deactivate it, create a recommendation preference.</p>
    /// </note>
    /// <p>Specify the <code>Inactive</code> status to deactivate the feature, or specify <code>Active</code> to activate it.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/inferred-workload-types.html">Inferred workload types</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn get_inferred_workload_types(&self) -> &::std::option::Option<crate::types::InferredWorkloadTypesPreference> {
        self.inner.get_inferred_workload_types()
    }
    /// <p>The provider of the external metrics recommendation preference to create or update.</p>
    /// <p>Specify a valid provider in the <code>source</code> field to activate the preference. To delete this preference, see the <code>DeleteRecommendationPreferences</code> action.</p>
    /// <p>This preference can only be set for the <code>Ec2Instance</code> resource type.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/external-metrics-ingestion.html">External metrics ingestion</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn external_metrics_preference(mut self, input: crate::types::ExternalMetricsPreference) -> Self {
        self.inner = self.inner.external_metrics_preference(input);
        self
    }
    /// <p>The provider of the external metrics recommendation preference to create or update.</p>
    /// <p>Specify a valid provider in the <code>source</code> field to activate the preference. To delete this preference, see the <code>DeleteRecommendationPreferences</code> action.</p>
    /// <p>This preference can only be set for the <code>Ec2Instance</code> resource type.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/external-metrics-ingestion.html">External metrics ingestion</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn set_external_metrics_preference(mut self, input: ::std::option::Option<crate::types::ExternalMetricsPreference>) -> Self {
        self.inner = self.inner.set_external_metrics_preference(input);
        self
    }
    /// <p>The provider of the external metrics recommendation preference to create or update.</p>
    /// <p>Specify a valid provider in the <code>source</code> field to activate the preference. To delete this preference, see the <code>DeleteRecommendationPreferences</code> action.</p>
    /// <p>This preference can only be set for the <code>Ec2Instance</code> resource type.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/external-metrics-ingestion.html">External metrics ingestion</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn get_external_metrics_preference(&self) -> &::std::option::Option<crate::types::ExternalMetricsPreference> {
        self.inner.get_external_metrics_preference()
    }
    /// <p>The preference to control the number of days the utilization metrics of the Amazon Web Services resource are analyzed. When this preference isn't specified, we use the default value <code>DAYS_14</code>.</p>
    /// <p>You can only set this preference for the Amazon EC2 instance and Amazon EC2 Auto Scaling group resource types.</p><note>
    /// <ul>
    /// <li>
    /// <p>Amazon EC2 instance lookback preferences can be set at the organization, account, and resource levels.</p></li>
    /// <li>
    /// <p>Amazon EC2 Auto Scaling group lookback preferences can only be set at the resource level.</p></li>
    /// </ul>
    /// </note>
    pub fn look_back_period(mut self, input: crate::types::LookBackPeriodPreference) -> Self {
        self.inner = self.inner.look_back_period(input);
        self
    }
    /// <p>The preference to control the number of days the utilization metrics of the Amazon Web Services resource are analyzed. When this preference isn't specified, we use the default value <code>DAYS_14</code>.</p>
    /// <p>You can only set this preference for the Amazon EC2 instance and Amazon EC2 Auto Scaling group resource types.</p><note>
    /// <ul>
    /// <li>
    /// <p>Amazon EC2 instance lookback preferences can be set at the organization, account, and resource levels.</p></li>
    /// <li>
    /// <p>Amazon EC2 Auto Scaling group lookback preferences can only be set at the resource level.</p></li>
    /// </ul>
    /// </note>
    pub fn set_look_back_period(mut self, input: ::std::option::Option<crate::types::LookBackPeriodPreference>) -> Self {
        self.inner = self.inner.set_look_back_period(input);
        self
    }
    /// <p>The preference to control the number of days the utilization metrics of the Amazon Web Services resource are analyzed. When this preference isn't specified, we use the default value <code>DAYS_14</code>.</p>
    /// <p>You can only set this preference for the Amazon EC2 instance and Amazon EC2 Auto Scaling group resource types.</p><note>
    /// <ul>
    /// <li>
    /// <p>Amazon EC2 instance lookback preferences can be set at the organization, account, and resource levels.</p></li>
    /// <li>
    /// <p>Amazon EC2 Auto Scaling group lookback preferences can only be set at the resource level.</p></li>
    /// </ul>
    /// </note>
    pub fn get_look_back_period(&self) -> &::std::option::Option<crate::types::LookBackPeriodPreference> {
        self.inner.get_look_back_period()
    }
    ///
    /// Appends an item to `utilizationPreferences`.
    ///
    /// To override the contents of this collection use [`set_utilization_preferences`](Self::set_utilization_preferences).
    ///
    /// <p>The preference to control the resource’s CPU utilization threshold, CPU utilization headroom, and memory utilization headroom. When this preference isn't specified, we use the following default values.</p>
    /// <p>CPU utilization:</p>
    /// <ul>
    /// <li>
    /// <p><code>P99_5</code> for threshold</p></li>
    /// <li>
    /// <p><code>PERCENT_20</code> for headroom</p></li>
    /// </ul>
    /// <p>Memory utilization:</p>
    /// <ul>
    /// <li>
    /// <p><code>PERCENT_20</code> for headroom</p></li>
    /// </ul><note>
    /// <ul>
    /// <li>
    /// <p>You can only set CPU and memory utilization preferences for the Amazon EC2 instance resource type.</p></li>
    /// <li>
    /// <p>The threshold setting isn’t available for memory utilization.</p></li>
    /// </ul>
    /// </note>
    pub fn utilization_preferences(mut self, input: crate::types::UtilizationPreference) -> Self {
        self.inner = self.inner.utilization_preferences(input);
        self
    }
    /// <p>The preference to control the resource’s CPU utilization threshold, CPU utilization headroom, and memory utilization headroom. When this preference isn't specified, we use the following default values.</p>
    /// <p>CPU utilization:</p>
    /// <ul>
    /// <li>
    /// <p><code>P99_5</code> for threshold</p></li>
    /// <li>
    /// <p><code>PERCENT_20</code> for headroom</p></li>
    /// </ul>
    /// <p>Memory utilization:</p>
    /// <ul>
    /// <li>
    /// <p><code>PERCENT_20</code> for headroom</p></li>
    /// </ul><note>
    /// <ul>
    /// <li>
    /// <p>You can only set CPU and memory utilization preferences for the Amazon EC2 instance resource type.</p></li>
    /// <li>
    /// <p>The threshold setting isn’t available for memory utilization.</p></li>
    /// </ul>
    /// </note>
    pub fn set_utilization_preferences(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::UtilizationPreference>>) -> Self {
        self.inner = self.inner.set_utilization_preferences(input);
        self
    }
    /// <p>The preference to control the resource’s CPU utilization threshold, CPU utilization headroom, and memory utilization headroom. When this preference isn't specified, we use the following default values.</p>
    /// <p>CPU utilization:</p>
    /// <ul>
    /// <li>
    /// <p><code>P99_5</code> for threshold</p></li>
    /// <li>
    /// <p><code>PERCENT_20</code> for headroom</p></li>
    /// </ul>
    /// <p>Memory utilization:</p>
    /// <ul>
    /// <li>
    /// <p><code>PERCENT_20</code> for headroom</p></li>
    /// </ul><note>
    /// <ul>
    /// <li>
    /// <p>You can only set CPU and memory utilization preferences for the Amazon EC2 instance resource type.</p></li>
    /// <li>
    /// <p>The threshold setting isn’t available for memory utilization.</p></li>
    /// </ul>
    /// </note>
    pub fn get_utilization_preferences(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::UtilizationPreference>> {
        self.inner.get_utilization_preferences()
    }
    ///
    /// Appends an item to `preferredResources`.
    ///
    /// To override the contents of this collection use [`set_preferred_resources`](Self::set_preferred_resources).
    ///
    /// <p>The preference to control which resource type values are considered when generating rightsizing recommendations. You can specify this preference as a combination of include and exclude lists. You must specify either an <code>includeList</code> or <code>excludeList</code>. If the preference is an empty set of resource type values, an error occurs.</p><note>
    /// <p>You can only set this preference for the Amazon EC2 instance and Amazon EC2 Auto Scaling group resource types.</p>
    /// </note>
    pub fn preferred_resources(mut self, input: crate::types::PreferredResource) -> Self {
        self.inner = self.inner.preferred_resources(input);
        self
    }
    /// <p>The preference to control which resource type values are considered when generating rightsizing recommendations. You can specify this preference as a combination of include and exclude lists. You must specify either an <code>includeList</code> or <code>excludeList</code>. If the preference is an empty set of resource type values, an error occurs.</p><note>
    /// <p>You can only set this preference for the Amazon EC2 instance and Amazon EC2 Auto Scaling group resource types.</p>
    /// </note>
    pub fn set_preferred_resources(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::PreferredResource>>) -> Self {
        self.inner = self.inner.set_preferred_resources(input);
        self
    }
    /// <p>The preference to control which resource type values are considered when generating rightsizing recommendations. You can specify this preference as a combination of include and exclude lists. You must specify either an <code>includeList</code> or <code>excludeList</code>. If the preference is an empty set of resource type values, an error occurs.</p><note>
    /// <p>You can only set this preference for the Amazon EC2 instance and Amazon EC2 Auto Scaling group resource types.</p>
    /// </note>
    pub fn get_preferred_resources(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::PreferredResource>> {
        self.inner.get_preferred_resources()
    }
    /// <p>The status of the savings estimation mode preference to create or update.</p>
    /// <p>Specify the <code>AfterDiscounts</code> status to activate the preference, or specify <code>BeforeDiscounts</code> to deactivate the preference.</p>
    /// <p>Only the account manager or delegated administrator of your organization can activate this preference.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/savings-estimation-mode.html"> Savings estimation mode</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn savings_estimation_mode(mut self, input: crate::types::SavingsEstimationMode) -> Self {
        self.inner = self.inner.savings_estimation_mode(input);
        self
    }
    /// <p>The status of the savings estimation mode preference to create or update.</p>
    /// <p>Specify the <code>AfterDiscounts</code> status to activate the preference, or specify <code>BeforeDiscounts</code> to deactivate the preference.</p>
    /// <p>Only the account manager or delegated administrator of your organization can activate this preference.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/savings-estimation-mode.html"> Savings estimation mode</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn set_savings_estimation_mode(mut self, input: ::std::option::Option<crate::types::SavingsEstimationMode>) -> Self {
        self.inner = self.inner.set_savings_estimation_mode(input);
        self
    }
    /// <p>The status of the savings estimation mode preference to create or update.</p>
    /// <p>Specify the <code>AfterDiscounts</code> status to activate the preference, or specify <code>BeforeDiscounts</code> to deactivate the preference.</p>
    /// <p>Only the account manager or delegated administrator of your organization can activate this preference.</p>
    /// <p>For more information, see <a href="https://docs.aws.amazon.com/compute-optimizer/latest/ug/savings-estimation-mode.html"> Savings estimation mode</a> in the <i>Compute Optimizer User Guide</i>.</p>
    pub fn get_savings_estimation_mode(&self) -> &::std::option::Option<crate::types::SavingsEstimationMode> {
        self.inner.get_savings_estimation_mode()
    }
}