AWS SDK for C++  1.9.156
AWS SDK for C++
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Aws::ComputeOptimizer::Model::InstanceRecommendation Class Reference

#include <InstanceRecommendation.h>

Public Member Functions

 InstanceRecommendation ()
 
 InstanceRecommendation (Aws::Utils::Json::JsonView jsonValue)
 
InstanceRecommendationoperator= (Aws::Utils::Json::JsonView jsonValue)
 
Aws::Utils::Json::JsonValue Jsonize () const
 
const Aws::StringGetInstanceArn () const
 
bool InstanceArnHasBeenSet () const
 
void SetInstanceArn (const Aws::String &value)
 
void SetInstanceArn (Aws::String &&value)
 
void SetInstanceArn (const char *value)
 
InstanceRecommendationWithInstanceArn (const Aws::String &value)
 
InstanceRecommendationWithInstanceArn (Aws::String &&value)
 
InstanceRecommendationWithInstanceArn (const char *value)
 
const Aws::StringGetAccountId () const
 
bool AccountIdHasBeenSet () const
 
void SetAccountId (const Aws::String &value)
 
void SetAccountId (Aws::String &&value)
 
void SetAccountId (const char *value)
 
InstanceRecommendationWithAccountId (const Aws::String &value)
 
InstanceRecommendationWithAccountId (Aws::String &&value)
 
InstanceRecommendationWithAccountId (const char *value)
 
const Aws::StringGetInstanceName () const
 
bool InstanceNameHasBeenSet () const
 
void SetInstanceName (const Aws::String &value)
 
void SetInstanceName (Aws::String &&value)
 
void SetInstanceName (const char *value)
 
InstanceRecommendationWithInstanceName (const Aws::String &value)
 
InstanceRecommendationWithInstanceName (Aws::String &&value)
 
InstanceRecommendationWithInstanceName (const char *value)
 
const Aws::StringGetCurrentInstanceType () const
 
bool CurrentInstanceTypeHasBeenSet () const
 
void SetCurrentInstanceType (const Aws::String &value)
 
void SetCurrentInstanceType (Aws::String &&value)
 
void SetCurrentInstanceType (const char *value)
 
InstanceRecommendationWithCurrentInstanceType (const Aws::String &value)
 
InstanceRecommendationWithCurrentInstanceType (Aws::String &&value)
 
InstanceRecommendationWithCurrentInstanceType (const char *value)
 
const FindingGetFinding () const
 
bool FindingHasBeenSet () const
 
void SetFinding (const Finding &value)
 
void SetFinding (Finding &&value)
 
InstanceRecommendationWithFinding (const Finding &value)
 
InstanceRecommendationWithFinding (Finding &&value)
 
const Aws::Vector< InstanceRecommendationFindingReasonCode > & GetFindingReasonCodes () const
 
bool FindingReasonCodesHasBeenSet () const
 
void SetFindingReasonCodes (const Aws::Vector< InstanceRecommendationFindingReasonCode > &value)
 
void SetFindingReasonCodes (Aws::Vector< InstanceRecommendationFindingReasonCode > &&value)
 
InstanceRecommendationWithFindingReasonCodes (const Aws::Vector< InstanceRecommendationFindingReasonCode > &value)
 
InstanceRecommendationWithFindingReasonCodes (Aws::Vector< InstanceRecommendationFindingReasonCode > &&value)
 
InstanceRecommendationAddFindingReasonCodes (const InstanceRecommendationFindingReasonCode &value)
 
InstanceRecommendationAddFindingReasonCodes (InstanceRecommendationFindingReasonCode &&value)
 
const Aws::Vector< UtilizationMetric > & GetUtilizationMetrics () const
 
bool UtilizationMetricsHasBeenSet () const
 
void SetUtilizationMetrics (const Aws::Vector< UtilizationMetric > &value)
 
void SetUtilizationMetrics (Aws::Vector< UtilizationMetric > &&value)
 
InstanceRecommendationWithUtilizationMetrics (const Aws::Vector< UtilizationMetric > &value)
 
InstanceRecommendationWithUtilizationMetrics (Aws::Vector< UtilizationMetric > &&value)
 
InstanceRecommendationAddUtilizationMetrics (const UtilizationMetric &value)
 
InstanceRecommendationAddUtilizationMetrics (UtilizationMetric &&value)
 
double GetLookBackPeriodInDays () const
 
bool LookBackPeriodInDaysHasBeenSet () const
 
void SetLookBackPeriodInDays (double value)
 
InstanceRecommendationWithLookBackPeriodInDays (double value)
 
const Aws::Vector< InstanceRecommendationOption > & GetRecommendationOptions () const
 
bool RecommendationOptionsHasBeenSet () const
 
void SetRecommendationOptions (const Aws::Vector< InstanceRecommendationOption > &value)
 
void SetRecommendationOptions (Aws::Vector< InstanceRecommendationOption > &&value)
 
InstanceRecommendationWithRecommendationOptions (const Aws::Vector< InstanceRecommendationOption > &value)
 
InstanceRecommendationWithRecommendationOptions (Aws::Vector< InstanceRecommendationOption > &&value)
 
InstanceRecommendationAddRecommendationOptions (const InstanceRecommendationOption &value)
 
InstanceRecommendationAddRecommendationOptions (InstanceRecommendationOption &&value)
 
const Aws::Vector< RecommendationSource > & GetRecommendationSources () const
 
bool RecommendationSourcesHasBeenSet () const
 
void SetRecommendationSources (const Aws::Vector< RecommendationSource > &value)
 
void SetRecommendationSources (Aws::Vector< RecommendationSource > &&value)
 
InstanceRecommendationWithRecommendationSources (const Aws::Vector< RecommendationSource > &value)
 
InstanceRecommendationWithRecommendationSources (Aws::Vector< RecommendationSource > &&value)
 
InstanceRecommendationAddRecommendationSources (const RecommendationSource &value)
 
InstanceRecommendationAddRecommendationSources (RecommendationSource &&value)
 
const Aws::Utils::DateTimeGetLastRefreshTimestamp () const
 
bool LastRefreshTimestampHasBeenSet () const
 
void SetLastRefreshTimestamp (const Aws::Utils::DateTime &value)
 
void SetLastRefreshTimestamp (Aws::Utils::DateTime &&value)
 
InstanceRecommendationWithLastRefreshTimestamp (const Aws::Utils::DateTime &value)
 
InstanceRecommendationWithLastRefreshTimestamp (Aws::Utils::DateTime &&value)
 
const CurrentPerformanceRiskGetCurrentPerformanceRisk () const
 
bool CurrentPerformanceRiskHasBeenSet () const
 
void SetCurrentPerformanceRisk (const CurrentPerformanceRisk &value)
 
void SetCurrentPerformanceRisk (CurrentPerformanceRisk &&value)
 
InstanceRecommendationWithCurrentPerformanceRisk (const CurrentPerformanceRisk &value)
 
InstanceRecommendationWithCurrentPerformanceRisk (CurrentPerformanceRisk &&value)
 
const EffectiveRecommendationPreferencesGetEffectiveRecommendationPreferences () const
 
bool EffectiveRecommendationPreferencesHasBeenSet () const
 
void SetEffectiveRecommendationPreferences (const EffectiveRecommendationPreferences &value)
 
void SetEffectiveRecommendationPreferences (EffectiveRecommendationPreferences &&value)
 
InstanceRecommendationWithEffectiveRecommendationPreferences (const EffectiveRecommendationPreferences &value)
 
InstanceRecommendationWithEffectiveRecommendationPreferences (EffectiveRecommendationPreferences &&value)
 

Detailed Description

Describes an Amazon EC2 instance recommendation.

See Also:


AWS API Reference

Definition at line 41 of file InstanceRecommendation.h.

Constructor & Destructor Documentation

◆ InstanceRecommendation() [1/2]

Aws::ComputeOptimizer::Model::InstanceRecommendation::InstanceRecommendation ( )

◆ InstanceRecommendation() [2/2]

Aws::ComputeOptimizer::Model::InstanceRecommendation::InstanceRecommendation ( Aws::Utils::Json::JsonView  jsonValue)

Member Function Documentation

◆ AccountIdHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::AccountIdHasBeenSet ( ) const
inline

The Amazon Web Services account ID of the instance.

Definition at line 99 of file InstanceRecommendation.h.

◆ AddFindingReasonCodes() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::AddFindingReasonCodes ( const InstanceRecommendationFindingReasonCode value)
inline

The reason for the finding classification of the instance.

Finding reason codes for instances include:

  • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

  • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

    Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the mem_used_percent metric in the CWAgent namespace, or the legacy MemoryUtilization metric in the System/Linux namespace. On Windows instances, Compute Optimizer analyses the Memory % Committed Bytes In Use metric in the CWAgent namespace.

  • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period.

  • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.

  • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

  • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.

Definition at line 1076 of file InstanceRecommendation.h.

◆ AddFindingReasonCodes() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::AddFindingReasonCodes ( InstanceRecommendationFindingReasonCode &&  value)
inline

The reason for the finding classification of the instance.

Finding reason codes for instances include:

  • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

  • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

    Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the mem_used_percent metric in the CWAgent namespace, or the legacy MemoryUtilization metric in the System/Linux namespace. On Windows instances, Compute Optimizer analyses the Memory % Committed Bytes In Use metric in the CWAgent namespace.

  • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period.

  • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.

  • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

  • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.

Definition at line 1183 of file InstanceRecommendation.h.

◆ AddRecommendationOptions() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::AddRecommendationOptions ( const InstanceRecommendationOption value)
inline

An array of objects that describe the recommendation options for the instance.

Definition at line 1300 of file InstanceRecommendation.h.

◆ AddRecommendationOptions() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::AddRecommendationOptions ( InstanceRecommendationOption &&  value)
inline

An array of objects that describe the recommendation options for the instance.

Definition at line 1306 of file InstanceRecommendation.h.

◆ AddRecommendationSources() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::AddRecommendationSources ( const RecommendationSource value)
inline

An array of objects that describe the source resource of the recommendation.

Definition at line 1349 of file InstanceRecommendation.h.

◆ AddRecommendationSources() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::AddRecommendationSources ( RecommendationSource &&  value)
inline

An array of objects that describe the source resource of the recommendation.

Definition at line 1355 of file InstanceRecommendation.h.

◆ AddUtilizationMetrics() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::AddUtilizationMetrics ( const UtilizationMetric value)
inline

An array of objects that describe the utilization metrics of the instance.

Definition at line 1226 of file InstanceRecommendation.h.

◆ AddUtilizationMetrics() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::AddUtilizationMetrics ( UtilizationMetric &&  value)
inline

An array of objects that describe the utilization metrics of the instance.

Definition at line 1232 of file InstanceRecommendation.h.

◆ CurrentInstanceTypeHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::CurrentInstanceTypeHasBeenSet ( ) const
inline

The instance type of the current instance.

Definition at line 181 of file InstanceRecommendation.h.

◆ CurrentPerformanceRiskHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::CurrentPerformanceRiskHasBeenSet ( ) const
inline

The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current Lambda function requires more memory.

Definition at line 1401 of file InstanceRecommendation.h.

◆ EffectiveRecommendationPreferencesHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::EffectiveRecommendationPreferencesHasBeenSet ( ) const
inline

An object that describes the effective recommendation preferences for the instance.

Definition at line 1442 of file InstanceRecommendation.h.

◆ FindingHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::FindingHasBeenSet ( ) const
inline

The finding classification of the instance.

Findings for instances include:

  • Underprovisioned —An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance.

  • Overprovisioned —An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost.

  • Optimized —An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.

Definition at line 250 of file InstanceRecommendation.h.

◆ FindingReasonCodesHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::FindingReasonCodesHasBeenSet ( ) const
inline

The reason for the finding classification of the instance.

Finding reason codes for instances include:

  • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

  • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

    Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the mem_used_percent metric in the CWAgent namespace, or the legacy MemoryUtilization metric in the System/Linux namespace. On Windows instances, Compute Optimizer analyses the Memory % Committed Bytes In Use metric in the CWAgent namespace.

  • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period.

  • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.

  • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

  • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.

Definition at line 541 of file InstanceRecommendation.h.

◆ GetAccountId()

const Aws::String& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetAccountId ( ) const
inline

The Amazon Web Services account ID of the instance.

Definition at line 94 of file InstanceRecommendation.h.

◆ GetCurrentInstanceType()

const Aws::String& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetCurrentInstanceType ( ) const
inline

The instance type of the current instance.

Definition at line 176 of file InstanceRecommendation.h.

◆ GetCurrentPerformanceRisk()

const CurrentPerformanceRisk& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetCurrentPerformanceRisk ( ) const
inline

The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current Lambda function requires more memory.

Definition at line 1394 of file InstanceRecommendation.h.

◆ GetEffectiveRecommendationPreferences()

const EffectiveRecommendationPreferences& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetEffectiveRecommendationPreferences ( ) const
inline

An object that describes the effective recommendation preferences for the instance.

Definition at line 1436 of file InstanceRecommendation.h.

◆ GetFinding()

const Finding& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetFinding ( ) const
inline

The finding classification of the instance.

Findings for instances include:

  • Underprovisioned —An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance.

  • Overprovisioned —An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost.

  • Optimized —An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.

Definition at line 231 of file InstanceRecommendation.h.

◆ GetFindingReasonCodes()

const Aws::Vector<InstanceRecommendationFindingReasonCode>& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetFindingReasonCodes ( ) const
inline

The reason for the finding classification of the instance.

Finding reason codes for instances include:

  • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

  • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

    Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the mem_used_percent metric in the CWAgent namespace, or the legacy MemoryUtilization metric in the System/Linux namespace. On Windows instances, Compute Optimizer analyses the Memory % Committed Bytes In Use metric in the CWAgent namespace.

  • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period.

  • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.

  • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

  • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.

Definition at line 434 of file InstanceRecommendation.h.

◆ GetInstanceArn()

const Aws::String& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetInstanceArn ( ) const
inline

The Amazon Resource Name (ARN) of the current instance.

Definition at line 53 of file InstanceRecommendation.h.

◆ GetInstanceName()

const Aws::String& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetInstanceName ( ) const
inline

The name of the current instance.

Definition at line 135 of file InstanceRecommendation.h.

◆ GetLastRefreshTimestamp()

const Aws::Utils::DateTime& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetLastRefreshTimestamp ( ) const
inline

The timestamp of when the instance recommendation was last generated.

Definition at line 1361 of file InstanceRecommendation.h.

◆ GetLookBackPeriodInDays()

double Aws::ComputeOptimizer::Model::InstanceRecommendation::GetLookBackPeriodInDays ( ) const
inline

The number of days for which utilization metrics were analyzed for the instance.

Definition at line 1239 of file InstanceRecommendation.h.

◆ GetRecommendationOptions()

const Aws::Vector<InstanceRecommendationOption>& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetRecommendationOptions ( ) const
inline

An array of objects that describe the recommendation options for the instance.

Definition at line 1264 of file InstanceRecommendation.h.

◆ GetRecommendationSources()

const Aws::Vector<RecommendationSource>& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetRecommendationSources ( ) const
inline

An array of objects that describe the source resource of the recommendation.

Definition at line 1313 of file InstanceRecommendation.h.

◆ GetUtilizationMetrics()

const Aws::Vector<UtilizationMetric>& Aws::ComputeOptimizer::Model::InstanceRecommendation::GetUtilizationMetrics ( ) const
inline

An array of objects that describe the utilization metrics of the instance.

Definition at line 1190 of file InstanceRecommendation.h.

◆ InstanceArnHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::InstanceArnHasBeenSet ( ) const
inline

The Amazon Resource Name (ARN) of the current instance.

Definition at line 58 of file InstanceRecommendation.h.

◆ InstanceNameHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::InstanceNameHasBeenSet ( ) const
inline

The name of the current instance.

Definition at line 140 of file InstanceRecommendation.h.

◆ Jsonize()

Aws::Utils::Json::JsonValue Aws::ComputeOptimizer::Model::InstanceRecommendation::Jsonize ( ) const

◆ LastRefreshTimestampHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::LastRefreshTimestampHasBeenSet ( ) const
inline

The timestamp of when the instance recommendation was last generated.

Definition at line 1366 of file InstanceRecommendation.h.

◆ LookBackPeriodInDaysHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::LookBackPeriodInDaysHasBeenSet ( ) const
inline

The number of days for which utilization metrics were analyzed for the instance.

Definition at line 1245 of file InstanceRecommendation.h.

◆ operator=()

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::operator= ( Aws::Utils::Json::JsonView  jsonValue)

◆ RecommendationOptionsHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::RecommendationOptionsHasBeenSet ( ) const
inline

An array of objects that describe the recommendation options for the instance.

Definition at line 1270 of file InstanceRecommendation.h.

◆ RecommendationSourcesHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::RecommendationSourcesHasBeenSet ( ) const
inline

An array of objects that describe the source resource of the recommendation.

Definition at line 1319 of file InstanceRecommendation.h.

◆ SetAccountId() [1/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetAccountId ( Aws::String &&  value)
inline

The Amazon Web Services account ID of the instance.

Definition at line 109 of file InstanceRecommendation.h.

◆ SetAccountId() [2/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetAccountId ( const Aws::String value)
inline

The Amazon Web Services account ID of the instance.

Definition at line 104 of file InstanceRecommendation.h.

◆ SetAccountId() [3/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetAccountId ( const char *  value)
inline

The Amazon Web Services account ID of the instance.

Definition at line 114 of file InstanceRecommendation.h.

◆ SetCurrentInstanceType() [1/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetCurrentInstanceType ( Aws::String &&  value)
inline

The instance type of the current instance.

Definition at line 191 of file InstanceRecommendation.h.

◆ SetCurrentInstanceType() [2/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetCurrentInstanceType ( const Aws::String value)
inline

The instance type of the current instance.

Definition at line 186 of file InstanceRecommendation.h.

◆ SetCurrentInstanceType() [3/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetCurrentInstanceType ( const char *  value)
inline

The instance type of the current instance.

Definition at line 196 of file InstanceRecommendation.h.

◆ SetCurrentPerformanceRisk() [1/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetCurrentPerformanceRisk ( const CurrentPerformanceRisk value)
inline

The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current Lambda function requires more memory.

Definition at line 1408 of file InstanceRecommendation.h.

◆ SetCurrentPerformanceRisk() [2/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetCurrentPerformanceRisk ( CurrentPerformanceRisk &&  value)
inline

The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current Lambda function requires more memory.

Definition at line 1415 of file InstanceRecommendation.h.

◆ SetEffectiveRecommendationPreferences() [1/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetEffectiveRecommendationPreferences ( const EffectiveRecommendationPreferences value)
inline

An object that describes the effective recommendation preferences for the instance.

Definition at line 1448 of file InstanceRecommendation.h.

◆ SetEffectiveRecommendationPreferences() [2/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetEffectiveRecommendationPreferences ( EffectiveRecommendationPreferences &&  value)
inline

An object that describes the effective recommendation preferences for the instance.

Definition at line 1454 of file InstanceRecommendation.h.

◆ SetFinding() [1/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetFinding ( const Finding value)
inline

The finding classification of the instance.

Findings for instances include:

  • Underprovisioned —An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance.

  • Overprovisioned —An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost.

  • Optimized —An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.

Definition at line 269 of file InstanceRecommendation.h.

◆ SetFinding() [2/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetFinding ( Finding &&  value)
inline

The finding classification of the instance.

Findings for instances include:

  • Underprovisioned —An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance.

  • Overprovisioned —An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost.

  • Optimized —An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.

Definition at line 288 of file InstanceRecommendation.h.

◆ SetFindingReasonCodes() [1/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetFindingReasonCodes ( Aws::Vector< InstanceRecommendationFindingReasonCode > &&  value)
inline

The reason for the finding classification of the instance.

Finding reason codes for instances include:

  • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

  • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

    Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the mem_used_percent metric in the CWAgent namespace, or the legacy MemoryUtilization metric in the System/Linux namespace. On Windows instances, Compute Optimizer analyses the Memory % Committed Bytes In Use metric in the CWAgent namespace.

  • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period.

  • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.

  • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

  • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.

Definition at line 755 of file InstanceRecommendation.h.

◆ SetFindingReasonCodes() [2/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetFindingReasonCodes ( const Aws::Vector< InstanceRecommendationFindingReasonCode > &  value)
inline

The reason for the finding classification of the instance.

Finding reason codes for instances include:

  • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

  • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

    Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the mem_used_percent metric in the CWAgent namespace, or the legacy MemoryUtilization metric in the System/Linux namespace. On Windows instances, Compute Optimizer analyses the Memory % Committed Bytes In Use metric in the CWAgent namespace.

  • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period.

  • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.

  • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

  • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.

Definition at line 648 of file InstanceRecommendation.h.

◆ SetInstanceArn() [1/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetInstanceArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the current instance.

Definition at line 68 of file InstanceRecommendation.h.

◆ SetInstanceArn() [2/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetInstanceArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the current instance.

Definition at line 63 of file InstanceRecommendation.h.

◆ SetInstanceArn() [3/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetInstanceArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the current instance.

Definition at line 73 of file InstanceRecommendation.h.

◆ SetInstanceName() [1/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetInstanceName ( Aws::String &&  value)
inline

The name of the current instance.

Definition at line 150 of file InstanceRecommendation.h.

◆ SetInstanceName() [2/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetInstanceName ( const Aws::String value)
inline

The name of the current instance.

Definition at line 145 of file InstanceRecommendation.h.

◆ SetInstanceName() [3/3]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetInstanceName ( const char *  value)
inline

The name of the current instance.

Definition at line 155 of file InstanceRecommendation.h.

◆ SetLastRefreshTimestamp() [1/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetLastRefreshTimestamp ( Aws::Utils::DateTime &&  value)
inline

The timestamp of when the instance recommendation was last generated.

Definition at line 1376 of file InstanceRecommendation.h.

◆ SetLastRefreshTimestamp() [2/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetLastRefreshTimestamp ( const Aws::Utils::DateTime value)
inline

The timestamp of when the instance recommendation was last generated.

Definition at line 1371 of file InstanceRecommendation.h.

◆ SetLookBackPeriodInDays()

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetLookBackPeriodInDays ( double  value)
inline

The number of days for which utilization metrics were analyzed for the instance.

Definition at line 1251 of file InstanceRecommendation.h.

◆ SetRecommendationOptions() [1/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetRecommendationOptions ( Aws::Vector< InstanceRecommendationOption > &&  value)
inline

An array of objects that describe the recommendation options for the instance.

Definition at line 1282 of file InstanceRecommendation.h.

◆ SetRecommendationOptions() [2/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetRecommendationOptions ( const Aws::Vector< InstanceRecommendationOption > &  value)
inline

An array of objects that describe the recommendation options for the instance.

Definition at line 1276 of file InstanceRecommendation.h.

◆ SetRecommendationSources() [1/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetRecommendationSources ( Aws::Vector< RecommendationSource > &&  value)
inline

An array of objects that describe the source resource of the recommendation.

Definition at line 1331 of file InstanceRecommendation.h.

◆ SetRecommendationSources() [2/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetRecommendationSources ( const Aws::Vector< RecommendationSource > &  value)
inline

An array of objects that describe the source resource of the recommendation.

Definition at line 1325 of file InstanceRecommendation.h.

◆ SetUtilizationMetrics() [1/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetUtilizationMetrics ( Aws::Vector< UtilizationMetric > &&  value)
inline

An array of objects that describe the utilization metrics of the instance.

Definition at line 1208 of file InstanceRecommendation.h.

◆ SetUtilizationMetrics() [2/2]

void Aws::ComputeOptimizer::Model::InstanceRecommendation::SetUtilizationMetrics ( const Aws::Vector< UtilizationMetric > &  value)
inline

An array of objects that describe the utilization metrics of the instance.

Definition at line 1202 of file InstanceRecommendation.h.

◆ UtilizationMetricsHasBeenSet()

bool Aws::ComputeOptimizer::Model::InstanceRecommendation::UtilizationMetricsHasBeenSet ( ) const
inline

An array of objects that describe the utilization metrics of the instance.

Definition at line 1196 of file InstanceRecommendation.h.

◆ WithAccountId() [1/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithAccountId ( Aws::String &&  value)
inline

The Amazon Web Services account ID of the instance.

Definition at line 124 of file InstanceRecommendation.h.

◆ WithAccountId() [2/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithAccountId ( const Aws::String value)
inline

The Amazon Web Services account ID of the instance.

Definition at line 119 of file InstanceRecommendation.h.

◆ WithAccountId() [3/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithAccountId ( const char *  value)
inline

The Amazon Web Services account ID of the instance.

Definition at line 129 of file InstanceRecommendation.h.

◆ WithCurrentInstanceType() [1/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithCurrentInstanceType ( Aws::String &&  value)
inline

The instance type of the current instance.

Definition at line 206 of file InstanceRecommendation.h.

◆ WithCurrentInstanceType() [2/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithCurrentInstanceType ( const Aws::String value)
inline

The instance type of the current instance.

Definition at line 201 of file InstanceRecommendation.h.

◆ WithCurrentInstanceType() [3/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithCurrentInstanceType ( const char *  value)
inline

The instance type of the current instance.

Definition at line 211 of file InstanceRecommendation.h.

◆ WithCurrentPerformanceRisk() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithCurrentPerformanceRisk ( const CurrentPerformanceRisk value)
inline

The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current Lambda function requires more memory.

Definition at line 1422 of file InstanceRecommendation.h.

◆ WithCurrentPerformanceRisk() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithCurrentPerformanceRisk ( CurrentPerformanceRisk &&  value)
inline

The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current Lambda function requires more memory.

Definition at line 1429 of file InstanceRecommendation.h.

◆ WithEffectiveRecommendationPreferences() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithEffectiveRecommendationPreferences ( const EffectiveRecommendationPreferences value)
inline

An object that describes the effective recommendation preferences for the instance.

Definition at line 1460 of file InstanceRecommendation.h.

◆ WithEffectiveRecommendationPreferences() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithEffectiveRecommendationPreferences ( EffectiveRecommendationPreferences &&  value)
inline

An object that describes the effective recommendation preferences for the instance.

Definition at line 1466 of file InstanceRecommendation.h.

◆ WithFinding() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithFinding ( const Finding value)
inline

The finding classification of the instance.

Findings for instances include:

  • Underprovisioned —An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance.

  • Overprovisioned —An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost.

  • Optimized —An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.

Definition at line 307 of file InstanceRecommendation.h.

◆ WithFinding() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithFinding ( Finding &&  value)
inline

The finding classification of the instance.

Findings for instances include:

  • Underprovisioned —An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance.

  • Overprovisioned —An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost.

  • Optimized —An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.

Definition at line 326 of file InstanceRecommendation.h.

◆ WithFindingReasonCodes() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithFindingReasonCodes ( Aws::Vector< InstanceRecommendationFindingReasonCode > &&  value)
inline

The reason for the finding classification of the instance.

Finding reason codes for instances include:

  • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

  • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

    Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the mem_used_percent metric in the CWAgent namespace, or the legacy MemoryUtilization metric in the System/Linux namespace. On Windows instances, Compute Optimizer analyses the Memory % Committed Bytes In Use metric in the CWAgent namespace.

  • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period.

  • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.

  • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

  • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.

Definition at line 969 of file InstanceRecommendation.h.

◆ WithFindingReasonCodes() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithFindingReasonCodes ( const Aws::Vector< InstanceRecommendationFindingReasonCode > &  value)
inline

The reason for the finding classification of the instance.

Finding reason codes for instances include:

  • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.

  • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

  • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

    Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the mem_used_percent metric in the CWAgent namespace, or the legacy MemoryUtilization metric in the System/Linux namespace. On Windows instances, Compute Optimizer analyses the Memory % Committed Bytes In Use metric in the CWAgent namespace.

  • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metrics of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metric of EBS volumes attached to the current instance during the look-back period.

  • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period.

  • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.

  • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.

  • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.

  • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

  • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.

Definition at line 862 of file InstanceRecommendation.h.

◆ WithInstanceArn() [1/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithInstanceArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the current instance.

Definition at line 83 of file InstanceRecommendation.h.

◆ WithInstanceArn() [2/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithInstanceArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the current instance.

Definition at line 78 of file InstanceRecommendation.h.

◆ WithInstanceArn() [3/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithInstanceArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the current instance.

Definition at line 88 of file InstanceRecommendation.h.

◆ WithInstanceName() [1/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithInstanceName ( Aws::String &&  value)
inline

The name of the current instance.

Definition at line 165 of file InstanceRecommendation.h.

◆ WithInstanceName() [2/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithInstanceName ( const Aws::String value)
inline

The name of the current instance.

Definition at line 160 of file InstanceRecommendation.h.

◆ WithInstanceName() [3/3]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithInstanceName ( const char *  value)
inline

The name of the current instance.

Definition at line 170 of file InstanceRecommendation.h.

◆ WithLastRefreshTimestamp() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithLastRefreshTimestamp ( Aws::Utils::DateTime &&  value)
inline

The timestamp of when the instance recommendation was last generated.

Definition at line 1386 of file InstanceRecommendation.h.

◆ WithLastRefreshTimestamp() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithLastRefreshTimestamp ( const Aws::Utils::DateTime value)
inline

The timestamp of when the instance recommendation was last generated.

Definition at line 1381 of file InstanceRecommendation.h.

◆ WithLookBackPeriodInDays()

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithLookBackPeriodInDays ( double  value)
inline

The number of days for which utilization metrics were analyzed for the instance.

Definition at line 1257 of file InstanceRecommendation.h.

◆ WithRecommendationOptions() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithRecommendationOptions ( Aws::Vector< InstanceRecommendationOption > &&  value)
inline

An array of objects that describe the recommendation options for the instance.

Definition at line 1294 of file InstanceRecommendation.h.

◆ WithRecommendationOptions() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithRecommendationOptions ( const Aws::Vector< InstanceRecommendationOption > &  value)
inline

An array of objects that describe the recommendation options for the instance.

Definition at line 1288 of file InstanceRecommendation.h.

◆ WithRecommendationSources() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithRecommendationSources ( Aws::Vector< RecommendationSource > &&  value)
inline

An array of objects that describe the source resource of the recommendation.

Definition at line 1343 of file InstanceRecommendation.h.

◆ WithRecommendationSources() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithRecommendationSources ( const Aws::Vector< RecommendationSource > &  value)
inline

An array of objects that describe the source resource of the recommendation.

Definition at line 1337 of file InstanceRecommendation.h.

◆ WithUtilizationMetrics() [1/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithUtilizationMetrics ( Aws::Vector< UtilizationMetric > &&  value)
inline

An array of objects that describe the utilization metrics of the instance.

Definition at line 1220 of file InstanceRecommendation.h.

◆ WithUtilizationMetrics() [2/2]

InstanceRecommendation& Aws::ComputeOptimizer::Model::InstanceRecommendation::WithUtilizationMetrics ( const Aws::Vector< UtilizationMetric > &  value)
inline

An array of objects that describe the utilization metrics of the instance.

Definition at line 1214 of file InstanceRecommendation.h.


The documentation for this class was generated from the following file: