# Generated by default/object.tt package Paws::ComputeOptimizer::InstanceRecommendation; use Moose; has AccountId => (is => 'ro', isa => 'Str', request_name => 'accountId', traits => ['NameInRequest']); has CurrentInstanceType => (is => 'ro', isa => 'Str', request_name => 'currentInstanceType', traits => ['NameInRequest']); has Finding => (is => 'ro', isa => 'Str', request_name => 'finding', traits => ['NameInRequest']); has FindingReasonCodes => (is => 'ro', isa => 'ArrayRef[Str|Undef]', request_name => 'findingReasonCodes', traits => ['NameInRequest']); has InstanceArn => (is => 'ro', isa => 'Str', request_name => 'instanceArn', traits => ['NameInRequest']); has InstanceName => (is => 'ro', isa => 'Str', request_name => 'instanceName', traits => ['NameInRequest']); has LastRefreshTimestamp => (is => 'ro', isa => 'Str', request_name => 'lastRefreshTimestamp', traits => ['NameInRequest']); has LookBackPeriodInDays => (is => 'ro', isa => 'Num', request_name => 'lookBackPeriodInDays', traits => ['NameInRequest']); has RecommendationOptions => (is => 'ro', isa => 'ArrayRef[Paws::ComputeOptimizer::InstanceRecommendationOption]', request_name => 'recommendationOptions', traits => ['NameInRequest']); has RecommendationSources => (is => 'ro', isa => 'ArrayRef[Paws::ComputeOptimizer::RecommendationSource]', request_name => 'recommendationSources', traits => ['NameInRequest']); has UtilizationMetrics => (is => 'ro', isa => 'ArrayRef[Paws::ComputeOptimizer::UtilizationMetric]', request_name => 'utilizationMetrics', traits => ['NameInRequest']); 1; ### main pod documentation begin ### =head1 NAME Paws::ComputeOptimizer::InstanceRecommendation =head1 USAGE This class represents one of two things: =head3 Arguments in a call to a service Use the attributes of this class as arguments to methods. You shouldn't make instances of this class. Each attribute should be used as a named argument in the calls that expect this type of object. As an example, if Att1 is expected to be a Paws::ComputeOptimizer::InstanceRecommendation object: $service_obj->Method(Att1 => { AccountId => $value, ..., UtilizationMetrics => $value }); =head3 Results returned from an API call Use accessors for each attribute. If Att1 is expected to be an Paws::ComputeOptimizer::InstanceRecommendation object: $result = $service_obj->Method(...); $result->Att1->AccountId =head1 DESCRIPTION Describes an Amazon EC2 instance recommendation. =head1 ATTRIBUTES =head2 AccountId => Str The AWS account ID of the instance. =head2 CurrentInstanceType => Str The instance type of the current instance. =head2 Finding => Str The finding classification of the instance. Findings for instances include: =over =item * B >EAn 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. =item * B >EAn 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. =item * B >EAn 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, AWS Compute Optimizer might recommend a new generation instance type. =back =head2 FindingReasonCodes => ArrayRef[Str|Undef] The reason for the finding classification of the instance. Finding reason codes for instances include: =over =item * B > E The instanceEs CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the C metric of the current instance during the look-back period. =item * B > E The instanceEs 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 C metric of the current instance during the look-back period. =item * B > E The instanceEs 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. =item * B > E The instanceEs 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 (https://docs.aws.amazon.com/compute-optimizer/latest/ug/metrics.html#cw-agent) in the I. On Linux instances, Compute Optimizer analyses the C metric in the C namespace, or the legacy C metric in the C namespace. On Windows instances, Compute Optimizer analyses the C metric in the C namespace. =item * B > E The instanceEs EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the C and C metrics of EBS volumes attached to the current instance during the look-back period. =item * B > E The instanceEs 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 C and C metrics of EBS volumes attached to the current instance during the look-back period. =item * B > E The instanceEs EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the C and C metric of EBS volumes attached to the current instance during the look-back period. =item * B > E The instanceEs 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 C and C metric of EBS volumes attached to the current instance during the look-back period. =item * B > E The instanceEs network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the C and C metrics of the current instance during the look-back period. =item * B > E The instanceEs 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 C and C metrics of the current instance during the look-back period. This finding reason happens when the C or C performance of an instance is impacted. =item * B > E The instanceEs 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 C and C metrics of the current instance during the look-back period. =item * B > E The instanceEs 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 C and C metrics of the current instance during the look-back period. =item * B > E The instanceEs disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the C and C metrics of the current instance during the look-back period. =item * B > E The instanceEs 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 C and C metrics of the current instance during the look-back period. =item * B > E The instanceEs disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the C and C metrics of the current instance during the look-back period. =item * B > E The instanceEs 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 C and C metrics of the current instance during the look-back period. =back For more information about instance metrics, see List the available CloudWatch metrics for your instances (https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/viewing_metrics_with_cloudwatch.html) in the I. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS (https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using_cloudwatch_ebs.html) in the I. =head2 InstanceArn => Str The Amazon Resource Name (ARN) of the current instance. =head2 InstanceName => Str The name of the current instance. =head2 LastRefreshTimestamp => Str The time stamp of when the instance recommendation was last refreshed. =head2 LookBackPeriodInDays => Num The number of days for which utilization metrics were analyzed for the instance. =head2 RecommendationOptions => ArrayRef[L] An array of objects that describe the recommendation options for the instance. =head2 RecommendationSources => ArrayRef[L] An array of objects that describe the source resource of the recommendation. =head2 UtilizationMetrics => ArrayRef[L] An array of objects that describe the utilization metrics of the instance. =head1 SEE ALSO This class forms part of L, describing an object used in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut