package Paws::ComputeOptimizer::GetLambdaFunctionRecommendations; use Moose; has AccountIds => (is => 'ro', isa => 'ArrayRef[Str|Undef]', traits => ['NameInRequest'], request_name => 'accountIds' ); has Filters => (is => 'ro', isa => 'ArrayRef[Paws::ComputeOptimizer::LambdaFunctionRecommendationFilter]', traits => ['NameInRequest'], request_name => 'filters' ); has FunctionArns => (is => 'ro', isa => 'ArrayRef[Str|Undef]', traits => ['NameInRequest'], request_name => 'functionArns' ); has MaxResults => (is => 'ro', isa => 'Int', traits => ['NameInRequest'], request_name => 'maxResults' ); has NextToken => (is => 'ro', isa => 'Str', traits => ['NameInRequest'], request_name => 'nextToken' ); use MooseX::ClassAttribute; class_has _api_call => (isa => 'Str', is => 'ro', default => 'GetLambdaFunctionRecommendations'); class_has _returns => (isa => 'Str', is => 'ro', default => 'Paws::ComputeOptimizer::GetLambdaFunctionRecommendationsResponse'); class_has _result_key => (isa => 'Str', is => 'ro'); 1; ### main pod documentation begin ### =head1 NAME Paws::ComputeOptimizer::GetLambdaFunctionRecommendations - Arguments for method GetLambdaFunctionRecommendations on L =head1 DESCRIPTION This class represents the parameters used for calling the method GetLambdaFunctionRecommendations on the L service. Use the attributes of this class as arguments to method GetLambdaFunctionRecommendations. You shouldn't make instances of this class. Each attribute should be used as a named argument in the call to GetLambdaFunctionRecommendations. =head1 SYNOPSIS my $compute-optimizer = Paws->service('ComputeOptimizer'); my $GetLambdaFunctionRecommendationsResponse = $compute -optimizer->GetLambdaFunctionRecommendations( AccountIds => [ 'MyAccountId', ... ], # OPTIONAL Filters => [ { Name => 'Finding', # values: Finding, FindingReasonCode; OPTIONAL Values => [ 'MyFilterValue', ... ], # OPTIONAL }, ... ], # OPTIONAL FunctionArns => [ 'MyFunctionArn', ... ], # OPTIONAL MaxResults => 1, # OPTIONAL NextToken => 'MyNextToken', # OPTIONAL ); # Results: my $LambdaFunctionRecommendations = $GetLambdaFunctionRecommendationsResponse->LambdaFunctionRecommendations; my $NextToken = $GetLambdaFunctionRecommendationsResponse->NextToken; # Returns a L object. Values for attributes that are native types (Int, String, Float, etc) can passed as-is (scalar values). Values for complex Types (objects) can be passed as a HashRef. The keys and values of the hashref will be used to instance the underlying object. For the AWS API documentation, see L =head1 ATTRIBUTES =head2 AccountIds => ArrayRef[Str|Undef] The ID of the AWS account for which to return function recommendations. If your account is the management account of an organization, use this parameter to specify the member account for which you want to return function recommendations. Only one account ID can be specified per request. =head2 Filters => ArrayRef[L] An array of objects that describe a filter that returns a more specific list of function recommendations. =head2 FunctionArns => ArrayRef[Str|Undef] The Amazon Resource Name (ARN) of the functions for which to return recommendations. You can specify a qualified or unqualified ARN. If you specify an unqualified ARN without a function version suffix, Compute Optimizer will return recommendations for the latest (C<$LATEST>) version of the function. If you specify a qualified ARN with a version suffix, Compute Optimizer will return recommendations for the specified function version. For more information about using function versions, see Using versions (https://docs.aws.amazon.com/lambda/latest/dg/configuration-versions.html#versioning-versions-using) in the I. =head2 MaxResults => Int The maximum number of function recommendations to return with a single request. To retrieve the remaining results, make another request with the returned C value. =head2 NextToken => Str The token to advance to the next page of function recommendations. =head1 SEE ALSO This class forms part of L, documenting arguments for method GetLambdaFunctionRecommendations in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut