
# Generated by default/object.tt
package Paws::AutoScalingPlans::CustomizedLoadMetricSpecification;
  use Moose;
  has Dimensions => (is => 'ro', isa => 'ArrayRef[Paws::AutoScalingPlans::MetricDimension]');
  has MetricName => (is => 'ro', isa => 'Str', required => 1);
  has Namespace => (is => 'ro', isa => 'Str', required => 1);
  has Statistic => (is => 'ro', isa => 'Str', required => 1);
  has Unit => (is => 'ro', isa => 'Str');

1;

### main pod documentation begin ###

=head1 NAME

Paws::AutoScalingPlans::CustomizedLoadMetricSpecification

=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::AutoScalingPlans::CustomizedLoadMetricSpecification object:

  $service_obj->Method(Att1 => { Dimensions => $value, ..., Unit => $value  });

=head3 Results returned from an API call

Use accessors for each attribute. If Att1 is expected to be an Paws::AutoScalingPlans::CustomizedLoadMetricSpecification object:

  $result = $service_obj->Method(...);
  $result->Att1->Dimensions

=head1 DESCRIPTION

Represents a CloudWatch metric of your choosing that can be used for
predictive scaling.

For predictive scaling to work with a customized load metric
specification, AWS Auto Scaling needs access to the C<Sum> and
C<Average> statistics that CloudWatch computes from metric data.

When you choose a load metric, make sure that the required C<Sum> and
C<Average> statistics for your metric are available in CloudWatch and
that they provide relevant data for predictive scaling. The C<Sum>
statistic must represent the total load on the resource, and the
C<Average> statistic must represent the average load per capacity unit
of the resource. For example, there is a metric that counts the number
of requests processed by your Auto Scaling group. If the C<Sum>
statistic represents the total request count processed by the group,
then the C<Average> statistic for the specified metric must represent
the average request count processed by each instance of the group.

If you publish your own metrics, you can aggregate the data points at a
given interval and then publish the aggregated data points to
CloudWatch. Before AWS Auto Scaling generates the forecast, it sums up
all the metric data points that occurred within each hour to match the
granularity period that is used in the forecast (60 minutes).

For information about terminology, available metrics, or how to publish
new metrics, see Amazon CloudWatch Concepts
(https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/cloudwatch_concepts.html)
in the I<Amazon CloudWatch User Guide>.

After creating your scaling plan, you can use the AWS Auto Scaling
console to visualize forecasts for the specified metric. For more
information, see View Scaling Information for a Resource
(https://docs.aws.amazon.com/autoscaling/plans/userguide/gs-create-scaling-plan.html#gs-view-resource)
in the I<AWS Auto Scaling User Guide>.

=head1 ATTRIBUTES


=head2 Dimensions => ArrayRef[L<Paws::AutoScalingPlans::MetricDimension>]

The dimensions of the metric.

Conditional: If you published your metric with dimensions, you must
specify the same dimensions in your customized load metric
specification.


=head2 B<REQUIRED> MetricName => Str

The name of the metric.


=head2 B<REQUIRED> Namespace => Str

The namespace of the metric.


=head2 B<REQUIRED> Statistic => Str

The statistic of the metric. The only valid value is C<Sum>.


=head2 Unit => Str

The unit of the metric.


=head1 SEE ALSO

This class forms part of L<Paws>, describing an object used in L<Paws::AutoScalingPlans>

=head1 BUGS and CONTRIBUTIONS

The source code is located here: L<https://github.com/pplu/aws-sdk-perl>

Please report bugs to: L<https://github.com/pplu/aws-sdk-perl/issues>

=cut