使用 Amazon CloudFormation 配置 Application Auto Scaling 资源 - Amazon CloudFormation
创建 AppStream 实例集的扩缩策略为 Aurora 数据库集群创建扩缩策略创建 DynamoDB 表的扩缩策略创建 Amazon ECS 服务的扩缩策略（指标：平均 CPU 和内存）创建 Amazon ECS 服务的扩缩策略（指标：每个目标的平均请求数）使用 Lambda 函数的 cron 表达式创建计划操作使用竞价型实例集的 at 表达式创建计划操作
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使用 Amazon CloudFormation 配置 Application Auto Scaling 资源

本节为不同 Amazon 资源的 Application Auto Scaling 扩展策略和计划操作提供了 Amazon CloudFormation 模板示例。

重要

当模板中包含 Application Auto Scaling 代码段时，您可能需要使用 DependsOn 属性 声明对通过模板创建的特定可扩展资源的依赖关系。这将覆盖默认并行度，并指示 Amazon CloudFormation 按指定的顺序对资源进行操作。否则，可能会在完全设置资源之前应用扩展配置。

创建 AppStream 实例集的扩缩策略

此代码段说明如何创建策略并将其应用于使用 AWS::ApplicationAutoScaling::ScalingPolicy 资源的 AWS::AppStream::Fleet 资源。AWS::ApplicationAutoScaling::ScalableTarget 资源声明一个应用此策略的可扩展目标。Application Auto Scaling 可以扩展队列实例数，最少为 1 个实例，最多为 20 个实例。该策略将实例集的平均容量利用率保持在 75%，横向扩展和横向缩减冷却时间为 300 秒（5 分钟）。

此示例利用 Fn::Join 和 Ref 内置函数，使用在同一模板中指定的 AWS::AppStream::Fleet 资源的逻辑名称来构造 ResourceId 属性。

JSON

{
  "Resources" : {
    "ScalableTarget" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalableTarget",
      "Properties" : {
        "MaxCapacity" : 20,
        "MinCapacity" : 1,
        "RoleARN" : { "Fn::Sub" : "arn:aws:iam::${AWS::AccountId}:role/aws-service-role/appstream.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_AppStreamFleet" },
        "ServiceNamespace" : "appstream",
        "ScalableDimension" : "appstream:fleet:DesiredCapacity",
        "ResourceId" : {
          "Fn::Join" : [
            "/",
            [
              "fleet",
              {
                "Ref" : "logicalName"
              }
            ]
          ]
        }
      }
    },
    "ScalingPolicyAppStreamFleet" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalingPolicy",
      "Properties" : {
        "PolicyName" : { "Fn::Sub" : "${AWS::StackName}-target-tracking-cpu75" },
        "PolicyType" : "TargetTrackingScaling",
        "ServiceNamespace" : "appstream",
        "ScalableDimension" : "appstream:fleet:DesiredCapacity",
        "ResourceId" : {
          "Fn::Join" : [
            "/",
            [
              "fleet",
              {
                "Ref" : "logicalName"
              }
            ]
          ]
        },
        "TargetTrackingScalingPolicyConfiguration" : {
          "TargetValue" : 75,
          "PredefinedMetricSpecification" : {
            "PredefinedMetricType" : "AppStreamAverageCapacityUtilization"
          },
          "ScaleInCooldown" : 300,
          "ScaleOutCooldown" : 300
        }
      }
    } 
  }
}

YAML

---
Resources:
  ScalableTarget:
    Type: AWS::ApplicationAutoScaling::ScalableTarget
    Properties:
      MaxCapacity: 20
      MinCapacity: 1
      RoleARN: 
        Fn::Sub: 'arn:aws:iam::${AWS::AccountId}:role/aws-service-role/appstream.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_AppStreamFleet'
      ServiceNamespace: appstream
      ScalableDimension: appstream:fleet:DesiredCapacity
      ResourceId: !Join
        - /
        - - fleet
          - !Ref logicalName
  ScalingPolicyAppStreamFleet:
    Type: AWS::ApplicationAutoScaling::ScalingPolicy
    Properties:
      PolicyName: !Sub ${AWS::StackName}-target-tracking-cpu75
      PolicyType: TargetTrackingScaling
      ServiceNamespace: appstream
      ScalableDimension: appstream:fleet:DesiredCapacity
      ResourceId: !Join
        - /
        - - fleet
          - !Ref logicalName
      TargetTrackingScalingPolicyConfiguration:
        TargetValue: 75
        PredefinedMetricSpecification:
          PredefinedMetricType: AppStreamAverageCapacityUtilization
        ScaleInCooldown: 300
        ScaleOutCooldown: 300

为 Aurora 数据库集群创建扩缩策略

在此代码段中，您注册了 AWS::RDS::DBCluster 资源。AWS::ApplicationAutoScaling::ScalableTarget 资源表示应动态扩展数据库集群以具有 1-8 个 Aurora 副本。您还可以使用 AWS::ApplicationAutoScaling::ScalingPolicy 资源将目标跟踪扩缩策略应用到集群。

在此配置中，RDSReaderAverageCPUUtilization 预定义指标用于根据 Aurora 数据库集群中所有 Aurora 副本上 40% 的平均 CPU 利用率来调整该 Aurora 数据库集群。该配置将缩减冷却时间指定为 10 分钟，并将扩展冷却时间指定为 5 分钟。

此示例利用 Fn::Sub 内置函数，使用在同一模板中指定的 AWS::RDS::DBCluster 资源的逻辑名称来构造 ResourceId 属性。

JSON

{
  "Resources" : {
    "ScalableTarget" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalableTarget",
      "Properties" : {
        "MaxCapacity" : 8,
        "MinCapacity" : 1,
        "RoleARN" : { "Fn::Sub" : "arn:aws:iam::${AWS::AccountId}:role/aws-service-role/rds.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_RDSCluster" },
        "ServiceNamespace" : "rds",
        "ScalableDimension" : "rds:cluster:ReadReplicaCount",
        "ResourceId" : { "Fn::Sub" : "cluster:${logicalName}" }
      }
    },
    "ScalingPolicyDBCluster" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalingPolicy",
      "Properties" : {
        "PolicyName" : { "Fn::Sub" : "${AWS::StackName}-target-tracking-cpu40" },
        "PolicyType" : "TargetTrackingScaling",
        "ServiceNamespace" : "rds",
        "ScalableDimension" : "rds:cluster:ReadReplicaCount",
        "ResourceId" : { "Fn::Sub" : "cluster:${logicalName}" }, 
        "TargetTrackingScalingPolicyConfiguration" : {
          "TargetValue" : 40,
          "PredefinedMetricSpecification" : {
            "PredefinedMetricType" : "RDSReaderAverageCPUUtilization"
          },
          "ScaleInCooldown" : 600,
          "ScaleOutCooldown" : 300
        }
      }
    }
  }
}

YAML

---
Resources:
  ScalableTarget:
    Type: AWS::ApplicationAutoScaling::ScalableTarget
    Properties:
      MaxCapacity: 8
      MinCapacity: 1
      RoleARN: 
        Fn::Sub: 'arn:aws:iam::${AWS::AccountId}:role/aws-service-role/rds.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_RDSCluster'
      ServiceNamespace: rds
      ScalableDimension: rds:cluster:ReadReplicaCount
      ResourceId: !Sub cluster:${logicalName}
  ScalingPolicyDBCluster:
    Type: AWS::ApplicationAutoScaling::ScalingPolicy
    Properties:
      PolicyName: !Sub ${AWS::StackName}-target-tracking-cpu40
      PolicyType: TargetTrackingScaling
      ServiceNamespace: rds
      ScalableDimension: rds:cluster:ReadReplicaCount
      ResourceId: !Sub cluster:${logicalName}
      TargetTrackingScalingPolicyConfiguration:
        TargetValue: 40
        PredefinedMetricSpecification:
          PredefinedMetricType: RDSReaderAverageCPUUtilization
        ScaleInCooldown: 600
        ScaleOutCooldown: 300

创建 DynamoDB 表的扩缩策略

此代码段说明如何使用 TargetTrackingScaling 策略类型创建策略并将其应用于使用 AWS::ApplicationAutoScaling::ScalingPolicy 资源的 AWS::DynamoDB::Table 资源。AWS::ApplicationAutoScaling::ScalableTarget 资源声明一个应用此策略的可扩展目标，其最小写入容量单位为 5，最大写入容量单位为 15。扩展策略会扩展表的写入容量吞吐量，以 DynamoDBWriteCapacityUtilization 预定义指标将目标利用率维持在 50%。

此示例利用 Fn::Join 和 Ref 内置函数，使用在同一模板中指定的 AWS::DynamoDB::Table 资源的逻辑名称来构造 ResourceId 属性。

注意

有关如何为 DynamoDB 资源创建 Amazon CloudFormation 模板的更多信息，请参阅 Amazon 数据库博客上的博客文章如何使用 Amazon CloudFormation 配置 Amazon DynamoDB 表和索引的自动伸缩。

JSON

{
  "Resources" : {
    "WriteCapacityScalableTarget" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalableTarget",
      "Properties" : {
        "MaxCapacity" : 15,
        "MinCapacity" : 5,
        "RoleARN" : { "Fn::Sub" : "arn:aws:iam::${AWS::AccountId}:role/aws-service-role/dynamodb.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_DynamoDBTable" },
        "ServiceNamespace" : "dynamodb",
        "ScalableDimension" : "dynamodb:table:WriteCapacityUnits",
        "ResourceId" : {
          "Fn::Join" : [
            "/",
            [
              "table",
              {
                "Ref" : "logicalName"
              }
            ]
          ]
        }
      }
    },
    "WriteScalingPolicy" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalingPolicy",
      "Properties" : {
        "PolicyName" : "WriteScalingPolicy",
        "PolicyType" : "TargetTrackingScaling",
        "ScalingTargetId" : { "Ref" : "WriteCapacityScalableTarget" },
        "TargetTrackingScalingPolicyConfiguration" : {
          "TargetValue" : 50.0,
          "ScaleInCooldown" : 60,
          "ScaleOutCooldown" : 60,
          "PredefinedMetricSpecification" : {
            "PredefinedMetricType" : "DynamoDBWriteCapacityUtilization"
          }
        }
      }
    }
  }
}

YAML

---
Resources:
  WriteCapacityScalableTarget:
    Type: AWS::ApplicationAutoScaling::ScalableTarget
    Properties:
      MaxCapacity: 15
      MinCapacity: 5
      RoleARN: 
        Fn::Sub: 'arn:aws:iam::${AWS::AccountId}:role/aws-service-role/dynamodb.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_DynamoDBTable'
      ServiceNamespace: dynamodb
      ScalableDimension: dynamodb:table:WriteCapacityUnits
      ResourceId: !Join
        - /
        - - table
          - !Ref logicalName
  WriteScalingPolicy:
    Type: AWS::ApplicationAutoScaling::ScalingPolicy
    Properties:
      PolicyName: WriteScalingPolicy
      PolicyType: TargetTrackingScaling
      ScalingTargetId: !Ref WriteCapacityScalableTarget
      TargetTrackingScalingPolicyConfiguration:
        TargetValue: 50.0
        ScaleInCooldown: 60
        ScaleOutCooldown: 60
        PredefinedMetricSpecification:
          PredefinedMetricType: DynamoDBWriteCapacityUtilization

创建 Amazon ECS 服务的扩缩策略（指标：平均 CPU 和内存）

此代码段说明如何创建策略并将其应用于使用 AWS::ApplicationAutoScaling::ScalingPolicy 资源的 AWS::ECS::Service 资源。AWS::ApplicationAutoScaling::ScalableTarget 资源声明一个应用此策略的可扩展目标。Application Auto Scaling 可扩展任务的数量，最少 1 个任务，最多 6 个任务。

此示例创建两个 TargetTrackingScaling 策略类型的扩展策略。这些策略用于根据服务的平均 CPU 和内存使用率扩展 ECS 服务。此示例利用 Fn::Join 和 Ref 内置函数，使用在同一模板中指定的 AWS::ECS::Cluster（myContainerCluster）和 AWS::ECS::Service（myService）资源的逻辑名称来构造 ResourceId 属性。

JSON

{
  "Resources" : {
    "ECSScalableTarget" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalableTarget",
      "Properties" : {
        "MaxCapacity" : "6",
        "MinCapacity" : "1",
        "RoleARN" : { "Fn::Sub" : "arn:aws:iam::${AWS::AccountId}:role/aws-service-role/ecs.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_ECSService" },
        "ServiceNamespace" : "ecs",
        "ScalableDimension" : "ecs:service:DesiredCount",
        "ResourceId" : {
          "Fn::Join" : [
            "/",
            [
              "service",
              {
                "Ref" : "myContainerCluster"
              },
              {
                "Fn::GetAtt" : [
                  "myService",
                  "Name"
                ]
              }
            ]
          ]
        }
      }
    },
    "ServiceScalingPolicyCPU" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalingPolicy",
      "Properties" : {
        "PolicyName" : { "Fn::Sub" : "${AWS::StackName}-target-tracking-cpu70" },
        "PolicyType" : "TargetTrackingScaling",
        "ScalingTargetId" : { "Ref" : "ECSScalableTarget" },
        "TargetTrackingScalingPolicyConfiguration" : {
          "TargetValue" : 70.0,
          "ScaleInCooldown" : 180,
          "ScaleOutCooldown" : 60,
          "PredefinedMetricSpecification" : {
            "PredefinedMetricType" : "ECSServiceAverageCPUUtilization"
          }
        }
      }
    },
    "ServiceScalingPolicyMem" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalingPolicy",
      "Properties" : {
        "PolicyName" : { "Fn::Sub" : "${AWS::StackName}-target-tracking-mem90" },
        "PolicyType" : "TargetTrackingScaling",
        "ScalingTargetId" : { "Ref" : "ECSScalableTarget" },
        "TargetTrackingScalingPolicyConfiguration" : {
          "TargetValue" : 90.0,
          "ScaleInCooldown" : 180,
          "ScaleOutCooldown" : 60,
          "PredefinedMetricSpecification" : {
            "PredefinedMetricType" : "ECSServiceAverageMemoryUtilization"
          }
        }
      }
    }
  }
}

YAML

---
Resources:
  ECSScalableTarget:
    Type: AWS::ApplicationAutoScaling::ScalableTarget
    Properties:
      MaxCapacity: 6
      MinCapacity: 1  
      RoleARN: 
        Fn::Sub: 'arn:aws:iam::${AWS::AccountId}:role/aws-service-role/ecs.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_ECSService'
      ServiceNamespace: ecs
      ScalableDimension: 'ecs:service:DesiredCount'
      ResourceId: !Join 
        - /
        - - service
          - !Ref myContainerCluster
          - !GetAtt myService.Name
  ServiceScalingPolicyCPU:
    Type: AWS::ApplicationAutoScaling::ScalingPolicy
    Properties:
      PolicyName: !Sub ${AWS::StackName}-target-tracking-cpu70
      PolicyType: TargetTrackingScaling
      ScalingTargetId: !Ref ECSScalableTarget
      TargetTrackingScalingPolicyConfiguration:
        TargetValue: 70.0
        ScaleInCooldown: 180
        ScaleOutCooldown: 60
        PredefinedMetricSpecification:
          PredefinedMetricType: ECSServiceAverageCPUUtilization
  ServiceScalingPolicyMem:
    Type: AWS::ApplicationAutoScaling::ScalingPolicy
    Properties:
      PolicyName: !Sub ${AWS::StackName}-target-tracking-mem90
      PolicyType: TargetTrackingScaling
      ScalingTargetId: !Ref ECSScalableTarget
      TargetTrackingScalingPolicyConfiguration:
        TargetValue: 90.0
        ScaleInCooldown: 180
        ScaleOutCooldown: 60
        PredefinedMetricSpecification:
          PredefinedMetricType: ECSServiceAverageMemoryUtilization

创建 Amazon ECS 服务的扩缩策略（指标：每个目标的平均请求数）

以下示例将具有 ALBRequestCountPerTarget 预定义指标的目标跟踪扩展策略应用到 ECS 服务。该策略用于在每个目标的请求计数（每分钟）超过目标值时向 ECS 服务添加容量。由于 DisableScaleIn 的值设置为 true，因此，目标跟踪策略不会从可扩展目标中删除容量。

此示例利用 Fn::Join 和 Fn::GetAtt 内置函数，使用在同一模板中指定的 AWS::ElasticLoadBalancingV2::LoadBalancer（myLoadBalancer）和 AWS::ElasticLoadBalancingV2::TargetGroup（myTargetGroup）资源的逻辑名称来构造 ResourceLabel 属性。

可扩展目标的 MaxCapacity 和 MinCapacity 属性以及扩展策略的 TargetValue 属性引用您在创建或更新堆栈时传递给模板的参数值。

JSON

{
  "Resources" : {
    "ECSScalableTarget" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalableTarget",
      "Properties" : {
        "MaxCapacity" : { "Ref" : "MaxCount" },
        "MinCapacity" : { "Ref" : "MinCount" },
        "RoleARN" : { "Fn::Sub" : "arn:aws:iam::${AWS::AccountId}:role/aws-service-role/ecs.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_ECSService" },
        "ServiceNamespace" : "ecs",
        "ScalableDimension" : "ecs:service:DesiredCount",
        "ResourceId" : {
          "Fn::Join" : [
            "/",
            [
              "service",
              {
                "Ref" : "myContainerCluster"
              },
              {
                "Fn::GetAtt" : [
                  "myService",
                  "Name"
                ]
              }
            ]
          ]
        }
      }
    },
    "ServiceScalingPolicyALB" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalingPolicy",
      "Properties" : {
        "PolicyName" : "alb-requests-per-target-per-minute",
        "PolicyType" : "TargetTrackingScaling",
        "ScalingTargetId" : { "Ref" : "ECSScalableTarget" },
        "TargetTrackingScalingPolicyConfiguration" : {
          "TargetValue" : { "Ref" : "ALBPolicyTargetValue" },
          "ScaleInCooldown" : 180,
          "ScaleOutCooldown" : 30,
          "DisableScaleIn" : true,
          "PredefinedMetricSpecification" : {
            "PredefinedMetricType" : "ALBRequestCountPerTarget",
            "ResourceLabel" : {
              "Fn::Join" : [
                "/",
                [
                  {
                    "Fn::GetAtt" : [
                      "myLoadBalancer",
                      "LoadBalancerFullName"
                    ]
                  },
                  {
                    "Fn::GetAtt" : [
                      "myTargetGroup",
                      "TargetGroupFullName"
                    ]
                  }
                ]
              ]
            }
          }
        }
      }
    }
  }
}

YAML

---
Resources:
  ECSScalableTarget:
    Type: AWS::ApplicationAutoScaling::ScalableTarget
    Properties:
      MaxCapacity: !Ref MaxCount
      MinCapacity: !Ref MinCount  
      RoleARN: 
        Fn::Sub: 'arn:aws:iam::${AWS::AccountId}:role/aws-service-role/ecs.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_ECSService'
      ServiceNamespace: ecs
      ScalableDimension: 'ecs:service:DesiredCount'
      ResourceId: !Join 
        - /
        - - service
          - !Ref myContainerCluster
          - !GetAtt myService.Name
  ServiceScalingPolicyALB:
    Type: AWS::ApplicationAutoScaling::ScalingPolicy
    Properties:
      PolicyName: alb-requests-per-target-per-minute
      PolicyType: TargetTrackingScaling
      ScalingTargetId: !Ref ECSScalableTarget
      TargetTrackingScalingPolicyConfiguration:
        TargetValue: !Ref ALBPolicyTargetValue
        ScaleInCooldown: 180
        ScaleOutCooldown: 30
        DisableScaleIn: true
        PredefinedMetricSpecification:
          PredefinedMetricType: ALBRequestCountPerTarget
          ResourceLabel: !Join 
            - '/' 
            - - !GetAtt myLoadBalancer.LoadBalancerFullName
              - !GetAtt myTargetGroup.TargetGroupFullName

使用 Lambda 函数的 cron 表达式创建计划操作

此代码段使用 AWS::ApplicationAutoScaling::ScalableTarget 资源注册名为 BLUE 的函数别名（AWS::Lambda::Alias）的预置并发。它还使用 cron 表达式创建具有重复计划的计划操作。定期计划的时区为 UTC。

它在 RoleARN 属性中使用 Fn::Join 和 Ref 内置函数以指定服务相关角色的 ARN。此示例利用 Fn::Sub 内置函数，使用在同一模板中指定的 AWS::Lambda::Function 或 AWS::Serverless::Function 资源的逻辑名称来构造 ResourceId 属性。

注意

您无法在指向未发布版本（$LATEST）的别名上分配预置并发。

有关如何为 Lambda 资源创建 Amazon CloudFormation 模板的更多信息，请参阅 Amazon 计算博客上的博客文章计划 Amazon Lambda 预置并发性以实现重复使用峰值。

JSON

{
  "ScalableTarget" : {
    "Type" : "AWS::ApplicationAutoScaling::ScalableTarget",
    "Properties" : {
      "MaxCapacity" : 250,
      "MinCapacity" : 0,
      "RoleARN" : {
        "Fn::Join" : [
          ":",
          [
            "arn:aws:iam:",
            {
              "Ref" : "AWS::AccountId"
            },
            "role/aws-service-role/lambda.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_LambdaConcurrency"
          ]
        ]
      },
      "ServiceNamespace" : "lambda",
      "ScalableDimension" : "lambda:function:ProvisionedConcurrency",
      "ResourceId" : { "Fn::Sub" : "function:${logicalName}:BLUE" },
      "ScheduledActions" : [
        {
          "ScalableTargetAction" : {
            "MinCapacity" : "250"
          },
          "ScheduledActionName" : "my-scale-out-scheduled-action",
          "Schedule" : "cron(0 18 * * ? *)",
          "EndTime" : "2022-12-31T12:00:00.000Z"
        }
      ]
    }
  }
}

YAML

ScalableTarget:
  Type: AWS::ApplicationAutoScaling::ScalableTarget
  Properties:
    MaxCapacity: 250
    MinCapacity: 0
    RoleARN: !Join 
      - ':'
      - - 'arn:aws:iam:'
        - !Ref 'AWS::AccountId'
        - role/aws-service-role/lambda.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_LambdaConcurrency
    ServiceNamespace: lambda
    ScalableDimension: lambda:function:ProvisionedConcurrency
    ResourceId: !Sub function:${logicalName}:BLUE
    ScheduledActions:
      - ScalableTargetAction:
          MinCapacity: 250
        ScheduledActionName: my-scale-out-scheduled-action
        Schedule: 'cron(0 18 * * ? *)'
        EndTime: '2022-12-31T12:00:00.000Z'

使用竞价型实例集的 at 表达式创建计划操作

此代码段展示如何使用 AWS::ApplicationAutoScaling::ScalableTarget 资源创建两个仅对 AWS::EC2::SpotFleet 资源发生一次的计划操作。每个一次性计划操作的时区均为 UTC。

此示例利用 Fn::Join 和 Ref 内置函数，使用在同一模板中指定的 AWS::EC2::SpotFleet 资源的逻辑名称来构造 ResourceId 属性。

注意

竞价型实例集请求必须使用 maintain 作为请求类型。一次性请求或 Spot 型限制不支持自动扩展。

JSON

{
  "Resources" : {
    "SpotFleetScalableTarget" : {
      "Type" : "AWS::ApplicationAutoScaling::ScalableTarget",
      "Properties" : {
        "MaxCapacity" : 0,
        "MinCapacity" : 0,
        "RoleARN" : { "Fn::Sub" : "arn:aws:iam::${AWS::AccountId}:role/aws-service-role/ec2.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_EC2SpotFleetRequest" },
        "ServiceNamespace" : "ec2",
        "ScalableDimension" : "ec2:spot-fleet-request:TargetCapacity",
        "ResourceId" : {
          "Fn::Join" : [
            "/",
            [
              "spot-fleet-request",
              {
                "Ref" : "logicalName"
              }
            ]
          ]
        },
        "ScheduledActions" : [
          {
            "ScalableTargetAction" : {
              "MaxCapacity" : "10",
              "MinCapacity" : "10"
            },
            "ScheduledActionName" : "my-scale-out-scheduled-action",
            "Schedule" : "at(2022-05-20T13:00:00)"
          },
          {
            "ScalableTargetAction" : {
              "MaxCapacity" : "0",
              "MinCapacity" : "0"
            },
            "ScheduledActionName" : "my-scale-in-scheduled-action",
            "Schedule" : "at(2022-05-20T21:00:00)"
          }
        ]
      }
    }
  }
}

YAML

---
Resources:
  SpotFleetScalableTarget:
    Type: AWS::ApplicationAutoScaling::ScalableTarget
    Properties:
      MaxCapacity: 0
      MinCapacity: 0
      RoleARN: 
        Fn::Sub: 'arn:aws:iam::${AWS::AccountId}:role/aws-service-role/ec2.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_EC2SpotFleetRequest'
      ServiceNamespace: ec2
      ScalableDimension: 'ec2:spot-fleet-request:TargetCapacity'
      ResourceId: !Join 
        - /
        - - spot-fleet-request
          - !Ref logicalName
      ScheduledActions:
        - ScalableTargetAction:
            MaxCapacity: 10
            MinCapacity: 10
          ScheduledActionName: my-scale-out-scheduled-action
          Schedule: 'at(2022-05-20T13:00:00)'
        - ScalableTargetAction:
            MaxCapacity: 0
            MinCapacity: 0
          ScheduledActionName: my-scale-in-scheduled-action
          Schedule: 'at(2022-05-20T21:00:00)'