Auto Scaling:DescribeScalingRules

The name of the metric of the event-triggered task that is associated with the scaling rule.

The adjustment method of the scaling rule. Valid values:

• QuantityChangeInCapacity: adds or removes the specified number of Elastic Compute Service (ECS) instances to or from the scaling group.
• PercentChangeInCapacity: adds or removes the specified percentage of ECS instances to or from the scaling group.
• TotalCapacity: adjusts the number of ECS instances in the scaling group to the specified number.

The maximum number of ECS instances that can be contained in the scaling group. If you specify this parameter, you must also specify PredictiveValueBehavior.

The warm-up period of instances. During the warm-up period, a series of preparation measures are taken for the new instances. Performance metrics of instances being warmed up are not counted towards the monitoring range.

The number of consecutive times that the event-triggered task created for scale-out purposes must meet the threshold conditions before an alert is triggered. After a target tracking scaling rule is created, an event-triggered task is automatically created and associated with the target tracking scaling rule.

The mode of the predictive scaling rule. Valid values:

• PredictAndScale: provides predictions and creates prediction tasks.
• PredictOnly: provides predictions but does not create prediction tasks.

The minimum number of instances that must be scaled. This parameter takes effect only if you set ScalingRuleType to SimpleScalingRule or StepScalingRule and set AdjustmentType to PercentChangeInCapacity.

The unique identifier of the scaling rule.

The amount of buffer time before prediction tasks are executed. By default, all prediction tasks that are automatically created based on a predictive scaling rule are executed on the hour. You can specify a buffer time for resource preparation before prediction tasks are executed. Valid values: 0 to 60. Unit: minutes.

The minimum number of ECS instances that must be contained in the scaling group.

The ID of the scaling group.

The action on the predicted maximum value. Valid values:

• MaxOverridePredictiveValue: uses the initial maximum capacity as the maximum value for prediction tasks if the predicted value is greater than the initial maximum capacity.
• PredictiveValueOverrideMax: uses the predicted value as the maximum value for prediction tasks when the predicted value is greater than the initial maximum capacity.
• PredictiveValueOverrideMaxWithBuffer: increases the predicted value by a ratio that is specified by PredictiveValueBuffer, and uses the increased value as the maximum value for prediction tasks if the predicted value increased by this ratio is greater than the initial maximum capacity.

The target value of the metric. If you set ScalingRuleType to TargetTrackingScalingRule or PredictiveScalingRule, Auto Scaling keeps the metric value close to the target value by adding instances to or removing instances from the scaling group.

The cooldown period of the scaling rule. This parameter is available only if you set ScalingRuleType to SimpleScalingRule. Valid values: 0 to 86400. Unit: seconds.

The maximum number of ECS instances that can be contained in the scaling group.

The ratio based on which the predicted value is increased when PredictiveValueBehavior is set to PredictiveValueOverrideMaxWithBuffer. If the predicted value increased by this ratio is greater than the initial maximum capacity, the increased value is used as the maximum value for prediction tasks. Valid values: 0 to 100.

The type of the scaling rule. Valid values:

• SimpleScalingRule: a simple scaling rule. Once a simple scaling rule is executed, Auto Scaling adjusts the number of ECS instances in the scaling group based on the values of AdjustmentType and AdjustmentValue.
• TargetTrackingScalingRule: a target tracking scaling rule. Once a target tracking scaling rule is executed, Auto Scaling dynamically calculates the number of ECS instances or elastic container instances to scale based on the predefined metric (MetricName) and attempts to maintain the metric value close to the specified target value (TargetValue).
• StepScalingRule: a step scaling rule. Once a step scaling rule is executed, Auto Scaling scales instances step by step based on the predefined thresholds and metric values.
• PredictiveScalingRule: a predictive scaling rule. Once a predictive scaling rule is executed, Auto Scaling analyzes the historical monitoring data based on the machine learning technology and predicts the trends of metric data. Auto Scaling also creates scheduled tasks to enable dynamic adjustment of the boundary values for the scaling group.

The number of instances that must be scaled based on the scaling rule.

The number of consecutive times that the event-triggered task for scale-in purposes must meet the threshold conditions before an alert is triggered. After a target tracking scaling rule is created, an event-triggered task is automatically created and associated with the target tracking scaling rule.

Indicates whether scale-in is disabled. This parameter takes effect only if you set ScalingRuleType to TargetTrackingScalingRule. Valid values:

• true
• false

The name of the scaling rule.

The ID of the scaling rule.

The event-triggered tasks that are associated with the scaling rule. The value of this parameter is returned only if you set ShowAlarmRules to true. Otherwise, null is returned.

The step adjustments of the step scaling rule.

The dimensions. This parameter is applicable to target tracking scaling rules. You can specify this parameter if your predefined metric requires extra dimensions. For example, if you predefine the LoadBalancerRealServerAverageQps metric, you must use this parameter to specify the rulePool dimension.