Expand description
Data structures used by operation inputs/outputs.
Modules§
Structs§
- Alarm
Represents a CloudWatch alarm associated with a scaling policy.
- Capacity
Forecast A
GetPredictiveScalingForecastcall returns the capacity forecast for a predictive scaling policy. This structure includes the data points for that capacity forecast, along with the timestamps of those data points.- Customized
Metric Specification Represents a CloudWatch metric of your choosing for a target tracking scaling policy to use with Application Auto Scaling.
For information about the available metrics for a service, see Amazon Web Services services that publish CloudWatch metrics in the Amazon CloudWatch User Guide.
To create your customized metric specification:
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Add values for each required parameter from CloudWatch. You can use an existing metric, or a new metric that you create. To use your own metric, you must first publish the metric to CloudWatch. For more information, see Publish custom metrics in the Amazon CloudWatch User Guide.
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Choose a metric that changes proportionally with capacity. The value of the metric should increase or decrease in inverse proportion to the number of capacity units. That is, the value of the metric should decrease when capacity increases, and increase when capacity decreases.
For more information about the CloudWatch terminology below, see Amazon CloudWatch concepts in the Amazon CloudWatch User Guide.
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- Load
Forecast A
GetPredictiveScalingForecastcall returns the load forecast for a predictive scaling policy. This structure includes the data points for that load forecast, along with the timestamps of those data points and the metric specification.- Metric
Dimension Describes the dimension names and values associated with a metric.
- NotScaled
Reason Describes the reason for an activity that isn't scaled (not scaled activity), in machine-readable format. For help interpreting the not scaled reason details, see Scaling activities for Application Auto Scaling in the Application Auto Scaling User Guide.
- Predefined
Metric Specification Represents a predefined metric for a target tracking scaling policy to use with Application Auto Scaling.
For more information, Predefined metrics for target tracking scaling policies in the Application Auto Scaling User Guide.
- Predictive
Scaling Customized Metric Specification Represents a CloudWatch metric of your choosing for a predictive scaling policy.
- Predictive
Scaling Metric Describes the scaling metric.
- Predictive
Scaling Metric Data Query The metric data to return. Also defines whether this call is returning data for one metric only, or whether it is performing a math expression on the values of returned metric statistics to create a new time series. A time series is a series of data points, each of which is associated with a timestamp.
- Predictive
Scaling Metric Dimension Describes the dimension of a metric.
- Predictive
Scaling Metric Specification This structure specifies the metrics and target utilization settings for a predictive scaling policy.
You must specify either a metric pair, or a load metric and a scaling metric individually. Specifying a metric pair instead of individual metrics provides a simpler way to configure metrics for a scaling policy. You choose the metric pair, and the policy automatically knows the correct sum and average statistics to use for the load metric and the scaling metric.
- Predictive
Scaling Metric Stat This structure defines the CloudWatch metric to return, along with the statistic and unit.
- Predictive
Scaling Policy Configuration Represents a predictive scaling policy configuration. Predictive scaling is supported on Amazon ECS services.
- Predictive
Scaling Predefined Load Metric Specification Describes a load metric for a predictive scaling policy.
When returned in the output of
DescribePolicies, it indicates that a predictive scaling policy uses individually specified load and scaling metrics instead of a metric pair.The following predefined metrics are available for predictive scaling:
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ECSServiceAverageCPUUtilization -
ECSServiceAverageMemoryUtilization -
ECSServiceCPUUtilization -
ECSServiceMemoryUtilization -
ECSServiceTotalCPUUtilization -
ECSServiceTotalMemoryUtilization -
ALBRequestCount -
ALBRequestCountPerTarget -
TotalALBRequestCount
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- Predictive
Scaling Predefined Metric Pair Specification Represents a metric pair for a predictive scaling policy.
The following predefined metrics are available for predictive scaling:
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ECSServiceAverageCPUUtilization -
ECSServiceAverageMemoryUtilization -
ECSServiceCPUUtilization -
ECSServiceMemoryUtilization -
ECSServiceTotalCPUUtilization -
ECSServiceTotalMemoryUtilization -
ALBRequestCount -
ALBRequestCountPerTarget -
TotalALBRequestCount
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- Predictive
Scaling Predefined Scaling Metric Specification Describes a scaling metric for a predictive scaling policy.
When returned in the output of
DescribePolicies, it indicates that a predictive scaling policy uses individually specified load and scaling metrics instead of a metric pair.The following predefined metrics are available for predictive scaling:
-
ECSServiceAverageCPUUtilization -
ECSServiceAverageMemoryUtilization -
ECSServiceCPUUtilization -
ECSServiceMemoryUtilization -
ECSServiceTotalCPUUtilization -
ECSServiceTotalMemoryUtilization -
ALBRequestCount -
ALBRequestCountPerTarget -
TotalALBRequestCount
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- Scalable
Target Represents a scalable target.
- Scalable
Target Action Represents the minimum and maximum capacity for a scheduled action.
- Scaling
Activity Represents a scaling activity.
- Scaling
Policy Represents a scaling policy to use with Application Auto Scaling.
For more information about configuring scaling policies for a specific service, see Amazon Web Services services that you can use with Application Auto Scaling in the Application Auto Scaling User Guide.
- Scheduled
Action Represents a scheduled action.
- Step
Adjustment Represents a step adjustment for a StepScalingPolicyConfiguration. Describes an adjustment based on the difference between the value of the aggregated CloudWatch metric and the breach threshold that you've defined for the alarm.
For the following examples, suppose that you have an alarm with a breach threshold of 50:
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To initiate the adjustment when the metric is greater than or equal to 50 and less than 60, specify a lower bound of
0and an upper bound of10. -
To initiate the adjustment when the metric is greater than 40 and less than or equal to 50, specify a lower bound of
-10and an upper bound of0.
There are a few rules for the step adjustments for your step policy:
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The ranges of your step adjustments can't overlap or have a gap.
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At most one step adjustment can have a null lower bound. If one step adjustment has a negative lower bound, then there must be a step adjustment with a null lower bound.
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At most one step adjustment can have a null upper bound. If one step adjustment has a positive upper bound, then there must be a step adjustment with a null upper bound.
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The upper and lower bound can't be null in the same step adjustment.
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- Step
Scaling Policy Configuration Represents a step scaling policy configuration to use with Application Auto Scaling.
For more information, see Step scaling policies in the Application Auto Scaling User Guide.
- Suspended
State Specifies whether the scaling activities for a scalable target are in a suspended state.
- Target
Tracking Metric Represents a specific metric.
Metric is a property of the
TargetTrackingMetricStatobject.- Target
Tracking Metric Data Query The metric data to return. Also defines whether this call is returning data for one metric only, or whether it is performing a math expression on the values of returned metric statistics to create a new time series. A time series is a series of data points, each of which is associated with a timestamp.
For more information and examples, see Create a target tracking scaling policy for Application Auto Scaling using metric math in the Application Auto Scaling User Guide.
- Target
Tracking Metric Dimension Describes the dimension of a metric.
- Target
Tracking Metric Stat This structure defines the CloudWatch metric to return, along with the statistic and unit.
For more information about the CloudWatch terminology below, see Amazon CloudWatch concepts in the Amazon CloudWatch User Guide.
- Target
Tracking Scaling Policy Configuration Represents a target tracking scaling policy configuration to use with Application Auto Scaling.
For more information, see Target tracking scaling policies in the Application Auto Scaling User Guide.
Enums§
- Adjustment
Type - When writing a match expression against
AdjustmentType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature. - Metric
Aggregation Type - When writing a match expression against
MetricAggregationType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature. - Metric
Statistic - When writing a match expression against
MetricStatistic, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature. - Metric
Type - When writing a match expression against
MetricType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature. - Policy
Type - When writing a match expression against
PolicyType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature. - Predictive
Scaling MaxCapacity Breach Behavior - When writing a match expression against
PredictiveScalingMaxCapacityBreachBehavior, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature. - Predictive
Scaling Mode - When writing a match expression against
PredictiveScalingMode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature. - Scalable
Dimension - When writing a match expression against
ScalableDimension, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature. - Scaling
Activity Status Code - When writing a match expression against
ScalingActivityStatusCode, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature. - Service
Namespace - When writing a match expression against
ServiceNamespace, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.