ScalableTarget

class aws_cdk.aws_applicationautoscaling.ScalableTarget(scope, id, *, max_capacity, min_capacity, resource_id, scalable_dimension, service_namespace, role=None)

Bases: Resource

Define a scalable target.

ExampleMetadata:

infused

Example:

import aws_cdk.aws_lambda as lambda_

# code: lambda.Code


handler = lambda_.Function(self, "MyFunction",
    runtime=lambda_.Runtime.PYTHON_3_7,
    handler="index.handler",
    code=code,

    reserved_concurrent_executions=2
)

fn_ver = handler.current_version

target = appscaling.ScalableTarget(self, "ScalableTarget",
    service_namespace=appscaling.ServiceNamespace.LAMBDA,
    max_capacity=100,
    min_capacity=10,
    resource_id=f"function:{handler.functionName}:{fnVer.version}",
    scalable_dimension="lambda:function:ProvisionedConcurrency"
)

target.scale_to_track_metric("PceTracking",
    target_value=0.9,
    predefined_metric=appscaling.PredefinedMetric.LAMBDA_PROVISIONED_CONCURRENCY_UTILIZATION
)
Parameters:

  • scope (Construct) –

  • id (str) –

  • max_capacity (Union[int, float]) – The maximum value that Application Auto Scaling can use to scale a target during a scaling activity.

  • min_capacity (Union[int, float]) – The minimum value that Application Auto Scaling can use to scale a target during a scaling activity.

  • resource_id (str) – The resource identifier to associate with this scalable target. This string consists of the resource type and unique identifier. Example value: service/ecsStack-MyECSCluster-AB12CDE3F4GH/ecsStack-MyECSService-AB12CDE3F4GH

  • scalable_dimension (str) – The scalable dimension that’s associated with the scalable target. Specify the service namespace, resource type, and scaling property. Example value: ecs:service:DesiredCount

  • service_namespace (ServiceNamespace) – The namespace of the AWS service that provides the resource or custom-resource for a resource provided by your own application or service. For valid AWS service namespace values, see the RegisterScalableTarget action in the Application Auto Scaling API Reference.

  • role (Optional[IRole]) – Role that allows Application Auto Scaling to modify your scalable target. Default: A role is automatically created

Methods

add_to_role_policy(statement)

Add a policy statement to the role’s policy.

Parameters:

statement (PolicyStatement) –

Return type:

None

apply_removal_policy(policy)

Apply the given removal policy to this resource.

The Removal Policy controls what happens to this resource when it stops being managed by CloudFormation, either because you’ve removed it from the CDK application or because you’ve made a change that requires the resource to be replaced.

The resource can be deleted (RemovalPolicy.DESTROY), or left in your AWS account for data recovery and cleanup later (RemovalPolicy.RETAIN).

Parameters:

policy (RemovalPolicy) –

Return type:

None

scale_on_metric(id, *, metric, scaling_steps, adjustment_type=None, cooldown=None, datapoints_to_alarm=None, evaluation_periods=None, metric_aggregation_type=None, min_adjustment_magnitude=None)

Scale out or in, in response to a metric.

Parameters:

  • id (str) –

  • metric (IMetric) – Metric to scale on.

  • scaling_steps (Sequence[Union[ScalingInterval, Dict[str, Any]]]) – The intervals for scaling. Maps a range of metric values to a particular scaling behavior. Must be between 2 and 40 steps.

  • adjustment_type (Optional[AdjustmentType]) – How the adjustment numbers inside ‘intervals’ are interpreted. Default: ChangeInCapacity

  • cooldown (Optional[Duration]) – Grace period after scaling activity. Subsequent scale outs during the cooldown period are squashed so that only the biggest scale out happens. Subsequent scale ins during the cooldown period are ignored. Default: No cooldown period

  • datapoints_to_alarm (Union[int, float, None]) – The number of data points out of the evaluation periods that must be breaching to trigger a scaling action. Creates an “M out of N” alarm, where this property is the M and the value set for evaluationPeriods is the N value. Only has meaning if evaluationPeriods != 1. Default: evaluationPeriods

  • evaluation_periods (Union[int, float, None]) – How many evaluation periods of the metric to wait before triggering a scaling action. Raising this value can be used to smooth out the metric, at the expense of slower response times. If datapointsToAlarm is not set, then all data points in the evaluation period must meet the criteria to trigger a scaling action. Default: 1

  • metric_aggregation_type (Optional[MetricAggregationType]) – Aggregation to apply to all data points over the evaluation periods. Only has meaning if evaluationPeriods != 1. Default: - The statistic from the metric if applicable (MIN, MAX, AVERAGE), otherwise AVERAGE.

  • min_adjustment_magnitude (Union[int, float, None]) – Minimum absolute number to adjust capacity with as result of percentage scaling. Only when using AdjustmentType = PercentChangeInCapacity, this number controls the minimum absolute effect size. Default: No minimum scaling effect

Return type:

StepScalingPolicy

scale_on_schedule(id, *, schedule, end_time=None, max_capacity=None, min_capacity=None, start_time=None)

Scale out or in based on time.

Parameters:

  • id (str) –

  • schedule (Schedule) – When to perform this action.

  • end_time (Optional[datetime]) – When this scheduled action expires. Default: The rule never expires.

  • max_capacity (Union[int, float, None]) – The new maximum capacity. During the scheduled time, the current capacity is above the maximum capacity, Application Auto Scaling scales in to the maximum capacity. At least one of maxCapacity and minCapacity must be supplied. Default: No new maximum capacity

  • min_capacity (Union[int, float, None]) – The new minimum capacity. During the scheduled time, if the current capacity is below the minimum capacity, Application Auto Scaling scales out to the minimum capacity. At least one of maxCapacity and minCapacity must be supplied. Default: No new minimum capacity

  • start_time (Optional[datetime]) – When this scheduled action becomes active. Default: The rule is activate immediately

Return type:

None

scale_to_track_metric(id, *, target_value, custom_metric=None, predefined_metric=None, resource_label=None, disable_scale_in=None, policy_name=None, scale_in_cooldown=None, scale_out_cooldown=None)

Scale out or in in order to keep a metric around a target value.

Parameters:

  • id (str) –

  • target_value (Union[int, float]) – The target value for the metric.

  • custom_metric (Optional[IMetric]) – A custom metric for application autoscaling. The metric must track utilization. Scaling out will happen if the metric is higher than the target value, scaling in will happen in the metric is lower than the target value. Exactly one of customMetric or predefinedMetric must be specified. Default: - No custom metric.

  • predefined_metric (Optional[PredefinedMetric]) – A predefined metric for application autoscaling. The metric must track utilization. Scaling out will happen if the metric is higher than the target value, scaling in will happen in the metric is lower than the target value. Exactly one of customMetric or predefinedMetric must be specified. Default: - No predefined metrics.

  • resource_label (Optional[str]) – Identify the resource associated with the metric type. Only used for predefined metric ALBRequestCountPerTarget. Example value: app/<load-balancer-name>/<load-balancer-id>/targetgroup/<target-group-name>/<target-group-id> Default: - No resource label.

  • disable_scale_in (Optional[bool]) – Indicates whether scale in by the target tracking policy is disabled. If the value is true, scale in is disabled and the target tracking policy won’t remove capacity from the scalable resource. Otherwise, scale in is enabled and the target tracking policy can remove capacity from the scalable resource. Default: false

  • policy_name (Optional[str]) – A name for the scaling policy. Default: - Automatically generated name.

  • scale_in_cooldown (Optional[Duration]) – Period after a scale in activity completes before another scale in activity can start. Default: Duration.seconds(300) for the following scalable targets: ECS services, Spot Fleet requests, EMR clusters, AppStream 2.0 fleets, Aurora DB clusters, Amazon SageMaker endpoint variants, Custom resources. For all other scalable targets, the default value is Duration.seconds(0): DynamoDB tables, DynamoDB global secondary indexes, Amazon Comprehend document classification endpoints, Lambda provisioned concurrency

  • scale_out_cooldown (Optional[Duration]) – Period after a scale out activity completes before another scale out activity can start. Default: Duration.seconds(300) for the following scalable targets: ECS services, Spot Fleet requests, EMR clusters, AppStream 2.0 fleets, Aurora DB clusters, Amazon SageMaker endpoint variants, Custom resources. For all other scalable targets, the default value is Duration.seconds(0): DynamoDB tables, DynamoDB global secondary indexes, Amazon Comprehend document classification endpoints, Lambda provisioned concurrency

Return type:

TargetTrackingScalingPolicy

to_string()

Returns a string representation of this construct.

Return type:

str

Attributes

env

The environment this resource belongs to.

For resources that are created and managed by the CDK (generally, those created by creating new class instances like Role, Bucket, etc.), this is always the same as the environment of the stack they belong to; however, for imported resources (those obtained from static methods like fromRoleArn, fromBucketName, etc.), that might be different than the stack they were imported into.

node

The tree node.

role

The role used to give AutoScaling permissions to your resource.

scalable_target_id

ID of the Scalable Target.

Example value: service/ecsStack-MyECSCluster-AB12CDE3F4GH/ecsStack-MyECSService-AB12CDE3F4GH|ecs:service:DesiredCount|ecs

Attribute:

true

stack

The stack in which this resource is defined.

Static Methods

classmethod from_scalable_target_id(scope, id, scalable_target_id)
Parameters:

  • scope (Construct) –

  • id (str) –

  • scalable_target_id (str) –

Return type:

IScalableTarget

classmethod is_construct(x)

Checks if x is a construct.

Use this method instead of instanceof to properly detect Construct instances, even when the construct library is symlinked.

Explanation: in JavaScript, multiple copies of the constructs library on disk are seen as independent, completely different libraries. As a consequence, the class Construct in each copy of the constructs library is seen as a different class, and an instance of one class will not test as instanceof the other class. npm install will not create installations like this, but users may manually symlink construct libraries together or use a monorepo tool: in those cases, multiple copies of the constructs library can be accidentally installed, and instanceof will behave unpredictably. It is safest to avoid using instanceof, and using this type-testing method instead.

Parameters:

x (Any) – Any object.

Return type:

bool

Returns:

true if x is an object created from a class which extends Construct.

classmethod is_owned_resource(construct)

Returns true if the construct was created by CDK, and false otherwise.

Parameters:

construct (IConstruct) –

Return type:

bool

classmethod is_resource(construct)

Check whether the given construct is a Resource.

Parameters:

construct (IConstruct) –

Return type:

bool