CfnInferenceScheduler

class aws_cdk.aws_lookoutequipment.CfnInferenceScheduler(scope, id, *, data_input_configuration, data_output_configuration, data_upload_frequency, model_name, role_arn, data_delay_offset_in_minutes=None, inference_scheduler_name=None, server_side_kms_key_id=None, tags=None)

Bases: aws_cdk.core.CfnResource

A CloudFormation AWS::LookoutEquipment::InferenceScheduler.

Creates a scheduled inference. Scheduling an inference is setting up a continuous real-time inference plan to analyze new measurement data. When setting up the schedule, you provide an Amazon S3 bucket location for the input data, assign it a delimiter between separate entries in the data, set an offset delay if desired, and set the frequency of inferencing. You must also provide an Amazon S3 bucket location for the output data. .. epigraph:

Updating some properties below (for example, InferenceSchedulerName and ServerSideKmsKeyId) triggers a resource replacement, which requires a new model. To replace such a property using AWS CloudFormation , but without creating a completely new stack, you must replace ModelName. If you need to replace the property, but want to use the same model, delete the current stack and create a new one with the updated properties.
CloudformationResource

AWS::LookoutEquipment::InferenceScheduler

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html

ExampleMetadata

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
import aws_cdk.aws_lookoutequipment as lookoutequipment

# data_input_configuration: Any
# data_output_configuration: Any

cfn_inference_scheduler = lookoutequipment.CfnInferenceScheduler(self, "MyCfnInferenceScheduler",
    data_input_configuration=data_input_configuration,
    data_output_configuration=data_output_configuration,
    data_upload_frequency="dataUploadFrequency",
    model_name="modelName",
    role_arn="roleArn",

    # the properties below are optional
    data_delay_offset_in_minutes=123,
    inference_scheduler_name="inferenceSchedulerName",
    server_side_kms_key_id="serverSideKmsKeyId",
    tags=[CfnTag(
        key="key",
        value="value"
    )]
)

Create a new AWS::LookoutEquipment::InferenceScheduler.

Parameters
  • scope (Construct) –

    • scope in which this resource is defined.

  • id (str) –

    • scoped id of the resource.

  • data_input_configuration (Any) – Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

  • data_output_configuration (Any) – Specifies configuration information for the output results for the inference scheduler, including the Amazon S3 location for the output.

  • data_upload_frequency (str) – How often data is uploaded to the source S3 bucket for the input data. This value is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

  • model_name (str) – The name of the ML model used for the inference scheduler.

  • role_arn (str) – The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference.

  • data_delay_offset_in_minutes (Union[int, float, None]) – A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if an offset delay time of five minutes was selected, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don’t need to stop and restart the scheduler when uploading new data.

  • inference_scheduler_name (Optional[str]) – The name of the inference scheduler.

  • server_side_kms_key_id (Optional[str]) – Provides the identifier of the AWS KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment .

  • tags (Optional[Sequence[CfnTag]]) – Any tags associated with the inference scheduler. For more information, see Tag .

Methods

add_deletion_override(path)

Syntactic sugar for addOverride(path, undefined).

Parameters

path (str) – The path of the value to delete.

Return type

None

add_depends_on(target)

Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.

This can be used for resources across stacks (or nested stack) boundaries and the dependency will automatically be transferred to the relevant scope.

Parameters

target (CfnResource) –

Return type

None

add_metadata(key, value)

Add a value to the CloudFormation Resource Metadata.

Parameters
  • key (str) –

  • value (Any) –

See

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html

Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.

Return type

None

add_override(path, value)

Adds an override to the synthesized CloudFormation resource.

To add a property override, either use addPropertyOverride or prefix path with “Properties.” (i.e. Properties.TopicName).

If the override is nested, separate each nested level using a dot (.) in the path parameter. If there is an array as part of the nesting, specify the index in the path.

To include a literal . in the property name, prefix with a \. In most programming languages you will need to write this as "\\." because the \ itself will need to be escaped.

For example:

cfn_resource.add_override("Properties.GlobalSecondaryIndexes.0.Projection.NonKeyAttributes", ["myattribute"])
cfn_resource.add_override("Properties.GlobalSecondaryIndexes.1.ProjectionType", "INCLUDE")

would add the overrides Example:

"Properties": {
   "GlobalSecondaryIndexes": [
     {
       "Projection": {
         "NonKeyAttributes": [ "myattribute" ]
         ...
       }
       ...
     },
     {
       "ProjectionType": "INCLUDE"
       ...
     },
   ]
   ...
}

The value argument to addOverride will not be processed or translated in any way. Pass raw JSON values in here with the correct capitalization for CloudFormation. If you pass CDK classes or structs, they will be rendered with lowercased key names, and CloudFormation will reject the template.

Parameters
  • path (str) –

    • The path of the property, you can use dot notation to override values in complex types. Any intermdediate keys will be created as needed.

  • value (Any) –

    • The value. Could be primitive or complex.

Return type

None

add_property_deletion_override(property_path)

Adds an override that deletes the value of a property from the resource definition.

Parameters

property_path (str) – The path to the property.

Return type

None

add_property_override(property_path, value)

Adds an override to a resource property.

Syntactic sugar for addOverride("Properties.<...>", value).

Parameters
  • property_path (str) – The path of the property.

  • value (Any) – The value.

Return type

None

apply_removal_policy(policy=None, *, apply_to_update_replace_policy=None, default=None)

Sets the deletion policy of the resource based on the removal policy specified.

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 (Optional[RemovalPolicy]) –

  • apply_to_update_replace_policy (Optional[bool]) – Apply the same deletion policy to the resource’s “UpdateReplacePolicy”. Default: true

  • default (Optional[RemovalPolicy]) – The default policy to apply in case the removal policy is not defined. Default: - Default value is resource specific. To determine the default value for a resoure, please consult that specific resource’s documentation.

Return type

None

get_att(attribute_name)

Returns a token for an runtime attribute of this resource.

Ideally, use generated attribute accessors (e.g. resource.arn), but this can be used for future compatibility in case there is no generated attribute.

Parameters

attribute_name (str) – The name of the attribute.

Return type

Reference

get_metadata(key)

Retrieve a value value from the CloudFormation Resource Metadata.

Parameters

key (str) –

See

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html

Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.

Return type

Any

inspect(inspector)

Examines the CloudFormation resource and discloses attributes.

Parameters

inspector (TreeInspector) –

  • tree inspector to collect and process attributes.

Return type

None

override_logical_id(new_logical_id)

Overrides the auto-generated logical ID with a specific ID.

Parameters

new_logical_id (str) – The new logical ID to use for this stack element.

Return type

None

to_string()

Returns a string representation of this construct.

Return type

str

Returns

a string representation of this resource

Attributes

CFN_RESOURCE_TYPE_NAME = 'AWS::LookoutEquipment::InferenceScheduler'
attr_inference_scheduler_arn

The Amazon Resource Name (ARN) of the inference scheduler being created.

CloudformationAttribute

InferenceSchedulerArn

Return type

str

cfn_options

Options for this resource, such as condition, update policy etc.

Return type

ICfnResourceOptions

cfn_resource_type

AWS resource type.

Return type

str

creation_stack

return:

the stack trace of the point where this Resource was created from, sourced from the +metadata+ entry typed +aws:cdk:logicalId+, and with the bottom-most node +internal+ entries filtered.

Return type

List[str]

data_delay_offset_in_minutes

A period of time (in minutes) by which inference on the data is delayed after the data starts.

For instance, if an offset delay time of five minutes was selected, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don’t need to stop and restart the scheduler when uploading new data.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html#cfn-lookoutequipment-inferencescheduler-datadelayoffsetinminutes

Return type

Union[int, float, None]

data_input_configuration

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html#cfn-lookoutequipment-inferencescheduler-datainputconfiguration

Return type

Any

data_output_configuration

Specifies configuration information for the output results for the inference scheduler, including the Amazon S3 location for the output.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html#cfn-lookoutequipment-inferencescheduler-dataoutputconfiguration

Return type

Any

data_upload_frequency

How often data is uploaded to the source S3 bucket for the input data.

This value is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html#cfn-lookoutequipment-inferencescheduler-datauploadfrequency

Return type

str

inference_scheduler_name

The name of the inference scheduler.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html#cfn-lookoutequipment-inferencescheduler-inferenceschedulername

Return type

Optional[str]

logical_id

The logical ID for this CloudFormation stack element.

The logical ID of the element is calculated from the path of the resource node in the construct tree.

To override this value, use overrideLogicalId(newLogicalId).

Return type

str

Returns

the logical ID as a stringified token. This value will only get resolved during synthesis.

model_name

The name of the ML model used for the inference scheduler.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html#cfn-lookoutequipment-inferencescheduler-modelname

Return type

str

node

The construct tree node associated with this construct.

Return type

ConstructNode

ref

Return a string that will be resolved to a CloudFormation { Ref } for this element.

If, by any chance, the intrinsic reference of a resource is not a string, you could coerce it to an IResolvable through Lazy.any({ produce: resource.ref }).

Return type

str

role_arn

The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html#cfn-lookoutequipment-inferencescheduler-rolearn

Return type

str

server_side_kms_key_id

Provides the identifier of the AWS KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment .

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html#cfn-lookoutequipment-inferencescheduler-serversidekmskeyid

Return type

Optional[str]

stack

The stack in which this element is defined.

CfnElements must be defined within a stack scope (directly or indirectly).

Return type

Stack

tags

Any tags associated with the inference scheduler.

For more information, see Tag .

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html#cfn-lookoutequipment-inferencescheduler-tags

Return type

TagManager

Static Methods

classmethod is_cfn_element(x)

Returns true if a construct is a stack element (i.e. part of the synthesized cloudformation template).

Uses duck-typing instead of instanceof to allow stack elements from different versions of this library to be included in the same stack.

Parameters

x (Any) –

Return type

bool

Returns

The construct as a stack element or undefined if it is not a stack element.

classmethod is_cfn_resource(construct)

Check whether the given construct is a CfnResource.

Parameters

construct (IConstruct) –

Return type

bool

classmethod is_construct(x)

Return whether the given object is a Construct.

Parameters

x (Any) –

Return type

bool