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: CfnResource

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.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-lookoutequipment-inferencescheduler.html
CloudformationResource:: AWS::LookoutEquipment::InferenceScheduler
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import 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"
    )]
)

Parameters:

scope (Construct) – Scope in which this resource is defined.
id (str) – Construct identifier for this resource (unique in its scope).
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 machine learning 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[Union[CfnTag, Dict[str, Any]]]]) – 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_dependency(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_depends_on(target)

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

Parameters:

target (CfnResource) –

Deprecated:

use addDependency

Stability:

deprecated

Return type:

None

add_metadata(key, value)

Add a value to the CloudFormation Resource Metadata.

Parameters:

key (str) –
value (Any) –

See:

Return type:

None

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.

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 intermediate 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). In some cases, a snapshot can be taken of the resource prior to deletion (RemovalPolicy.SNAPSHOT). A list of resources that support this policy can be found in the following link:

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 resource, please consult that specific resource’s documentation.

See:

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-attribute-deletionpolicy.html#aws-attribute-deletionpolicy-options

Return type:

None

get_att(attribute_name, type_hint=None)

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.
type_hint (Optional[ResolutionTypeHint]) –

Return type:

Reference

get_metadata(key)

Retrieve a value value from the CloudFormation Resource Metadata.

Parameters:

key (str) –

See:

Return type:

Any

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.

inspect(inspector)

Examines the CloudFormation resource and discloses attributes.

Parameters:: inspector (TreeInspector) – tree inspector to collect and process attributes.
Return type:: None

obtain_dependencies()

Retrieves an array of resources this resource depends on.

This assembles dependencies on resources across stacks (including nested stacks) automatically.

Return type:: List[Union[Stack, CfnResource]]

obtain_resource_dependencies()

Get a shallow copy of dependencies between this resource and other resources in the same stack.

Return type:: List[CfnResource]

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

remove_dependency(target)

Indicates that this resource no longer depends on another resource.

This can be used for resources across stacks (including nested stacks) and the dependency will automatically be removed from the relevant scope.

Parameters:

target (CfnResource) –

Return type:

None

replace_dependency(target, new_target)

Replaces one dependency with another.

Parameters:

target (CfnResource) – The dependency to replace.
new_target (CfnResource) – The new dependency to add.

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

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

cfn_resource_type: AWS resource type.

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.

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

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

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

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

inference_scheduler_name: The name of the inference scheduler.

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).

Returns:

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

model_name: The name of the machine learning model used for the inference scheduler.

node: The tree node.

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 }).

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

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

stack

The stack in which this element is defined.

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

tags: Tag Manager which manages the tags for this resource.

tags_raw: Any tags associated with the inference scheduler.

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(x)

Check whether the given object is a CfnResource.

Parameters:

x (Any) –

Return type:

bool

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.

DataInputConfigurationProperty

class CfnInferenceScheduler.DataInputConfigurationProperty(*, s3_input_configuration, inference_input_name_configuration=None, input_time_zone_offset=None)

Bases: object

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

Parameters:

s3_input_configuration (Union[IResolvable, S3InputConfigurationProperty, Dict[str, Any]]) – Specifies configuration information for the input data for the inference, including input data S3 location.
inference_input_name_configuration (Union[IResolvable, InputNameConfigurationProperty, Dict[str, Any], None]) – Specifies configuration information for the input data for the inference, including timestamp format and delimiter.
input_time_zone_offset (Optional[str]) – Indicates the difference between your time zone and Greenwich Mean Time (GMT).

See:

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

ExampleMetadata:

fixture=_generated

Example:

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

data_input_configuration_property = lookoutequipment.CfnInferenceScheduler.DataInputConfigurationProperty(
    s3_input_configuration=lookoutequipment.CfnInferenceScheduler.S3InputConfigurationProperty(
        bucket="bucket",

        # the properties below are optional
        prefix="prefix"
    ),

    # the properties below are optional
    inference_input_name_configuration=lookoutequipment.CfnInferenceScheduler.InputNameConfigurationProperty(
        component_timestamp_delimiter="componentTimestampDelimiter",
        timestamp_format="timestampFormat"
    ),
    input_time_zone_offset="inputTimeZoneOffset"
)

Attributes

inference_input_name_configuration

Specifies configuration information for the input data for the inference, including timestamp format and delimiter.

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

input_time_zone_offset

Indicates the difference between your time zone and Greenwich Mean Time (GMT).

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

s3_input_configuration

Specifies configuration information for the input data for the inference, including input data S3 location.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-datainputconfiguration.html#cfn-lookoutequipment-inferencescheduler-datainputconfiguration-s3inputconfiguration

DataOutputConfigurationProperty

class CfnInferenceScheduler.DataOutputConfigurationProperty(*, s3_output_configuration, kms_key_id=None)

Bases: object

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

Parameters:

s3_output_configuration (Union[IResolvable, S3OutputConfigurationProperty, Dict[str, Any]]) – Specifies configuration information for the output results from the inference, including output S3 location.
kms_key_id (Optional[str]) – The ID number for the AWS KMS key used to encrypt the inference output.

See:

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

ExampleMetadata:

fixture=_generated

Example:

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

data_output_configuration_property = lookoutequipment.CfnInferenceScheduler.DataOutputConfigurationProperty(
    s3_output_configuration=lookoutequipment.CfnInferenceScheduler.S3OutputConfigurationProperty(
        bucket="bucket",

        # the properties below are optional
        prefix="prefix"
    ),

    # the properties below are optional
    kms_key_id="kmsKeyId"
)

Attributes

kms_key_id

The ID number for the AWS KMS key used to encrypt the inference output.

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

s3_output_configuration

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

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-dataoutputconfiguration.html#cfn-lookoutequipment-inferencescheduler-dataoutputconfiguration-s3outputconfiguration

InputNameConfigurationProperty

class CfnInferenceScheduler.InputNameConfigurationProperty(*, component_timestamp_delimiter=None, timestamp_format=None)

Bases: object

Specifies configuration information for the input data for the inference, including timestamp format and delimiter.

Parameters:

component_timestamp_delimiter (Optional[str]) – Indicates the delimiter character used between items in the data.
timestamp_format (Optional[str]) – The format of the timestamp, whether Epoch time, or standard, with or without hyphens (-).

See:

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

ExampleMetadata:

fixture=_generated

Example:

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

input_name_configuration_property = lookoutequipment.CfnInferenceScheduler.InputNameConfigurationProperty(
    component_timestamp_delimiter="componentTimestampDelimiter",
    timestamp_format="timestampFormat"
)

Attributes

component_timestamp_delimiter

Indicates the delimiter character used between items in the data.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-inputnameconfiguration.html#cfn-lookoutequipment-inferencescheduler-inputnameconfiguration-componenttimestampdelimiter

timestamp_format

The format of the timestamp, whether Epoch time, or standard, with or without hyphens (-).

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-inputnameconfiguration.html#cfn-lookoutequipment-inferencescheduler-inputnameconfiguration-timestampformat

S3InputConfigurationProperty

class CfnInferenceScheduler.S3InputConfigurationProperty(*, bucket, prefix=None)

Bases: object

Specifies configuration information for the input data for the inference, including input data S3 location.

Parameters:

bucket (str) –
prefix (Optional[str]) –

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-s3inputconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

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

s3_input_configuration_property = lookoutequipment.CfnInferenceScheduler.S3InputConfigurationProperty(
    bucket="bucket",

    # the properties below are optional
    prefix="prefix"
)

Attributes

bucket

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-s3inputconfiguration.html#cfn-lookoutequipment-inferencescheduler-s3inputconfiguration-bucket

Type:: see

prefix

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-s3inputconfiguration.html#cfn-lookoutequipment-inferencescheduler-s3inputconfiguration-prefix

Type:: see

S3OutputConfigurationProperty

class CfnInferenceScheduler.S3OutputConfigurationProperty(*, bucket, prefix=None)

Bases: object

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

Parameters:

bucket (str) –
prefix (Optional[str]) –

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-s3outputconfiguration.html

ExampleMetadata:

fixture=_generated

Example:

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

s3_output_configuration_property = lookoutequipment.CfnInferenceScheduler.S3OutputConfigurationProperty(
    bucket="bucket",

    # the properties below are optional
    prefix="prefix"
)

Attributes

bucket

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-s3outputconfiguration.html#cfn-lookoutequipment-inferencescheduler-s3outputconfiguration-bucket

Type:: see

prefix

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lookoutequipment-inferencescheduler-s3outputconfiguration.html#cfn-lookoutequipment-inferencescheduler-s3outputconfiguration-prefix

Type:: see