CfnInferenceComponentProps

class aws_cdk.aws_sagemaker.CfnInferenceComponentProps(*, endpoint_name, specification, deployment_config=None, endpoint_arn=None, inference_component_name=None, runtime_config=None, tags=None, variant_name=None)

Bases: object

Properties for defining a CfnInferenceComponent.

Parameters:

endpoint_name (str) – The name of the endpoint that hosts the inference component.
specification (Union[IResolvable, InferenceComponentSpecificationProperty, Dict[str, Any]]) – The specification for the inference component.
deployment_config (Union[IResolvable, InferenceComponentDeploymentConfigProperty, Dict[str, Any], None]) – The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
endpoint_arn (Optional[str]) – The Amazon Resource Name (ARN) of the endpoint that hosts the inference component.
inference_component_name (Optional[str]) – The name of the inference component.
runtime_config (Union[IResolvable, InferenceComponentRuntimeConfigProperty, Dict[str, Any], None]) – The runtime config for the inference component.
tags (Optional[Sequence[Union[CfnTag, Dict[str, Any]]]]) – An array of tags to apply to the resource.
variant_name (Optional[str]) – The name of the production variant that hosts the inference component.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-inferencecomponent.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_sagemaker as sagemaker

cfn_inference_component_props = sagemaker.CfnInferenceComponentProps(
    endpoint_name="endpointName",
    specification=sagemaker.CfnInferenceComponent.InferenceComponentSpecificationProperty(
        base_inference_component_name="baseInferenceComponentName",
        compute_resource_requirements=sagemaker.CfnInferenceComponent.InferenceComponentComputeResourceRequirementsProperty(
            max_memory_required_in_mb=123,
            min_memory_required_in_mb=123,
            number_of_accelerator_devices_required=123,
            number_of_cpu_cores_required=123
        ),
        container=sagemaker.CfnInferenceComponent.InferenceComponentContainerSpecificationProperty(
            artifact_url="artifactUrl",
            deployed_image=sagemaker.CfnInferenceComponent.DeployedImageProperty(
                resolution_time="resolutionTime",
                resolved_image="resolvedImage",
                specified_image="specifiedImage"
            ),
            environment={
                "environment_key": "environment"
            },
            image="image"
        ),
        model_name="modelName",
        startup_parameters=sagemaker.CfnInferenceComponent.InferenceComponentStartupParametersProperty(
            container_startup_health_check_timeout_in_seconds=123,
            model_data_download_timeout_in_seconds=123
        )
    ),

    # the properties below are optional
    deployment_config=sagemaker.CfnInferenceComponent.InferenceComponentDeploymentConfigProperty(
        auto_rollback_configuration=sagemaker.CfnInferenceComponent.AutoRollbackConfigurationProperty(
            alarms=[sagemaker.CfnInferenceComponent.AlarmProperty(
                alarm_name="alarmName"
            )]
        ),
        rolling_update_policy=sagemaker.CfnInferenceComponent.InferenceComponentRollingUpdatePolicyProperty(
            maximum_batch_size=sagemaker.CfnInferenceComponent.InferenceComponentCapacitySizeProperty(
                type="type",
                value=123
            ),
            maximum_execution_timeout_in_seconds=123,
            rollback_maximum_batch_size=sagemaker.CfnInferenceComponent.InferenceComponentCapacitySizeProperty(
                type="type",
                value=123
            ),
            wait_interval_in_seconds=123
        )
    ),
    endpoint_arn="endpointArn",
    inference_component_name="inferenceComponentName",
    runtime_config=sagemaker.CfnInferenceComponent.InferenceComponentRuntimeConfigProperty(
        copy_count=123,
        current_copy_count=123,
        desired_copy_count=123
    ),
    tags=[CfnTag(
        key="key",
        value="value"
    )],
    variant_name="variantName"
)