Amazon SageMaker Sagemaker Data Quality Job Definition API
The Sagemaker Data Quality Job Definition API from Amazon SageMaker — 4 operation(s) for sagemaker data quality job definition.
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OpenAPI Specification
openapi: 3.1.0
info:
title: Amazon SageMaker Service Data Quality Job Definition API
version: '2017-07-24'
description: Generated from AWS's published Smithy model for Amazon SageMaker Service. 4 operation(s).
contact:
name: Amazon Web Services
url: https://aws.amazon.com/contact-us/
license:
name: Apache 2.0
identifier: Apache-2.0
url: https://github.com/aws/api-models-aws/blob/main/LICENSE
servers:
- url: https://api.sagemaker.{region}.amazonaws.com
variables:
region:
default: us-east-1
security:
- sigv4: []
paths:
/#CreateDataQualityJobDefinition:
post:
operationId: CreateDataQualityJobDefinition
summary: Create Data Quality Job Definition
description: Creates a definition for a job that monitors data quality and drift. For information about model monitor,
see Amazon SageMaker AI Model Monitor.
responses:
'200':
description: Success
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/CreateDataQualityJobDefinitionResponse'
'400':
description: ResourceInUse; ResourceLimitExceeded
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/ResourceInUse'
parameters:
- name: X-Amz-Target
in: header
required: true
schema:
type: string
enum:
- SageMaker.CreateDataQualityJobDefinition
requestBody:
required: true
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/CreateDataQualityJobDefinitionRequest'
tags:
- Data Quality Job Definition
/#DeleteDataQualityJobDefinition:
post:
operationId: DeleteDataQualityJobDefinition
summary: Delete Data Quality Job Definition
description: Deletes a data quality monitoring job definition.
responses:
'200':
description: Success
content:
application/x-amz-json-1.1:
schema:
type: string
'400':
description: ResourceNotFound
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/ResourceNotFound'
parameters:
- name: X-Amz-Target
in: header
required: true
schema:
type: string
enum:
- SageMaker.DeleteDataQualityJobDefinition
requestBody:
required: true
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/DeleteDataQualityJobDefinitionRequest'
tags:
- Data Quality Job Definition
/#DescribeDataQualityJobDefinition:
post:
operationId: DescribeDataQualityJobDefinition
summary: Describe Data Quality Job Definition
description: Gets the details of a data quality monitoring job definition.
responses:
'200':
description: Success
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/DescribeDataQualityJobDefinitionResponse'
'400':
description: ResourceNotFound
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/ResourceNotFound'
parameters:
- name: X-Amz-Target
in: header
required: true
schema:
type: string
enum:
- SageMaker.DescribeDataQualityJobDefinition
requestBody:
required: true
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/DescribeDataQualityJobDefinitionRequest'
tags:
- Data Quality Job Definition
/#ListDataQualityJobDefinitions:
post:
operationId: ListDataQualityJobDefinitions
summary: List Data Quality Job Definitions
description: Lists the data quality job definitions in your account.
responses:
'200':
description: Success
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/ListDataQualityJobDefinitionsResponse'
parameters:
- name: X-Amz-Target
in: header
required: true
schema:
type: string
enum:
- SageMaker.ListDataQualityJobDefinitions
requestBody:
required: true
content:
application/x-amz-json-1.1:
schema:
$ref: '#/components/schemas/ListDataQualityJobDefinitionsRequest'
tags:
- Data Quality Job Definition
components:
securitySchemes:
sigv4:
type: apiKey
in: header
name: Authorization
description: AWS Signature Version 4. The Authorization header carries an AWS4-HMAC-SHA256 signature over the canonical
request, with X-Amz-Date (and X-Amz-Security-Token for temporary credentials). Not a bearer token.
x-aws-sigv4:
signingName: sagemaker
schemas:
BatchTransformInput:
type: object
properties:
DataCapturedDestinationS3Uri:
type: string
description: The Amazon S3 location being used to capture the data.
DatasetFormat:
$ref: '#/components/schemas/MonitoringDatasetFormat'
LocalPath:
type: string
description: Path to the filesystem where the batch transform data is available to the container.
S3InputMode:
type: string
enum:
- Pipe
- File
description: Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe
mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
S3DataDistributionType:
type: string
enum:
- FullyReplicated
- ShardedByS3Key
description: Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to
FullyReplicated
FeaturesAttribute:
type: string
description: The attributes of the input data that are the input features.
InferenceAttribute:
type: string
description: The attribute of the input data that represents the ground truth label.
ProbabilityAttribute:
type: string
description: In a classification problem, the attribute that represents the class probability.
ProbabilityThresholdAttribute:
type: number
description: The threshold for the class probability to be evaluated as a positive result.
StartTimeOffset:
type: string
description: If specified, monitoring jobs substract this time from the start time. For information about using
offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
EndTimeOffset:
type: string
description: If specified, monitoring jobs subtract this time from the end time. For information about using offsets
for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
ExcludeFeaturesAttribute:
type: string
description: The attributes of the input data to exclude from the analysis.
required:
- DataCapturedDestinationS3Uri
- DatasetFormat
- LocalPath
CreateDataQualityJobDefinitionRequest:
type: object
properties:
JobDefinitionName:
type: string
description: The name for the monitoring job definition.
DataQualityBaselineConfig:
$ref: '#/components/schemas/DataQualityBaselineConfig'
DataQualityAppSpecification:
$ref: '#/components/schemas/DataQualityAppSpecification'
DataQualityJobInput:
$ref: '#/components/schemas/DataQualityJobInput'
DataQualityJobOutputConfig:
$ref: '#/components/schemas/MonitoringOutputConfig'
JobResources:
$ref: '#/components/schemas/MonitoringResources'
NetworkConfig:
$ref: '#/components/schemas/MonitoringNetworkConfig'
RoleArn:
type: string
description: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks
on your behalf.
StoppingCondition:
$ref: '#/components/schemas/MonitoringStoppingCondition'
Tags:
type: array
items:
$ref: '#/components/schemas/Tag'
description: (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the
Amazon Web Services Billing and Cost Management User Guide.
required:
- JobDefinitionName
- DataQualityAppSpecification
- DataQualityJobInput
- DataQualityJobOutputConfig
- JobResources
- RoleArn
CreateDataQualityJobDefinitionResponse:
type: object
properties:
JobDefinitionArn:
type: string
description: The Amazon Resource Name (ARN) of the job definition.
required:
- JobDefinitionArn
DataQualityAppSpecification:
type: object
properties:
ImageUri:
type: string
description: The container image that the data quality monitoring job runs.
ContainerEntrypoint:
type: array
items:
type: string
description: The entrypoint for a container used to run a monitoring job.
ContainerArguments:
type: array
items:
type: string
description: The arguments to send to the container that the monitoring job runs.
RecordPreprocessorSourceUri:
type: string
description: An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode
the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable
only for the built-in (first party) containers.
PostAnalyticsProcessorSourceUri:
type: string
description: An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for
the built-in (first party) containers.
Environment:
type: object
additionalProperties:
type: string
description: Sets the environment variables in the container that the monitoring job runs.
required:
- ImageUri
DataQualityBaselineConfig:
type: object
properties:
BaseliningJobName:
type: string
description: The name of the job that performs baselining for the data quality monitoring job.
ConstraintsResource:
$ref: '#/components/schemas/MonitoringConstraintsResource'
StatisticsResource:
$ref: '#/components/schemas/MonitoringStatisticsResource'
DataQualityJobInput:
type: object
properties:
EndpointInput:
$ref: '#/components/schemas/EndpointInput'
BatchTransformInput:
$ref: '#/components/schemas/BatchTransformInput'
DeleteDataQualityJobDefinitionRequest:
type: object
properties:
JobDefinitionName:
type: string
description: The name of the data quality monitoring job definition to delete.
required:
- JobDefinitionName
DescribeDataQualityJobDefinitionRequest:
type: object
properties:
JobDefinitionName:
type: string
description: The name of the data quality monitoring job definition to describe.
required:
- JobDefinitionName
DescribeDataQualityJobDefinitionResponse:
type: object
properties:
JobDefinitionArn:
type: string
description: The Amazon Resource Name (ARN) of the data quality monitoring job definition.
JobDefinitionName:
type: string
description: The name of the data quality monitoring job definition.
CreationTime:
type: string
format: date-time
description: The time that the data quality monitoring job definition was created.
DataQualityBaselineConfig:
$ref: '#/components/schemas/DataQualityBaselineConfig'
DataQualityAppSpecification:
$ref: '#/components/schemas/DataQualityAppSpecification'
DataQualityJobInput:
$ref: '#/components/schemas/DataQualityJobInput'
DataQualityJobOutputConfig:
$ref: '#/components/schemas/MonitoringOutputConfig'
JobResources:
$ref: '#/components/schemas/MonitoringResources'
NetworkConfig:
$ref: '#/components/schemas/MonitoringNetworkConfig'
RoleArn:
type: string
description: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks
on your behalf.
StoppingCondition:
$ref: '#/components/schemas/MonitoringStoppingCondition'
required:
- JobDefinitionArn
- JobDefinitionName
- CreationTime
- DataQualityAppSpecification
- DataQualityJobInput
- DataQualityJobOutputConfig
- JobResources
- RoleArn
EndpointInput:
type: object
properties:
EndpointName:
type: string
description: An endpoint in customer's account which has enabled DataCaptureConfig enabled.
LocalPath:
type: string
description: Path to the filesystem where the endpoint data is available to the container.
S3InputMode:
type: string
enum:
- Pipe
- File
description: Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe
mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
S3DataDistributionType:
type: string
enum:
- FullyReplicated
- ShardedByS3Key
description: Whether input data distributed in Amazon S3 is fully replicated or sharded by an Amazon S3 key. Defaults
to FullyReplicated
FeaturesAttribute:
type: string
description: The attributes of the input data that are the input features.
InferenceAttribute:
type: string
description: The attribute of the input data that represents the ground truth label.
ProbabilityAttribute:
type: string
description: In a classification problem, the attribute that represents the class probability.
ProbabilityThresholdAttribute:
type: number
description: The threshold for the class probability to be evaluated as a positive result.
StartTimeOffset:
type: string
description: If specified, monitoring jobs substract this time from the start time. For information about using
offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
EndTimeOffset:
type: string
description: If specified, monitoring jobs substract this time from the end time. For information about using offsets
for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
ExcludeFeaturesAttribute:
type: string
description: The attributes of the input data to exclude from the analysis.
required:
- EndpointName
- LocalPath
ListDataQualityJobDefinitionsRequest:
type: object
properties:
EndpointName:
type: string
description: A filter that lists the data quality job definitions associated with the specified endpoint.
SortBy:
type: string
enum:
- Name
- CreationTime
description: The field to sort results by. The default is CreationTime.
SortOrder:
type: string
enum:
- Ascending
- Descending
description: Whether to sort the results in Ascending or Descending order. The default is Descending.
NextToken:
type: string
description: If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes
a NextToken. To retrieve the next set of transform jobs, use the token in the next request.>
MaxResults:
type: integer
description: The maximum number of data quality monitoring job definitions to return in the response.
NameContains:
type: string
description: A string in the data quality monitoring job definition name. This filter returns only data quality
monitoring job definitions whose name contains the specified string.
CreationTimeBefore:
type: string
format: date-time
description: A filter that returns only data quality monitoring job definitions created before the specified time.
CreationTimeAfter:
type: string
format: date-time
description: A filter that returns only data quality monitoring job definitions created after the specified time.
ListDataQualityJobDefinitionsResponse:
type: object
properties:
JobDefinitionSummaries:
type: array
items:
$ref: '#/components/schemas/MonitoringJobDefinitionSummary'
description: A list of data quality monitoring job definitions.
NextToken:
type: string
description: If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes
a NextToken. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.
required:
- JobDefinitionSummaries
MonitoringClusterConfig:
type: object
properties:
InstanceCount:
type: integer
description: The number of ML compute instances to use in the model monitoring job. For distributed processing jobs,
specify a value greater than 1. The default value is 1.
InstanceType:
type: string
enum:
- ml.t3.medium
- ml.t3.large
- ml.t3.xlarge
- ml.t3.2xlarge
- ml.m4.xlarge
- ml.m4.2xlarge
- ml.m4.4xlarge
- ml.m4.10xlarge
- ml.m4.16xlarge
- ml.c4.xlarge
- ml.c4.2xlarge
- ml.c4.4xlarge
- ml.c4.8xlarge
- ml.p2.xlarge
- ml.p2.8xlarge
- ml.p2.16xlarge
- ml.p3.2xlarge
- ml.p3.8xlarge
- ml.p3.16xlarge
- ml.c5.xlarge
- ml.c5.2xlarge
- ml.c5.4xlarge
- ml.c5.9xlarge
- ml.c5.18xlarge
- ml.m5.large
- ml.m5.xlarge
- ml.m5.2xlarge
- ml.m5.4xlarge
- ml.m5.12xlarge
- ml.m5.24xlarge
- ml.r5.large
- ml.r5.xlarge
- ml.r5.2xlarge
- ml.r5.4xlarge
- ml.r5.8xlarge
- ml.r5.12xlarge
- ml.r5.16xlarge
- ml.r5.24xlarge
- ml.g4dn.xlarge
- ml.g4dn.2xlarge
- ml.g4dn.4xlarge
- ml.g4dn.8xlarge
- ml.g4dn.12xlarge
- ml.g4dn.16xlarge
- ml.g5.xlarge
- ml.g5.2xlarge
- ml.g5.4xlarge
- ml.g5.8xlarge
- ml.g5.16xlarge
- ml.g5.12xlarge
- ml.g5.24xlarge
- ml.g5.48xlarge
- ml.r5d.large
- ml.r5d.xlarge
- ml.r5d.2xlarge
- ml.r5d.4xlarge
- ml.r5d.8xlarge
- ml.r5d.12xlarge
- ml.r5d.16xlarge
- ml.r5d.24xlarge
- ml.g6.xlarge
- ml.g6.2xlarge
- ml.g6.4xlarge
- ml.g6.8xlarge
- ml.g6.12xlarge
- ml.g6.16xlarge
- ml.g6.24xlarge
- ml.g6.48xlarge
- ml.g6e.xlarge
- ml.g6e.2xlarge
- ml.g6e.4xlarge
- ml.g6e.8xlarge
- ml.g6e.12xlarge
- ml.g6e.16xlarge
- ml.g6e.24xlarge
- ml.g6e.48xlarge
- ml.m6i.large
- ml.m6i.xlarge
- ml.m6i.2xlarge
- ml.m6i.4xlarge
- ml.m6i.8xlarge
- ml.m6i.12xlarge
- ml.m6i.16xlarge
- ml.m6i.24xlarge
- ml.m6i.32xlarge
- ml.c6i.xlarge
- ml.c6i.2xlarge
- ml.c6i.4xlarge
- ml.c6i.8xlarge
- ml.c6i.12xlarge
- ml.c6i.16xlarge
- ml.c6i.24xlarge
- ml.c6i.32xlarge
- ml.m7i.large
- ml.m7i.xlarge
- ml.m7i.2xlarge
- ml.m7i.4xlarge
- ml.m7i.8xlarge
- ml.m7i.12xlarge
- ml.m7i.16xlarge
- ml.m7i.24xlarge
- ml.m7i.48xlarge
- ml.c7i.large
- ml.c7i.xlarge
- ml.c7i.2xlarge
- ml.c7i.4xlarge
- ml.c7i.8xlarge
- ml.c7i.12xlarge
- ml.c7i.16xlarge
- ml.c7i.24xlarge
- ml.c7i.48xlarge
- ml.r7i.large
- ml.r7i.xlarge
- ml.r7i.2xlarge
- ml.r7i.4xlarge
- ml.r7i.8xlarge
- ml.r7i.12xlarge
- ml.r7i.16xlarge
- ml.r7i.24xlarge
- ml.r7i.48xlarge
- ml.p5.4xlarge
- ml.g7e.2xlarge
- ml.g7e.4xlarge
- ml.g7e.8xlarge
- ml.g7e.12xlarge
- ml.g7e.24xlarge
- ml.g7e.48xlarge
- ml.g7.2xlarge
- ml.g7.4xlarge
- ml.g7.8xlarge
- ml.g7.12xlarge
- ml.g7.24xlarge
- ml.g7.48xlarge
- ml.r6i.large
- ml.r6i.xlarge
- ml.r6i.2xlarge
- ml.r6i.4xlarge
- ml.r6i.8xlarge
- ml.r6i.12xlarge
- ml.r6i.16xlarge
- ml.r6i.24xlarge
- ml.r6i.32xlarge
- ml.m8i.large
- ml.m8i.xlarge
- ml.m8i.2xlarge
- ml.m8i.4xlarge
- ml.m8i.8xlarge
- ml.m8i.12xlarge
- ml.m8i.16xlarge
- ml.m8i.24xlarge
- ml.m8i.32xlarge
- ml.m8i.48xlarge
- ml.m8i.96xlarge
- ml.c8i.xlarge
- ml.c8i.2xlarge
- ml.c8i.4xlarge
- ml.c8i.8xlarge
- ml.c8i.12xlarge
- ml.c8i.16xlarge
- ml.c8i.24xlarge
- ml.c8i.32xlarge
- ml.c8i.48xlarge
- ml.c8i.96xlarge
- ml.r8i.large
- ml.r8i.xlarge
- ml.r8i.2xlarge
- ml.r8i.4xlarge
- ml.r8i.8xlarge
- ml.r8i.12xlarge
- ml.r8i.16xlarge
- ml.r8i.24xlarge
- ml.r8i.32xlarge
- ml.r8i.48xlarge
- ml.r8i.96xlarge
- ml.m7i-flex.large
- ml.m7i-flex.xlarge
- ml.m7i-flex.2xlarge
- ml.m7i-flex.4xlarge
- ml.m7i-flex.8xlarge
- ml.m7i-flex.12xlarge
- ml.m7i-flex.16xlarge
- ml.c7i-flex.xlarge
- ml.c7i-flex.2xlarge
- ml.c7i-flex.4xlarge
- ml.c7i-flex.8xlarge
- ml.c7i-flex.12xlarge
- ml.c7i-flex.16xlarge
- ml.m8i-flex.large
- ml.m8i-flex.xlarge
- ml.m8i-flex.2xlarge
- ml.m8i-flex.4xlarge
- ml.m8i-flex.8xlarge
- ml.m8i-flex.12xlarge
- ml.m8i-flex.16xlarge
- ml.c8i-flex.xlarge
- ml.c8i-flex.2xlarge
- ml.c8i-flex.4xlarge
- ml.c8i-flex.8xlarge
- ml.c8i-flex.12xlarge
- ml.c8i-flex.16xlarge
- ml.r8i-flex.large
- ml.r8i-flex.xlarge
- ml.r8i-flex.2xlarge
- ml.r8i-flex.4xlarge
- ml.r8i-flex.8xlarge
- ml.r8i-flex.12xlarge
- ml.r8i-flex.16xlarge
description: The ML compute instance type for the processing job.
VolumeSizeInGB:
type: integer
description: The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient
ML storage for your scenario.
VolumeKmsKeyId:
type: string
description: The Key Management Service (KMS) key that Amazon SageMaker AI uses to encrypt data on the storage volume
attached to the ML compute instance(s) that run the model monitoring job.
required:
- InstanceCount
- InstanceType
- VolumeSizeInGB
MonitoringConstraintsResource:
type: object
properties:
S3Uri:
type: string
description: The Amazon S3 URI for the constraints resource.
MonitoringCsvDatasetFormat:
type: object
properties:
Header:
type: boolean
description: Indicates if the CSV data has a header.
MonitoringDatasetFormat:
type: object
properties:
Csv:
$ref: '#/components/schemas/MonitoringCsvDatasetFormat'
Json:
$ref: '#/components/schemas/MonitoringJsonDatasetFormat'
Parquet:
$ref: '#/components/schemas/MonitoringParquetDatasetFormat'
MonitoringJobDefinitionSummary:
type: object
properties:
MonitoringJobDefinitionName:
type: string
description: The name of the monitoring job.
MonitoringJobDefinitionArn:
type: string
description: The Amazon Resource Name (ARN) of the monitoring job.
CreationTime:
type: string
format: date-time
description: The time that the monitoring job was created.
EndpointName:
type: string
description: The name of the endpoint that the job monitors.
required:
- MonitoringJobDefinitionName
- MonitoringJobDefinitionArn
- CreationTime
- EndpointName
MonitoringJsonDatasetFormat:
type: object
properties:
Line:
type: boolean
description: Indicates if the file should be read as a JSON object per line.
MonitoringNetworkConfig:
type: object
properties:
EnableInterContainerTrafficEncryption:
type: boolean
description: Whether to encrypt all communications between the instances used for the monitoring jobs. Choose True
to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might
take longer.
EnableNetworkIsolation:
type: boolean
description: Whether to allow inbound and outbound network calls to and from the containers used for the monitoring
job.
VpcConfig:
$ref: '#/components/schemas/VpcConfig'
MonitoringOutput:
type: object
properties:
S3Output:
$ref: '#/components/schemas/MonitoringS3Output'
required:
- S3Output
MonitoringOutputConfig:
type: object
properties:
MonitoringOutputs:
type: array
items:
$ref: '#/components/schemas/MonitoringOutput'
description: Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is
uploaded.
KmsKeyId:
type: string
description: The Key Management Service (KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at
rest using Amazon S3 server-side encryption.
required:
- MonitoringOutputs
MonitoringParquetDatasetFormat:
type: object
properties: {}
MonitoringResources:
type: object
properties:
ClusterConfig:
$ref: '#/components/schemas/MonitoringClusterConfig'
required:
- ClusterConfig
MonitoringS3Output:
type: object
properties:
S3Uri:
type: string
description: A URI that identifies the Amazon S3 storage location where Amazon SageMaker AI saves the results of
a monitoring job.
LocalPath:
type: string
description: The local path to the Amazon S3 storage location where Amazon SageMaker AI saves the results of a monitoring
job. LocalPath is an absolute path for the output data.
S3UploadMode:
type: string
enum:
- Continuous
- EndOfJob
description: Whether to upload the results of the monitoring job continuously or after the job completes.
required:
- S3Uri
- LocalPath
MonitoringStatisticsResource:
type: object
properties:
S3Uri:
type: string
description: The Amazon S3 URI for the statistics resource.
MonitoringStoppingCondition:
type: object
properties:
MaxRuntimeInSeconds:
type: integer
description: The maximum runtime allowed in seconds. The MaxRuntimeInSeconds cannot exceed the frequency of the
job. For data quality and model explainability, this can be up to 3600 seconds for an hourly schedule. For model
bias and model quality hourly schedules, this can be up to 1800 seconds.
required:
- MaxRuntimeInSeconds
ResourceInUse:
type: object
properties:
Message:
type: string
ResourceNotFound:
type: object
properties:
Message:
type: string
Tag:
type: object
properties:
Key:
type: string
description: The tag key. Tag keys must be unique per resource.
Value:
type: string
description: The tag value.
required:
- Key
- Value
VpcConfig:
type: object
properties:
SecurityGroupIds:
type: array
items:
type: string
description: The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is
specified in the Subnets field.
Subnets:
type: array
items:
type: string
description: The ID of the subnets in the VPC to which you want to connect your training job or model. For information
about the availability of specific instance types, see Supported Instance Types and Availability Zones.
required:
- SecurityGroupIds
- Subnets
x-provenance:
method: harvested
publisher: Amazon Web Services
source: https://raw.githubusercontent.com/aws/api-models-aws/582e55931c45b944739742a2c1620b6026dd2d13/models/sagemaker/service/2017-07-24/sagemaker-2017-07-24.json
note: converted by smithy-to-openapi.py from AWS's Smithy model (roadmap#1001)