SageMaker / Client / describe_ai_benchmark_job

describe_ai_benchmark_job¶

SageMaker.Client.describe_ai_benchmark_job(**kwargs)¶

Returns details of an AI benchmark job, including its status, configuration, target endpoint, and timing information.

Request Syntax

response = client.describe_ai_benchmark_job(
    AIBenchmarkJobName='string'
)

Parameters:

AIBenchmarkJobName (string) –

[REQUIRED]

The name of the AI benchmark job to describe.

Return type:

dict

Returns:

Response Syntax

{
    'AIBenchmarkJobName': 'string',
    'AIBenchmarkJobArn': 'string',
    'AIBenchmarkJobStatus': 'InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped',
    'FailureReason': 'string',
    'BenchmarkTarget': {
        'Endpoint': {
            'Identifier': 'string',
            'TargetContainerHostname': 'string',
            'InferenceComponents': [
                {
                    'Identifier': 'string'
                },
            ]
        }
    },
    'OutputConfig': {
        'S3OutputLocation': 'string',
        'CloudWatchLogs': [
            {
                'LogGroupArn': 'string',
                'LogStreamName': 'string'
            },
        ]
    },
    'AIWorkloadConfigIdentifier': 'string',
    'RoleArn': 'string',
    'NetworkConfig': {
        'VpcConfig': {
            'SecurityGroupIds': [
                'string',
            ],
            'Subnets': [
                'string',
            ]
        }
    },
    'CreationTime': datetime(2015, 1, 1),
    'StartTime': datetime(2015, 1, 1),
    'EndTime': datetime(2015, 1, 1),
    'Tags': [
        {
            'Key': 'string',
            'Value': 'string'
        },
    ]
}

Response Structure

(dict) –
- AIBenchmarkJobName (string) –
  
  The name of the AI benchmark job.
- AIBenchmarkJobArn (string) –
  
  The Amazon Resource Name (ARN) of the AI benchmark job.
- AIBenchmarkJobStatus (string) –
  
  The status of the AI benchmark job.
- FailureReason (string) –
  
  If the benchmark job failed, the reason it failed.
- BenchmarkTarget (dict) –
  
  The target endpoint that was benchmarked.
  Note
  This is a Tagged Union structure. Only one of the following top level keys will be set: Endpoint. If a client receives an unknown member it will set SDK_UNKNOWN_MEMBER as the top level key, which maps to the name or tag of the unknown member. The structure of SDK_UNKNOWN_MEMBER is as follows:
  'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}
  - Endpoint (dict) –
    
    The SageMaker endpoint to benchmark.
    - Identifier (string) –
      
      The name or Amazon Resource Name (ARN) of the SageMaker endpoint to benchmark.
    - TargetContainerHostname (string) –
      
      The hostname of the specific container to target within a multi-container endpoint.
    - InferenceComponents (list) –
      
      The list of inference components to benchmark on the endpoint.
      - (dict) –
        
        An inference component to benchmark.
        
        Identifier (string) –
        
        The name or Amazon Resource Name (ARN) of the inference component.
- OutputConfig (dict) –
  
  The output configuration for the benchmark job, including the Amazon S3 output location and CloudWatch log information.
  - S3OutputLocation (string) –
    
    The Amazon S3 URI where benchmark results are stored.
  - CloudWatchLogs (list) –
    
    The CloudWatch log information for the benchmark job.
    - (dict) –
      
      CloudWatch log information for an AI benchmark or recommendation job.
      - LogGroupArn (string) –
        
        The Amazon Resource Name (ARN) of the CloudWatch log group.
      - LogStreamName (string) –
        
        The name of the CloudWatch log stream.
- AIWorkloadConfigIdentifier (string) –
  
  The name or Amazon Resource Name (ARN) of the AI workload configuration used for this benchmark job.
- RoleArn (string) –
  
  The Amazon Resource Name (ARN) of the IAM role used by the benchmark job.
- NetworkConfig (dict) –
  
  The network configuration for the benchmark job.
  - VpcConfig (dict) –
    
    The VPC configuration, including security group IDs and subnet IDs.
    - SecurityGroupIds (list) –
      
      The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
      - (string) –
    - Subnets (list) –
      
      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.
      - (string) –
- CreationTime (datetime) –
  
  A timestamp that indicates when the benchmark job was created.
- StartTime (datetime) –
  
  A timestamp that indicates when the benchmark job started running.
- EndTime (datetime) –
  
  A timestamp that indicates when the benchmark job completed.
- Tags (list) –
  
  The tags associated with the benchmark job.
  - (dict) –
    
    A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
    
    You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.
    
    For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.
    - Key (string) –
      
      The tag key. Tag keys must be unique per resource.
    - Value (string) –
      
      The tag value.

Exceptions

SageMaker.Client.exceptions.ResourceNotFound