Create Ai Benchmark Job

sagemaker_create_ai_benchmark_job

R Documentation

Creates a benchmark job that runs performance benchmarks against inference infrastructure using a predefined AI workload configuration

Description

Creates a benchmark job that runs performance benchmarks against inference infrastructure using a predefined AI workload configuration. The benchmark job measures metrics such as latency, throughput, and cost for your generative AI inference endpoints.

Usage

sagemaker_create_ai_benchmark_job(AIBenchmarkJobName, BenchmarkTarget,
  OutputConfig, AIWorkloadConfigIdentifier, RoleArn, NetworkConfig, Tags)

Arguments

AIBenchmarkJobName	[required] The name of the AI benchmark job. The name must be unique within your Amazon Web Services account in the current Amazon Web Services Region.
BenchmarkTarget	[required] The target endpoint to benchmark. Specify a SageMaker endpoint by providing its name or Amazon Resource Name (ARN).
OutputConfig	[required] The output configuration for the benchmark job, including the Amazon S3 location where benchmark results are stored.
AIWorkloadConfigIdentifier	[required] The name or Amazon Resource Name (ARN) of the AI workload configuration to use for this benchmark job.
RoleArn	[required] The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
NetworkConfig	The network configuration for the benchmark job, including VPC settings.
Tags	The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define.

Value

A list with the following syntax:

list(
  AIBenchmarkJobArn = "string"
)

Request syntax

svc$create_ai_benchmark_job(
  AIBenchmarkJobName = "string",
  BenchmarkTarget = list(
    Endpoint = list(
      Identifier = "string",
      TargetContainerHostname = "string",
      InferenceComponents = list(
        list(
          Identifier = "string"
        )
      )
    )
  ),
  OutputConfig = list(
    S3OutputLocation = "string"
  ),
  AIWorkloadConfigIdentifier = "string",
  RoleArn = "string",
  NetworkConfig = list(
    VpcConfig = list(
      SecurityGroupIds = list(
        "string"
      ),
      Subnets = list(
        "string"
      )
    )
  ),
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)