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  • new tasks.SageMakerCreateTransformJob(this, 'Batch Inference', {
      transformJobName: 'MyTransformJob',
      modelName: 'MyModelName',
      modelClientOptions: {
        invocationsMaxRetries: 3,  // default is 0
        invocationsTimeout: Duration.minutes(5),  // default is 60 seconds
      },
      transformInput: {
        transformDataSource: {
          s3DataSource: {
            s3Uri: 's3://inputbucket/train',
            s3DataType: tasks.S3DataType.S3_PREFIX,
          }
        }
      },
      transformOutput: {
        s3OutputPath: 's3://outputbucket/TransformJobOutputPath',
      },
      transformResources: {
        instanceCount: 1,
        instanceType: ec2.InstanceType.of(ec2.InstanceClass.M4, ec2.InstanceSize.XLARGE),
      }
    });
    
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  • new tasks.SageMakerCreateTransformJob(this, 'Batch Inference', {
      transformJobName: 'MyTransformJob',
      modelName: 'MyModelName',
      modelClientOptions: {
        invocationsMaxRetries: 3,  // default is 0
        invocationsTimeout: Duration.minutes(5),  // default is 60 seconds
      },
      transformInput: {
        transformDataSource: {
          s3DataSource: {
            s3Uri: 's3://inputbucket/train',
            s3DataType: tasks.S3DataType.S3_PREFIX,
          }
        }
      },
      transformOutput: {
        s3OutputPath: 's3://outputbucket/TransformJobOutputPath',
      },
      transformResources: {
        instanceCount: 1,
        instanceType: ec2.InstanceType.of(ec2.InstanceClass.M4, ec2.InstanceSize.XLARGE),
      }
    });
    
    
    Docs
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  • new tasks.SageMakerCreateTrainingJob(this, 'TrainSagemaker', {
      trainingJobName: sfn.JsonPath.stringAt('$.JobName'),
      algorithmSpecification: {
        algorithmName: 'BlazingText',
        trainingInputMode: tasks.InputMode.FILE,
      },
      inputDataConfig: [{
        channelName: 'train',
        dataSource: {
          s3DataSource: {
            s3DataType: tasks.S3DataType.S3_PREFIX,
            s3Location: tasks.S3Location.fromJsonExpression('$.S3Bucket'),
          },
        },
      }],
      outputDataConfig: {
        s3OutputLocation: tasks.S3Location.fromBucket(s3.Bucket.fromBucketName(this, 'Bucket', 'mybucket'), 'myoutputpath'),
      },
      resourceConfig: {
        instanceCount: 1,
        instanceType: new ec2.InstanceType(sfn.JsonPath.stringAt('$.InstanceType')),
        volumeSize: Size.gibibytes(50),
      }, // optional: default is 1 instance of EC2 `M4.XLarge` with `10GB` volume
      stoppingCondition: {
        maxRuntime: Duration.hours(2),
      }, // optional: default is 1 hour
    });
    
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  • new tasks.SageMakerCreateModel(this, 'Sagemaker', {
      modelName: 'MyModel',
      primaryContainer: new tasks.ContainerDefinition({
        image: tasks.DockerImage.fromJsonExpression(sfn.JsonPath.stringAt('$.Model.imageName')),
        mode: tasks.Mode.SINGLE_MODEL,
        modelS3Location: tasks.S3Location.fromJsonExpression('$.TrainingJob.ModelArtifacts.S3ModelArtifacts'),
      }),
    });
    
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  • new tasks.SageMakerCreateEndpoint(this, 'SagemakerEndpoint', {
      endpointName: sfn.JsonPath.stringAt('$.EndpointName'),
      endpointConfigName: sfn.JsonPath.stringAt('$.EndpointConfigName'),
    });
    
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  • new tasks.SageMakerCreateEndpointConfig(this, 'SagemakerEndpointConfig', {
      endpointConfigName: 'MyEndpointConfig',
      productionVariants: [{
      initialInstanceCount: 2,
      instanceType: ec2.InstanceType.of(ec2.InstanceClass.M5, ec2.InstanceSize.XLARGE),
        modelName: 'MyModel',
        variantName: 'awesome-variant',
      }],
    });
    
    Docs
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