Container Contract Inputs - Amazon SageMaker

Container Contract Inputs

The Amazon SageMaker Model Monitor platform invokes your container code according to a specified schedule. If you chose to write your own container code, the following environment variables are available for your container code. In this context, you can analyze the current dataset or evaluate the constraints if you chose to and emit metrics, if applicable.

"Environment": { "dataset_format": "{\"sagemakerCaptureJson\": {\"captureIndexNames\": [\"endpointInput\",\"endpointOutput\"]}}", "dataset_source": "/opt/ml/processing/endpointdata", "end_time": "2019-12-01T16: 20: 00Z", "output_path": "/opt/ml/processing/resultdata", "publish_cloudwatch_metrics": "Disabled", "sagemaker_endpoint_name": "endpoint-name", "sagemaker_monitoring_schedule_name": "schedule-name", "start_time": "2019-12-01T15: 20: 00Z" }
Table: Parameters
Parameter Name Description

For a job started from a MonitoringSchedule backed by an Endpoint, this is sageMakerCaptureJson with the capture indices endpointInput,or endpointOutput, or both.


The local path in which the data corresponding to the monitoring period, as specified by start_time and end_time, are available. At this path, the data is available in /{endpoint-name}/{variant-name}/yyyy/mm/dd/hh.

We sometimes download more than what is specified by the start and end times. It is up to the container code to parse the data as required.


The local path to write output reports and other files. You specify this parameter in the CreateMonitoringSchedule request as MonitoringOutputConfig.MonitoringOutput[0].LocalPath. It is uploaded to the S3Uri path specified in MonitoringOutputConfig.MonitoringOutput[0].S3Uri.


For a job launched by CreateMonitoringSchedule, this parameter is set to Enabled. The container can choose to write the Amazon CloudWatch output file at [filepath].


The name of the Endpoint that this scheduled job was launched for.


The name of the MonitoringSchedule that launched this job.


The prefix specified in the DataCaptureConfig parameter of the Endpoint. The container can use this if it needs to directly access more data than already downloaded by Amazon SageMaker at the dataset_source path.

start_time, end_time

The time window for this analysis run. For example, for a job scheduled to run at 05:00 UTC and a job that runs on 20/02/2020, start_time: is 2020-02-19T06:00:00Z and end_time: is 2020-02-20T05:00:00Z


The local path of the baseline constraint file specified in BaselineConfig.ConstraintResource.S3Uri. This is available only if this parameter was specified in the CreateMonitoringSchedule request.


The local path to the baseline statistics file specified in BaselineConfig.StatisticsResource.S3Uri. This is available only if this parameter was specified in the CreateMonitoringSchedule request.: