SageMaker Monitoring Schedule

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SageMaker Monitoring Schedule is an AWS resource that defines and manages recurring monitoring jobs for machine learning models. It allows you to automatically run data quality, model quality, bias, or feature attribution checks on a set schedule. This helps ensure models remain accurate, fair, and reliable over time by continuously evaluating their performance against defined baselines.

aws.sagemaker_monitoring_schedule

Fields

ID	Type	Data Type	Description
_key	core	string
account_id	core	string
creation_time	core	timestamp	The time at which the monitoring job was created.
endpoint_name	core	string	The name of the endpoint for the monitoring job.
failure_reason	core	string	A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
last_modified_time	core	timestamp	The time at which the monitoring job was last modified.
last_monitoring_execution_summary	core	json	Describes metadata on the last execution to run, if there was one.
monitoring_schedule_arn	core	string	The Amazon Resource Name (ARN) of the monitoring schedule.
monitoring_schedule_config	core	json	The configuration object that specifies the monitoring schedule and defines the monitoring job.
monitoring_schedule_name	core	string	Name of the monitoring schedule.
monitoring_schedule_status	core	string	The status of an monitoring job.
monitoring_type	core	string	The type of the monitoring job that this schedule runs. This is one of the following values. DATA_QUALITY - The schedule is for a data quality monitoring job. MODEL_QUALITY - The schedule is for a model quality monitoring job. MODEL_BIAS - The schedule is for a bias monitoring job. MODEL_EXPLAINABILITY - The schedule is for an explainability monitoring job.
tags	core	hstore