SageMaker MLflow Tracking Server

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The SageMaker MLflow Tracking Server is a managed service in AWS that integrates MLflow with Amazon SageMaker. It provides a centralized tracking server for logging, organizing, and querying machine learning experiment metadata such as parameters, metrics, and artifacts. This allows data scientists and ML engineers to manage experiments at scale without the overhead of deploying and maintaining their own MLflow infrastructure.

aws.sagemaker_mlflow_tracking_server

Fields

ID	Type	Data Type	Description
_key	core	string
account_id	core	string
artifact_store_uri	core	string	The S3 URI of the general purpose bucket used as the MLflow Tracking Server artifact store.
automatic_model_registration	core	bool	Whether automatic registration of new MLflow models to the SageMaker Model Registry is enabled.
created_by	core	json	Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
creation_time	core	timestamp	The timestamp of when the described MLflow Tracking Server was created.
is_active	core	string	Whether the described MLflow Tracking Server is currently active.
last_modified_by	core	json	Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
last_modified_time	core	timestamp	The timestamp of when the described MLflow Tracking Server was last modified.
mlflow_version	core	string	The MLflow version used for the described tracking server.
role_arn	core	string	The Amazon Resource Name (ARN) for an IAM role in your account that the described MLflow Tracking Server uses to access the artifact store in Amazon S3.
tags	core	hstore
tracking_server_arn	core	string	The ARN of the described tracking server.
tracking_server_maintenance_status	core	string	The current maintenance status of the described MLflow Tracking Server.
tracking_server_name	core	string	The name of the described tracking server.
tracking_server_size	core	string	The size of the described tracking server.
tracking_server_status	core	string	The current creation status of the described MLflow Tracking Server.
tracking_server_url	core	string	The URL to connect to the MLflow user interface for the described tracking server.
weekly_maintenance_window_start	core	string	The day and time of the week when weekly maintenance occurs on the described tracking server.