2026/03/05 - Amazon SageMaker Service - 3 updated api methods
Changes Adds support for S3 Bucket Ownership validation for SageMaker Managed MLflow.
{'S3BucketOwnerAccountId': 'string', 'S3BucketOwnerVerification': 'boolean'}
Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact store. For more information, see Create an MLflow Tracking Server.
See also: AWS API Documentation
Request Syntax
client.create_mlflow_tracking_server(
TrackingServerName='string',
ArtifactStoreUri='string',
TrackingServerSize='Small'|'Medium'|'Large',
MlflowVersion='string',
RoleArn='string',
AutomaticModelRegistration=True|False,
WeeklyMaintenanceWindowStart='string',
Tags=[
{
'Key': 'string',
'Value': 'string'
},
],
S3BucketOwnerAccountId='string',
S3BucketOwnerVerification=True|False
)
string
[REQUIRED]
A unique string identifying the tracking server name. This string is part of the tracking server ARN.
string
[REQUIRED]
The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
string
The size of the tracking server you want to create. You can choose between "Small", "Medium", and "Large". The default MLflow Tracking Server configuration size is "Small". You can choose a size depending on the projected use of the tracking server such as the volume of data logged, number of users, and frequency of use.
We recommend using a small tracking server for teams of up to 25 users, a medium tracking server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
string
The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
string
[REQUIRED]
The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to access the artifact store in Amazon S3. The role should have AmazonS3FullAccess permissions. For more information on IAM permissions for tracking server creation, see Set up IAM permissions for MLflow.
boolean
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to True. To disable automatic model registration, set this value to False. If not specified, AutomaticModelRegistration defaults to False.
string
The day and time of the week in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.
list
Tags consisting of key-value pairs used to manage metadata for the tracking server.
(dict) --
A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.
Key (string) -- [REQUIRED]
The tag key. Tag keys must be unique per resource.
Value (string) -- [REQUIRED]
The tag value.
string
Expected Amazon Web Services account ID that owns the Amazon S3 bucket for artifact storage. Defaults to caller's account ID if not provided.
boolean
Enable Amazon S3 Ownership checks when interacting with Amazon S3 buckets from a SageMaker Managed MLflow Tracking Server. Defaults to True if not provided.
dict
Response Syntax
{
'TrackingServerArn': 'string'
}
Response Structure
(dict) --
TrackingServerArn (string) --
The ARN of the tracking server.
{'S3BucketOwnerAccountId': 'string', 'S3BucketOwnerVerification': 'boolean'}
Returns information about an MLflow Tracking Server.
See also: AWS API Documentation
Request Syntax
client.describe_mlflow_tracking_server(
TrackingServerName='string'
)
string
[REQUIRED]
The name of the MLflow Tracking Server to describe.
dict
Response Syntax
{
'TrackingServerArn': 'string',
'TrackingServerName': 'string',
'ArtifactStoreUri': 'string',
'TrackingServerSize': 'Small'|'Medium'|'Large',
'MlflowVersion': 'string',
'RoleArn': 'string',
'TrackingServerStatus': 'Creating'|'Created'|'CreateFailed'|'Updating'|'Updated'|'UpdateFailed'|'Deleting'|'DeleteFailed'|'Stopping'|'Stopped'|'StopFailed'|'Starting'|'Started'|'StartFailed'|'MaintenanceInProgress'|'MaintenanceComplete'|'MaintenanceFailed',
'TrackingServerMaintenanceStatus': 'MaintenanceInProgress'|'MaintenanceComplete'|'MaintenanceFailed',
'IsActive': 'Active'|'Inactive',
'TrackingServerUrl': 'string',
'WeeklyMaintenanceWindowStart': 'string',
'AutomaticModelRegistration': True|False,
'CreationTime': datetime(2015, 1, 1),
'CreatedBy': {
'UserProfileArn': 'string',
'UserProfileName': 'string',
'DomainId': 'string',
'IamIdentity': {
'Arn': 'string',
'PrincipalId': 'string',
'SourceIdentity': 'string'
}
},
'LastModifiedTime': datetime(2015, 1, 1),
'LastModifiedBy': {
'UserProfileArn': 'string',
'UserProfileName': 'string',
'DomainId': 'string',
'IamIdentity': {
'Arn': 'string',
'PrincipalId': 'string',
'SourceIdentity': 'string'
}
},
'S3BucketOwnerAccountId': 'string',
'S3BucketOwnerVerification': True|False
}
Response Structure
(dict) --
TrackingServerArn (string) --
The ARN of the described tracking server.
TrackingServerName (string) --
The name of the described tracking server.
ArtifactStoreUri (string) --
The S3 URI of the general purpose bucket used as the MLflow Tracking Server artifact store.
TrackingServerSize (string) --
The size of the described tracking server.
MlflowVersion (string) --
The MLflow version used for the described tracking server.
RoleArn (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.
TrackingServerStatus (string) --
The current creation status of the described MLflow Tracking Server.
TrackingServerMaintenanceStatus (string) --
The current maintenance status of the described MLflow Tracking Server.
IsActive (string) --
Whether the described MLflow Tracking Server is currently active.
TrackingServerUrl (string) --
The URL to connect to the MLflow user interface for the described tracking server.
WeeklyMaintenanceWindowStart (string) --
The day and time of the week when weekly maintenance occurs on the described tracking server.
AutomaticModelRegistration (boolean) --
Whether automatic registration of new MLflow models to the SageMaker Model Registry is enabled.
CreationTime (datetime) --
The timestamp of when the described MLflow Tracking Server was created.
CreatedBy (dict) --
Information about the user who created or modified a SageMaker resource.
UserProfileArn (string) --
The Amazon Resource Name (ARN) of the user's profile.
UserProfileName (string) --
The name of the user's profile.
DomainId (string) --
The domain associated with the user.
IamIdentity (dict) --
The IAM Identity details associated with the user. These details are associated with model package groups, model packages, and project entities only.
Arn (string) --
The Amazon Resource Name (ARN) of the IAM identity.
PrincipalId (string) --
The ID of the principal that assumes the IAM identity.
SourceIdentity (string) --
The person or application which assumes the IAM identity.
LastModifiedTime (datetime) --
The timestamp of when the described MLflow Tracking Server was last modified.
LastModifiedBy (dict) --
Information about the user who created or modified a SageMaker resource.
UserProfileArn (string) --
The Amazon Resource Name (ARN) of the user's profile.
UserProfileName (string) --
The name of the user's profile.
DomainId (string) --
The domain associated with the user.
IamIdentity (dict) --
The IAM Identity details associated with the user. These details are associated with model package groups, model packages, and project entities only.
Arn (string) --
The Amazon Resource Name (ARN) of the IAM identity.
PrincipalId (string) --
The ID of the principal that assumes the IAM identity.
SourceIdentity (string) --
The person or application which assumes the IAM identity.
S3BucketOwnerAccountId (string) --
Expected Amazon Web Services account ID that owns the Amazon S3 bucket for artifact storage.
S3BucketOwnerVerification (boolean) --
Whether Amazon S3 Bucket Ownership checks are enabled whenever the tracking server interacts with Amazon Amazon S3.
{'S3BucketOwnerAccountId': 'string', 'S3BucketOwnerVerification': 'boolean'}
Updates properties of an existing MLflow Tracking Server.
See also: AWS API Documentation
Request Syntax
client.update_mlflow_tracking_server(
TrackingServerName='string',
ArtifactStoreUri='string',
TrackingServerSize='Small'|'Medium'|'Large',
AutomaticModelRegistration=True|False,
WeeklyMaintenanceWindowStart='string',
S3BucketOwnerAccountId='string',
S3BucketOwnerVerification=True|False
)
string
[REQUIRED]
The name of the MLflow Tracking Server to update.
string
The new S3 URI for the general purpose bucket to use as the artifact store for the MLflow Tracking Server.
string
The new size for the MLflow Tracking Server.
boolean
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to True. To disable automatic model registration, set this value to False. If not specified, AutomaticModelRegistration defaults to False
string
The new weekly maintenance window start day and time to update. The maintenance window day and time should be in Coordinated Universal Time (UTC) 24-hour standard time. For example: TUE:03:30.
string
The new expected Amazon Web Services account ID that owns the Amazon S3 bucket for artifact storage.
boolean
Whether to enable or disable Amazon S3 Bucket Owenrship Verifaction whenever the MLflow Tracking Server interacts with Amazon Amazon S3.
dict
Response Syntax
{
'TrackingServerArn': 'string'
}
Response Structure
(dict) --
TrackingServerArn (string) --
The ARN of the updated MLflow Tracking Server.