Struct aws_sdk_sagemaker::operation::create_mlflow_tracking_server::builders::CreateMlflowTrackingServerFluentBuilder

pub struct CreateMlflowTrackingServerFluentBuilder { /* private fields */ }

Fluent builder constructing a request to CreateMlflowTrackingServer.

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.

Implementations

impl CreateMlflowTrackingServerFluentBuilder

pub fn as_input(&self) -> &CreateMlflowTrackingServerInputBuilder

Access the CreateMlflowTrackingServer as a reference.

pub async fn send( self, ) -> Result<CreateMlflowTrackingServerOutput, SdkError<CreateMlflowTrackingServerError, HttpResponse>>

Sends the request and returns the response.

If an error occurs, an SdkError will be returned with additional details that can be matched against.

By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.

pub fn customize( self, ) -> CustomizableOperation<CreateMlflowTrackingServerOutput, CreateMlflowTrackingServerError, Self>

Consumes this builder, creating a customizable operation that can be modified before being sent.

pub fn tracking_server_name(self, input: impl Into<String>) -> Self

A unique string identifying the tracking server name. This string is part of the tracking server ARN.

pub fn set_tracking_server_name(self, input: Option<String>) -> Self

A unique string identifying the tracking server name. This string is part of the tracking server ARN.

pub fn get_tracking_server_name(&self) -> &Option<String>

A unique string identifying the tracking server name. This string is part of the tracking server ARN.

pub fn artifact_store_uri(self, input: impl Into<String>) -> Self

The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.

pub fn set_artifact_store_uri(self, input: Option<String>) -> Self

The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.

pub fn get_artifact_store_uri(&self) -> &Option<String>

The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.

pub fn tracking_server_size(self, input: TrackingServerSize) -> Self

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.

pub fn set_tracking_server_size(self, input: Option<TrackingServerSize>) -> Self

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.

pub fn get_tracking_server_size(&self) -> &Option<TrackingServerSize>

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.

pub fn mlflow_version(self, input: impl Into<String>) -> Self

The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.

pub fn set_mlflow_version(self, input: Option<String>) -> Self

The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.

pub fn get_mlflow_version(&self) -> &Option<String>

The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.

pub fn role_arn(self, input: impl Into<String>) -> Self

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.

pub fn set_role_arn(self, input: Option<String>) -> Self

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.

pub fn get_role_arn(&self) -> &Option<String>

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.

pub fn automatic_model_registration(self, input: bool) -> Self

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.

pub fn set_automatic_model_registration(self, input: Option<bool>) -> Self

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.

pub fn get_automatic_model_registration(&self) -> &Option<bool>

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.

pub fn weekly_maintenance_window_start(self, input: impl Into<String>) -> Self

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.

pub fn set_weekly_maintenance_window_start(self, input: Option<String>) -> Self

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.

pub fn get_weekly_maintenance_window_start(&self) -> &Option<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.

pub fn tags(self, input: Tag) -> Self

Appends an item to Tags.

To override the contents of this collection use set_tags.

Tags consisting of key-value pairs used to manage metadata for the tracking server.

pub fn set_tags(self, input: Option<Vec<Tag>>) -> Self

Tags consisting of key-value pairs used to manage metadata for the tracking server.

pub fn get_tags(&self) -> &Option<Vec<Tag>>

Tags consisting of key-value pairs used to manage metadata for the tracking server.

Trait Implementations

impl Clone for CreateMlflowTrackingServerFluentBuilder

fn clone(&self) -> CreateMlflowTrackingServerFluentBuilder

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateMlflowTrackingServerFluentBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.