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AWS v6.60.0 published on Tuesday, Nov 19, 2024 by Pulumi
pulumi/pulumi-aws

aws.sagemaker.MlflowTrackingServer

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AWS v6.60.0 published on Tuesday, Nov 19, 2024 by Pulumi
pulumi/pulumi-aws

    Provides a SageMaker MLFlow Tracking Server resource.

    Example Usage

    Cognito Usage

    import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

const example = new aws.sagemaker.MlflowTrackingServer("example", {
    trackingServerName: "example",
    roleArn: exampleAwsIamRole.arn,
    artifactStoreUri: `s3://${exampleAwsS3Bucket.bucket}/path`,
});

    import pulumi
import pulumi_aws as aws

example = aws.sagemaker.MlflowTrackingServer("example",
    tracking_server_name="example",
    role_arn=example_aws_iam_role["arn"],
    artifact_store_uri=f"s3://{example_aws_s3_bucket['bucket']}/path")

    package main

import (
	"fmt"

	"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/sagemaker"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := sagemaker.NewMlflowTrackingServer(ctx, "example", &sagemaker.MlflowTrackingServerArgs{
			TrackingServerName: pulumi.String("example"),
			RoleArn:            pulumi.Any(exampleAwsIamRole.Arn),
			ArtifactStoreUri:   pulumi.Sprintf("s3://%v/path", exampleAwsS3Bucket.Bucket),
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;

return await Deployment.RunAsync(() => 
{
    var example = new Aws.Sagemaker.MlflowTrackingServer("example", new()
    {
        TrackingServerName = "example",
        RoleArn = exampleAwsIamRole.Arn,
        ArtifactStoreUri = $"s3://{exampleAwsS3Bucket.Bucket}/path",
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.sagemaker.MlflowTrackingServer;
import com.pulumi.aws.sagemaker.MlflowTrackingServerArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var example = new MlflowTrackingServer("example", MlflowTrackingServerArgs.builder()
            .trackingServerName("example")
            .roleArn(exampleAwsIamRole.arn())
            .artifactStoreUri(String.format("s3://%s/path", exampleAwsS3Bucket.bucket()))
            .build());

    }
}

    resources:
  example:
    type: aws:sagemaker:MlflowTrackingServer
    properties:
      trackingServerName: example
      roleArn: ${exampleAwsIamRole.arn}
      artifactStoreUri: s3://${exampleAwsS3Bucket.bucket}/path

    Create MlflowTrackingServer Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new MlflowTrackingServer(name: string, args: MlflowTrackingServerArgs, opts?: CustomResourceOptions);
    @overload
def MlflowTrackingServer(resource_name: str,
                         args: MlflowTrackingServerArgs,
                         opts: Optional[ResourceOptions] = None)

@overload
def MlflowTrackingServer(resource_name: str,
                         opts: Optional[ResourceOptions] = None,
                         artifact_store_uri: Optional[str] = None,
                         role_arn: Optional[str] = None,
                         tracking_server_name: Optional[str] = None,
                         automatic_model_registration: Optional[bool] = None,
                         mlflow_version: Optional[str] = None,
                         tags: Optional[Mapping[str, str]] = None,
                         tracking_server_size: Optional[str] = None,
                         weekly_maintenance_window_start: Optional[str] = None)
    func NewMlflowTrackingServer(ctx *Context, name string, args MlflowTrackingServerArgs, opts ...ResourceOption) (*MlflowTrackingServer, error)
    public MlflowTrackingServer(string name, MlflowTrackingServerArgs args, CustomResourceOptions? opts = null)
    public MlflowTrackingServer(String name, MlflowTrackingServerArgs args)
public MlflowTrackingServer(String name, MlflowTrackingServerArgs args, CustomResourceOptions options)

    type: aws:sagemaker:MlflowTrackingServer
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args MlflowTrackingServerArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args MlflowTrackingServerArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args MlflowTrackingServerArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args MlflowTrackingServerArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args MlflowTrackingServerArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var mlflowTrackingServerResource = new Aws.Sagemaker.MlflowTrackingServer("mlflowTrackingServerResource", new()
{
    ArtifactStoreUri = "string",
    RoleArn = "string",
    TrackingServerName = "string",
    AutomaticModelRegistration = false,
    MlflowVersion = "string",
    Tags = 
    {
        { "string", "string" },
    },
    TrackingServerSize = "string",
    WeeklyMaintenanceWindowStart = "string",
});

    example, err := sagemaker.NewMlflowTrackingServer(ctx, "mlflowTrackingServerResource", &sagemaker.MlflowTrackingServerArgs{
	ArtifactStoreUri:           pulumi.String("string"),
	RoleArn:                    pulumi.String("string"),
	TrackingServerName:         pulumi.String("string"),
	AutomaticModelRegistration: pulumi.Bool(false),
	MlflowVersion:              pulumi.String("string"),
	Tags: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	TrackingServerSize:           pulumi.String("string"),
	WeeklyMaintenanceWindowStart: pulumi.String("string"),
})

    var mlflowTrackingServerResource = new MlflowTrackingServer("mlflowTrackingServerResource", MlflowTrackingServerArgs.builder()
    .artifactStoreUri("string")
    .roleArn("string")
    .trackingServerName("string")
    .automaticModelRegistration(false)
    .mlflowVersion("string")
    .tags(Map.of("string", "string"))
    .trackingServerSize("string")
    .weeklyMaintenanceWindowStart("string")
    .build());

    mlflow_tracking_server_resource = aws.sagemaker.MlflowTrackingServer("mlflowTrackingServerResource",
    artifact_store_uri="string",
    role_arn="string",
    tracking_server_name="string",
    automatic_model_registration=False,
    mlflow_version="string",
    tags={
        "string": "string",
    },
    tracking_server_size="string",
    weekly_maintenance_window_start="string")

    const mlflowTrackingServerResource = new aws.sagemaker.MlflowTrackingServer("mlflowTrackingServerResource", {
    artifactStoreUri: "string",
    roleArn: "string",
    trackingServerName: "string",
    automaticModelRegistration: false,
    mlflowVersion: "string",
    tags: {
        string: "string",
    },
    trackingServerSize: "string",
    weeklyMaintenanceWindowStart: "string",
});

    type: aws:sagemaker:MlflowTrackingServer
properties:
    artifactStoreUri: string
    automaticModelRegistration: false
    mlflowVersion: string
    roleArn: string
    tags:
        string: string
    trackingServerName: string
    trackingServerSize: string
    weeklyMaintenanceWindowStart: string

    MlflowTrackingServer Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The MlflowTrackingServer resource accepts the following input properties:

    ArtifactStoreUri string
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    RoleArn 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.
    TrackingServerName string
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    AutomaticModelRegistration bool
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    MlflowVersion string
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    Tags Dictionary<string, string>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    TrackingServerSize 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.
    WeeklyMaintenanceWindowStart 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.
    ArtifactStoreUri string
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    RoleArn 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.
    TrackingServerName string
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    AutomaticModelRegistration bool
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    MlflowVersion string
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    Tags map[string]string
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    TrackingServerSize 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.
    WeeklyMaintenanceWindowStart 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.
    artifactStoreUri String
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    roleArn 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.
    trackingServerName String
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    automaticModelRegistration Boolean
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    mlflowVersion String
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    tags Map<String,String>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    trackingServerSize 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.
    weeklyMaintenanceWindowStart 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.
    artifactStoreUri string
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    roleArn 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.
    trackingServerName string
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    automaticModelRegistration boolean
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    mlflowVersion string
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    tags {[key: string]: string}
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    trackingServerSize 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.
    weeklyMaintenanceWindowStart 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.
    artifact_store_uri str
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    role_arn str
    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.
    tracking_server_name str
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    automatic_model_registration bool
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    mlflow_version str
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    tags Mapping[str, str]
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tracking_server_size str
    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.
    weekly_maintenance_window_start str
    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.
    artifactStoreUri String
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    roleArn 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.
    trackingServerName String
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    automaticModelRegistration Boolean
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    mlflowVersion String
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    tags Map<String>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    trackingServerSize 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.
    weeklyMaintenanceWindowStart 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.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the MlflowTrackingServer resource produces the following output properties:

    Arn string
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    Id string
    The provider-assigned unique ID for this managed resource.
    TagsAll Dictionary<string, string>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    TrackingServerUrl string
    The URL to connect to the MLflow user interface for the described tracking server.
    Arn string
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    Id string
    The provider-assigned unique ID for this managed resource.
    TagsAll map[string]string
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    TrackingServerUrl string
    The URL to connect to the MLflow user interface for the described tracking server.
    arn String
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    id String
    The provider-assigned unique ID for this managed resource.
    tagsAll Map<String,String>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    trackingServerUrl String
    The URL to connect to the MLflow user interface for the described tracking server.
    arn string
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    id string
    The provider-assigned unique ID for this managed resource.
    tagsAll {[key: string]: string}
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    trackingServerUrl string
    The URL to connect to the MLflow user interface for the described tracking server.
    arn str
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    id str
    The provider-assigned unique ID for this managed resource.
    tags_all Mapping[str, str]
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    tracking_server_url str
    The URL to connect to the MLflow user interface for the described tracking server.
    arn String
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    id String
    The provider-assigned unique ID for this managed resource.
    tagsAll Map<String>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    trackingServerUrl String
    The URL to connect to the MLflow user interface for the described tracking server.

    Look up Existing MlflowTrackingServer Resource

    Get an existing MlflowTrackingServer resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: MlflowTrackingServerState, opts?: CustomResourceOptions): MlflowTrackingServer
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        arn: Optional[str] = None,
        artifact_store_uri: Optional[str] = None,
        automatic_model_registration: Optional[bool] = None,
        mlflow_version: Optional[str] = None,
        role_arn: Optional[str] = None,
        tags: Optional[Mapping[str, str]] = None,
        tags_all: Optional[Mapping[str, str]] = None,
        tracking_server_name: Optional[str] = None,
        tracking_server_size: Optional[str] = None,
        tracking_server_url: Optional[str] = None,
        weekly_maintenance_window_start: Optional[str] = None) -> MlflowTrackingServer
    func GetMlflowTrackingServer(ctx *Context, name string, id IDInput, state *MlflowTrackingServerState, opts ...ResourceOption) (*MlflowTrackingServer, error)
    public static MlflowTrackingServer Get(string name, Input<string> id, MlflowTrackingServerState? state, CustomResourceOptions? opts = null)
    public static MlflowTrackingServer get(String name, Output<String> id, MlflowTrackingServerState state, CustomResourceOptions options)
    Resource lookup is not supported in YAML
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    Arn string
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    ArtifactStoreUri string
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    AutomaticModelRegistration bool
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    MlflowVersion string
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    RoleArn 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.
    Tags Dictionary<string, string>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    TagsAll Dictionary<string, string>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    TrackingServerName string
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    TrackingServerSize 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.
    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 in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.
    Arn string
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    ArtifactStoreUri string
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    AutomaticModelRegistration bool
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    MlflowVersion string
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    RoleArn 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.
    Tags map[string]string
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    TagsAll map[string]string
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    TrackingServerName string
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    TrackingServerSize 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.
    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 in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.
    arn String
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    artifactStoreUri String
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    automaticModelRegistration Boolean
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    mlflowVersion String
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    roleArn 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.
    tags Map<String,String>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tagsAll Map<String,String>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    trackingServerName String
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    trackingServerSize 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.
    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 in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.
    arn string
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    artifactStoreUri string
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    automaticModelRegistration boolean
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    mlflowVersion string
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    roleArn 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.
    tags {[key: string]: string}
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tagsAll {[key: string]: string}
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    trackingServerName string
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    trackingServerSize 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.
    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 in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.
    arn str
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    artifact_store_uri str
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    automatic_model_registration bool
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    mlflow_version str
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    role_arn str
    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.
    tags Mapping[str, str]
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tags_all Mapping[str, str]
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    tracking_server_name str
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    tracking_server_size str
    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.
    tracking_server_url str
    The URL to connect to the MLflow user interface for the described tracking server.
    weekly_maintenance_window_start str
    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.
    arn String
    The Amazon Resource Name (ARN) assigned by AWS to this MLFlow Tracking Server.
    artifactStoreUri String
    The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
    automaticModelRegistration Boolean
    A list of Member Definitions that contains objects that identify the workers that make up the work team.
    mlflowVersion String
    The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
    roleArn 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.
    tags Map<String>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tagsAll Map<String>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    trackingServerName String
    A unique string identifying the tracking server name. This string is part of the tracking server ARN.
    trackingServerSize 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.
    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 in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.

    Import

    Using pulumi import, import SageMaker MLFlow Tracking Servers using the workteam_name. For example:

    $ pulumi import aws:sagemaker/mlflowTrackingServer:MlflowTrackingServer example example

    To learn more about importing existing cloud resources, see Importing resources.

    Package Details

    Repository
    AWS Classic pulumi/pulumi-aws
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the aws Terraform Provider.
    aws logo
    AWS v6.60.0 published on Tuesday, Nov 19, 2024 by Pulumi
    pulumi/pulumi-aws