pulumi-azure-native-kotlin/com.pulumi.azurenative.machinelearningservices.kotlin/DatastoreArgs

DatastoreArgs

data class DatastoreArgs(val datastoreProperties: Output<Any>? = null, val name: Output<String>? = null, val resourceGroupName: Output<String>? = null, val skipValidation: Output<Boolean>? = null, val workspaceName: Output<String>? = null) : ConvertibleToJava<DatastoreArgs>

Azure Resource Manager resource envelope. Azure REST API version: 2023-04-01. Other available API versions: 2021-03-01-preview, 2022-02-01-preview, 2023-04-01-preview, 2023-06-01-preview, 2023-08-01-preview, 2023-10-01.

Example Usage

CreateOrUpdate datastore (Azure Data Lake Gen1 w/ ServicePrincipal).

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var datastore = new AzureNative.MachineLearningServices.Datastore("datastore", new()
    {
        DatastoreProperties = new AzureNative.MachineLearningServices.Inputs.AzureDataLakeGen1DatastoreArgs
        {
            Credentials = new AzureNative.MachineLearningServices.Inputs.ServicePrincipalDatastoreCredentialsArgs
            {
                AuthorityUrl = "string",
                ClientId = "00000000-1111-2222-3333-444444444444",
                CredentialsType = "ServicePrincipal",
                ResourceUrl = "string",
                Secrets = new AzureNative.MachineLearningServices.Inputs.ServicePrincipalDatastoreSecretsArgs
                {
                    ClientSecret = "string",
                    SecretsType = "ServicePrincipal",
                },
                TenantId = "00000000-1111-2222-3333-444444444444",
            },
            DatastoreType = "AzureDataLakeGen1",
            Description = "string",
            StoreName = "string",
            Tags =
            {
                { "string", "string" },
            },
        },
        Name = "string",
        ResourceGroupName = "test-rg",
        SkipValidation = false,
        WorkspaceName = "my-aml-workspace",
    });
});
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package main
import (
	"github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices/v2"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewDatastore(ctx, "datastore", &machinelearningservices.DatastoreArgs{
			DatastoreProperties: machinelearningservices.AzureDataLakeGen1Datastore{
				Credentials: machinelearningservices.ServicePrincipalDatastoreCredentials{
					AuthorityUrl:    "string",
					ClientId:        "00000000-1111-2222-3333-444444444444",
					CredentialsType: "ServicePrincipal",
					ResourceUrl:     "string",
					Secrets: machinelearningservices.ServicePrincipalDatastoreSecrets{
						ClientSecret: "string",
						SecretsType:  "ServicePrincipal",
					},
					TenantId: "00000000-1111-2222-3333-444444444444",
				},
				DatastoreType: "AzureDataLakeGen1",
				Description:   "string",
				StoreName:     "string",
				Tags: map[string]interface{}{
					"string": "string",
				},
			},
			Name:              pulumi.String("string"),
			ResourceGroupName: pulumi.String("test-rg"),
			SkipValidation:    pulumi.Bool(false),
			WorkspaceName:     pulumi.String("my-aml-workspace"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}
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package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.machinelearningservices.Datastore;
import com.pulumi.azurenative.machinelearningservices.DatastoreArgs;
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 datastore = new Datastore("datastore", DatastoreArgs.builder()
            .datastoreProperties(Map.ofEntries(
                Map.entry("credentials", Map.ofEntries(
                    Map.entry("authorityUrl", "string"),
                    Map.entry("clientId", "00000000-1111-2222-3333-444444444444"),
                    Map.entry("credentialsType", "ServicePrincipal"),
                    Map.entry("resourceUrl", "string"),
                    Map.entry("secrets", Map.ofEntries(
                        Map.entry("clientSecret", "string"),
                        Map.entry("secretsType", "ServicePrincipal")
                    )),
                    Map.entry("tenantId", "00000000-1111-2222-3333-444444444444")
                )),
                Map.entry("datastoreType", "AzureDataLakeGen1"),
                Map.entry("description", "string"),
                Map.entry("storeName", "string"),
                Map.entry("tags", AzureBlobDatastoreArgs.builder()
                    .string("string")
                    .build())
            ))
            .name("string")
            .resourceGroupName("test-rg")
            .skipValidation(false)
            .workspaceName("my-aml-workspace")
            .build());
    }
}
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CreateOrUpdate datastore (Azure Data Lake Gen2 w/ Service Principal).

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var datastore = new AzureNative.MachineLearningServices.Datastore("datastore", new()
    {
        DatastoreProperties = new AzureNative.MachineLearningServices.Inputs.AzureDataLakeGen2DatastoreArgs
        {
            AccountName = "string",
            Credentials = new AzureNative.MachineLearningServices.Inputs.ServicePrincipalDatastoreCredentialsArgs
            {
                AuthorityUrl = "string",
                ClientId = "00000000-1111-2222-3333-444444444444",
                CredentialsType = "ServicePrincipal",
                ResourceUrl = "string",
                Secrets = new AzureNative.MachineLearningServices.Inputs.ServicePrincipalDatastoreSecretsArgs
                {
                    ClientSecret = "string",
                    SecretsType = "ServicePrincipal",
                },
                TenantId = "00000000-1111-2222-3333-444444444444",
            },
            DatastoreType = "AzureDataLakeGen2",
            Description = "string",
            Endpoint = "string",
            Filesystem = "string",
            Protocol = "string",
            Tags =
            {
                { "string", "string" },
            },
        },
        Name = "string",
        ResourceGroupName = "test-rg",
        SkipValidation = false,
        WorkspaceName = "my-aml-workspace",
    });
});
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package main
import (
	"github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices/v2"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewDatastore(ctx, "datastore", &machinelearningservices.DatastoreArgs{
			DatastoreProperties: machinelearningservices.AzureDataLakeGen2Datastore{
				AccountName: "string",
				Credentials: machinelearningservices.ServicePrincipalDatastoreCredentials{
					AuthorityUrl:    "string",
					ClientId:        "00000000-1111-2222-3333-444444444444",
					CredentialsType: "ServicePrincipal",
					ResourceUrl:     "string",
					Secrets: machinelearningservices.ServicePrincipalDatastoreSecrets{
						ClientSecret: "string",
						SecretsType:  "ServicePrincipal",
					},
					TenantId: "00000000-1111-2222-3333-444444444444",
				},
				DatastoreType: "AzureDataLakeGen2",
				Description:   "string",
				Endpoint:      "string",
				Filesystem:    "string",
				Protocol:      "string",
				Tags: map[string]interface{}{
					"string": "string",
				},
			},
			Name:              pulumi.String("string"),
			ResourceGroupName: pulumi.String("test-rg"),
			SkipValidation:    pulumi.Bool(false),
			WorkspaceName:     pulumi.String("my-aml-workspace"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}
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package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.machinelearningservices.Datastore;
import com.pulumi.azurenative.machinelearningservices.DatastoreArgs;
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 datastore = new Datastore("datastore", DatastoreArgs.builder()
            .datastoreProperties(Map.ofEntries(
                Map.entry("accountName", "string"),
                Map.entry("credentials", Map.ofEntries(
                    Map.entry("authorityUrl", "string"),
                    Map.entry("clientId", "00000000-1111-2222-3333-444444444444"),
                    Map.entry("credentialsType", "ServicePrincipal"),
                    Map.entry("resourceUrl", "string"),
                    Map.entry("secrets", Map.ofEntries(
                        Map.entry("clientSecret", "string"),
                        Map.entry("secretsType", "ServicePrincipal")
                    )),
                    Map.entry("tenantId", "00000000-1111-2222-3333-444444444444")
                )),
                Map.entry("datastoreType", "AzureDataLakeGen2"),
                Map.entry("description", "string"),
                Map.entry("endpoint", "string"),
                Map.entry("filesystem", "string"),
                Map.entry("protocol", "string"),
                Map.entry("tags", AzureBlobDatastoreArgs.builder()
                    .string("string")
                    .build())
            ))
            .name("string")
            .resourceGroupName("test-rg")
            .skipValidation(false)
            .workspaceName("my-aml-workspace")
            .build());
    }
}
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CreateOrUpdate datastore (Azure File store w/ AccountKey).

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var datastore = new AzureNative.MachineLearningServices.Datastore("datastore", new()
    {
        DatastoreProperties = new AzureNative.MachineLearningServices.Inputs.AzureFileDatastoreArgs
        {
            AccountName = "string",
            Credentials = new AzureNative.MachineLearningServices.Inputs.AccountKeyDatastoreCredentialsArgs
            {
                CredentialsType = "AccountKey",
                Secrets = new AzureNative.MachineLearningServices.Inputs.AccountKeyDatastoreSecretsArgs
                {
                    Key = "string",
                    SecretsType = "AccountKey",
                },
            },
            DatastoreType = "AzureFile",
            Description = "string",
            Endpoint = "string",
            FileShareName = "string",
            Protocol = "string",
            Tags =
            {
                { "string", "string" },
            },
        },
        Name = "string",
        ResourceGroupName = "test-rg",
        SkipValidation = false,
        WorkspaceName = "my-aml-workspace",
    });
});
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package main
import (
	"github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices/v2"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewDatastore(ctx, "datastore", &machinelearningservices.DatastoreArgs{
			DatastoreProperties: machinelearningservices.AzureFileDatastore{
				AccountName: "string",
				Credentials: machinelearningservices.AccountKeyDatastoreCredentials{
					CredentialsType: "AccountKey",
					Secrets: machinelearningservices.AccountKeyDatastoreSecrets{
						Key:         "string",
						SecretsType: "AccountKey",
					},
				},
				DatastoreType: "AzureFile",
				Description:   "string",
				Endpoint:      "string",
				FileShareName: "string",
				Protocol:      "string",
				Tags: map[string]interface{}{
					"string": "string",
				},
			},
			Name:              pulumi.String("string"),
			ResourceGroupName: pulumi.String("test-rg"),
			SkipValidation:    pulumi.Bool(false),
			WorkspaceName:     pulumi.String("my-aml-workspace"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}
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package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.machinelearningservices.Datastore;
import com.pulumi.azurenative.machinelearningservices.DatastoreArgs;
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 datastore = new Datastore("datastore", DatastoreArgs.builder()
            .datastoreProperties(Map.ofEntries(
                Map.entry("accountName", "string"),
                Map.entry("credentials", Map.ofEntries(
                    Map.entry("credentialsType", "AccountKey"),
                    Map.entry("secrets", Map.ofEntries(
                        Map.entry("key", "string"),
                        Map.entry("secretsType", "AccountKey")
                    ))
                )),
                Map.entry("datastoreType", "AzureFile"),
                Map.entry("description", "string"),
                Map.entry("endpoint", "string"),
                Map.entry("fileShareName", "string"),
                Map.entry("protocol", "string"),
                Map.entry("tags", AzureBlobDatastoreArgs.builder()
                    .string("string")
                    .build())
            ))
            .name("string")
            .resourceGroupName("test-rg")
            .skipValidation(false)
            .workspaceName("my-aml-workspace")
            .build());
    }
}
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CreateOrUpdate datastore (AzureBlob w/ AccountKey).

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var datastore = new AzureNative.MachineLearningServices.Datastore("datastore", new()
    {
        DatastoreProperties = new AzureNative.MachineLearningServices.Inputs.AzureBlobDatastoreArgs
        {
            AccountName = "string",
            ContainerName = "string",
            Credentials = new AzureNative.MachineLearningServices.Inputs.AccountKeyDatastoreCredentialsArgs
            {
                CredentialsType = "AccountKey",
                Secrets = new AzureNative.MachineLearningServices.Inputs.AccountKeyDatastoreSecretsArgs
                {
                    Key = "string",
                    SecretsType = "AccountKey",
                },
            },
            DatastoreType = "AzureBlob",
            Description = "string",
            Endpoint = "core.windows.net",
            Protocol = "https",
            Tags =
            {
                { "string", "string" },
            },
        },
        Name = "string",
        ResourceGroupName = "test-rg",
        SkipValidation = false,
        WorkspaceName = "my-aml-workspace",
    });
});
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package main
import (
	"github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices/v2"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewDatastore(ctx, "datastore", &machinelearningservices.DatastoreArgs{
			DatastoreProperties: machinelearningservices.AzureBlobDatastore{
				AccountName:   "string",
				ContainerName: "string",
				Credentials: machinelearningservices.AccountKeyDatastoreCredentials{
					CredentialsType: "AccountKey",
					Secrets: machinelearningservices.AccountKeyDatastoreSecrets{
						Key:         "string",
						SecretsType: "AccountKey",
					},
				},
				DatastoreType: "AzureBlob",
				Description:   "string",
				Endpoint:      "core.windows.net",
				Protocol:      "https",
				Tags: map[string]interface{}{
					"string": "string",
				},
			},
			Name:              pulumi.String("string"),
			ResourceGroupName: pulumi.String("test-rg"),
			SkipValidation:    pulumi.Bool(false),
			WorkspaceName:     pulumi.String("my-aml-workspace"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}
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package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.machinelearningservices.Datastore;
import com.pulumi.azurenative.machinelearningservices.DatastoreArgs;
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 datastore = new Datastore("datastore", DatastoreArgs.builder()
            .datastoreProperties(Map.ofEntries(
                Map.entry("accountName", "string"),
                Map.entry("containerName", "string"),
                Map.entry("credentials", Map.ofEntries(
                    Map.entry("credentialsType", "AccountKey"),
                    Map.entry("secrets", Map.ofEntries(
                        Map.entry("key", "string"),
                        Map.entry("secretsType", "AccountKey")
                    ))
                )),
                Map.entry("datastoreType", "AzureBlob"),
                Map.entry("description", "string"),
                Map.entry("endpoint", "core.windows.net"),
                Map.entry("protocol", "https"),
                Map.entry("tags", AzureBlobDatastoreArgs.builder()
                    .string("string")
                    .build())
            ))
            .name("string")
            .resourceGroupName("test-rg")
            .skipValidation(false)
            .workspaceName("my-aml-workspace")
            .build());
    }
}
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Import

An existing resource can be imported using its type token, name, and identifier, e.g.

$ pulumi import azure-native:machinelearningservices:Datastore string /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datastores/{name}
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Constructors

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fun DatastoreArgs(datastoreProperties: Output<Any>? = null, name: Output<String>? = null, resourceGroupName: Output<String>? = null, skipValidation: Output<Boolean>? = null, workspaceName: Output<String>? = null)

Functions

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open override fun toJava(): DatastoreArgs

Properties

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val datastoreProperties: Output<Any>? = null

Required Additional attributes of the entity.

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val name: Output<String>? = null

Datastore name.

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val resourceGroupName: Output<String>? = null

The name of the resource group. The name is case insensitive.

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val skipValidation: Output<Boolean>? = null

Flag to skip validation.

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val workspaceName: Output<String>? = null

Name of Azure Machine Learning workspace.