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

MachineLearningComputeArgs

data class MachineLearningComputeArgs(val computeName: Output<String>? = null, val identity: Output<IdentityArgs>? = null, val location: Output<String>? = null, val properties: Output<Any>? = null, val resourceGroupName: Output<String>? = null, val sku: Output<SkuArgs>? = null, val tags: Output<Map<String, String>>? = null, val workspaceName: Output<String>? = null) : ConvertibleToJava<MachineLearningComputeArgs>

Machine Learning compute object wrapped into ARM resource envelope. API Version: 2021-01-01.

Example Usage

Create AKS Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var machineLearningCompute = new AzureNative.MachineLearningServices.MachineLearningCompute("machineLearningCompute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.AKSArgs
        {
            ComputeType = "AKS",
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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package main
import (
	machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewMachineLearningCompute(ctx, "machineLearningCompute", &machinelearningservices.MachineLearningComputeArgs{
			ComputeName: pulumi.String("compute123"),
			Location:    pulumi.String("eastus"),
			Properties: machinelearningservices.AKS{
				ComputeType: "AKS",
			},
			ResourceGroupName: pulumi.String("testrg123"),
			WorkspaceName:     pulumi.String("workspaces123"),
		})
		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.MachineLearningCompute;
import com.pulumi.azurenative.machinelearningservices.MachineLearningComputeArgs;
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 machineLearningCompute = new MachineLearningCompute("machineLearningCompute", MachineLearningComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.of("computeType", "AKS"))
            .resourceGroupName("testrg123")
            .workspaceName("workspaces123")
            .build());
    }
}
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Create a AML Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var machineLearningCompute = new AzureNative.MachineLearningServices.MachineLearningCompute("machineLearningCompute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.AmlComputeArgs
        {
            ComputeType = "AmlCompute",
            Properties = new AzureNative.MachineLearningServices.Inputs.AmlComputePropertiesArgs
            {
                EnableNodePublicIp = true,
                IsolatedNetwork = false,
                OsType = "Windows",
                RemoteLoginPortPublicAccess = "NotSpecified",
                ScaleSettings = new AzureNative.MachineLearningServices.Inputs.ScaleSettingsArgs
                {
                    MaxNodeCount = 1,
                    MinNodeCount = 0,
                    NodeIdleTimeBeforeScaleDown = "PT5M",
                },
                VirtualMachineImage = new AzureNative.MachineLearningServices.Inputs.VirtualMachineImageArgs
                {
                    Id = "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.Compute/galleries/myImageGallery/images/myImageDefinition/versions/0.0.1",
                },
                VmPriority = "Dedicated",
                VmSize = "STANDARD_NC6",
            },
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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package main
import (
	machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewMachineLearningCompute(ctx, "machineLearningCompute", &machinelearningservices.MachineLearningComputeArgs{
			ComputeName: pulumi.String("compute123"),
			Location:    pulumi.String("eastus"),
			Properties: machinelearningservices.AmlCompute{
				ComputeType: "AmlCompute",
				Properties: machinelearningservices.AmlComputeProperties{
					EnableNodePublicIp:          true,
					IsolatedNetwork:             false,
					OsType:                      "Windows",
					RemoteLoginPortPublicAccess: "NotSpecified",
					ScaleSettings: machinelearningservices.ScaleSettings{
						MaxNodeCount:                1,
						MinNodeCount:                0,
						NodeIdleTimeBeforeScaleDown: "PT5M",
					},
					VirtualMachineImage: machinelearningservices.VirtualMachineImage{
						Id: "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.Compute/galleries/myImageGallery/images/myImageDefinition/versions/0.0.1",
					},
					VmPriority: "Dedicated",
					VmSize:     "STANDARD_NC6",
				},
			},
			ResourceGroupName: pulumi.String("testrg123"),
			WorkspaceName:     pulumi.String("workspaces123"),
		})
		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.MachineLearningCompute;
import com.pulumi.azurenative.machinelearningservices.MachineLearningComputeArgs;
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 machineLearningCompute = new MachineLearningCompute("machineLearningCompute", MachineLearningComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.ofEntries(
                Map.entry("computeType", "AmlCompute"),
                Map.entry("properties", Map.ofEntries(
                    Map.entry("enableNodePublicIp", true),
                    Map.entry("isolatedNetwork", false),
                    Map.entry("osType", "Windows"),
                    Map.entry("remoteLoginPortPublicAccess", "NotSpecified"),
                    Map.entry("scaleSettings", Map.ofEntries(
                        Map.entry("maxNodeCount", 1),
                        Map.entry("minNodeCount", 0),
                        Map.entry("nodeIdleTimeBeforeScaleDown", "PT5M")
                    )),
                    Map.entry("virtualMachineImage", Map.of("id", "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.Compute/galleries/myImageGallery/images/myImageDefinition/versions/0.0.1")),
                    Map.entry("vmPriority", "Dedicated"),
                    Map.entry("vmSize", "STANDARD_NC6")
                ))
            ))
            .resourceGroupName("testrg123")
            .workspaceName("workspaces123")
            .build());
    }
}
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Create a DataFactory Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var machineLearningCompute = new AzureNative.MachineLearningServices.MachineLearningCompute("machineLearningCompute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.DataFactoryArgs
        {
            ComputeType = "DataFactory",
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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package main
import (
	machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewMachineLearningCompute(ctx, "machineLearningCompute", &machinelearningservices.MachineLearningComputeArgs{
			ComputeName: pulumi.String("compute123"),
			Location:    pulumi.String("eastus"),
			Properties: machinelearningservices.DataFactory{
				ComputeType: "DataFactory",
			},
			ResourceGroupName: pulumi.String("testrg123"),
			WorkspaceName:     pulumi.String("workspaces123"),
		})
		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.MachineLearningCompute;
import com.pulumi.azurenative.machinelearningservices.MachineLearningComputeArgs;
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 machineLearningCompute = new MachineLearningCompute("machineLearningCompute", MachineLearningComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.of("computeType", "DataFactory"))
            .resourceGroupName("testrg123")
            .workspaceName("workspaces123")
            .build());
    }
}
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Create an ComputeInstance Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var machineLearningCompute = new AzureNative.MachineLearningServices.MachineLearningCompute("machineLearningCompute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.ComputeInstanceArgs
        {
            ComputeType = "ComputeInstance",
            Properties = new AzureNative.MachineLearningServices.Inputs.ComputeInstancePropertiesArgs
            {
                ApplicationSharingPolicy = "Personal",
                ComputeInstanceAuthorizationType = "personal",
                PersonalComputeInstanceSettings = new AzureNative.MachineLearningServices.Inputs.PersonalComputeInstanceSettingsArgs
                {
                    AssignedUser = new AzureNative.MachineLearningServices.Inputs.AssignedUserArgs
                    {
                        ObjectId = "00000000-0000-0000-0000-000000000000",
                        TenantId = "00000000-0000-0000-0000-000000000000",
                    },
                },
                SshSettings = new AzureNative.MachineLearningServices.Inputs.ComputeInstanceSshSettingsArgs
                {
                    SshPublicAccess = "Disabled",
                },
                Subnet = "test-subnet-resource-id",
                VmSize = "STANDARD_NC6",
            },
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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package main
import (
	machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewMachineLearningCompute(ctx, "machineLearningCompute", &machinelearningservices.MachineLearningComputeArgs{
			ComputeName: pulumi.String("compute123"),
			Location:    pulumi.String("eastus"),
			Properties: machinelearningservices.ComputeInstance{
				ComputeType: "ComputeInstance",
				Properties: machinelearningservices.ComputeInstanceProperties{
					ApplicationSharingPolicy:         "Personal",
					ComputeInstanceAuthorizationType: "personal",
					PersonalComputeInstanceSettings: machinelearningservices.PersonalComputeInstanceSettings{
						AssignedUser: machinelearningservices.AssignedUser{
							ObjectId: "00000000-0000-0000-0000-000000000000",
							TenantId: "00000000-0000-0000-0000-000000000000",
						},
					},
					SshSettings: machinelearningservices.ComputeInstanceSshSettings{
						SshPublicAccess: "Disabled",
					},
					Subnet: "test-subnet-resource-id",
					VmSize: "STANDARD_NC6",
				},
			},
			ResourceGroupName: pulumi.String("testrg123"),
			WorkspaceName:     pulumi.String("workspaces123"),
		})
		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.MachineLearningCompute;
import com.pulumi.azurenative.machinelearningservices.MachineLearningComputeArgs;
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 machineLearningCompute = new MachineLearningCompute("machineLearningCompute", MachineLearningComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.ofEntries(
                Map.entry("computeType", "ComputeInstance"),
                Map.entry("properties", Map.ofEntries(
                    Map.entry("applicationSharingPolicy", "Personal"),
                    Map.entry("computeInstanceAuthorizationType", "personal"),
                    Map.entry("personalComputeInstanceSettings", Map.of("assignedUser", Map.ofEntries(
                        Map.entry("objectId", "00000000-0000-0000-0000-000000000000"),
                        Map.entry("tenantId", "00000000-0000-0000-0000-000000000000")
                    ))),
                    Map.entry("sshSettings", Map.of("sshPublicAccess", "Disabled")),
                    Map.entry("subnet", "test-subnet-resource-id"),
                    Map.entry("vmSize", "STANDARD_NC6")
                ))
            ))
            .resourceGroupName("testrg123")
            .workspaceName("workspaces123")
            .build());
    }
}
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Create an ComputeInstance Compute with minimal inputs

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var machineLearningCompute = new AzureNative.MachineLearningServices.MachineLearningCompute("machineLearningCompute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.ComputeInstanceArgs
        {
            ComputeType = "ComputeInstance",
            Properties = new AzureNative.MachineLearningServices.Inputs.ComputeInstancePropertiesArgs
            {
                VmSize = "STANDARD_NC6",
            },
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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package main
import (
	machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewMachineLearningCompute(ctx, "machineLearningCompute", &machinelearningservices.MachineLearningComputeArgs{
			ComputeName: pulumi.String("compute123"),
			Location:    pulumi.String("eastus"),
			Properties: machinelearningservices.ComputeInstance{
				ComputeType: "ComputeInstance",
				Properties: machinelearningservices.ComputeInstanceProperties{
					VmSize: "STANDARD_NC6",
				},
			},
			ResourceGroupName: pulumi.String("testrg123"),
			WorkspaceName:     pulumi.String("workspaces123"),
		})
		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.MachineLearningCompute;
import com.pulumi.azurenative.machinelearningservices.MachineLearningComputeArgs;
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 machineLearningCompute = new MachineLearningCompute("machineLearningCompute", MachineLearningComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.ofEntries(
                Map.entry("computeType", "ComputeInstance"),
                Map.entry("properties", Map.of("vmSize", "STANDARD_NC6"))
            ))
            .resourceGroupName("testrg123")
            .workspaceName("workspaces123")
            .build());
    }
}
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Update a AKS Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var machineLearningCompute = new AzureNative.MachineLearningServices.MachineLearningCompute("machineLearningCompute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.AKSArgs
        {
            ComputeType = "AKS",
            Description = "some compute",
            Properties = new AzureNative.MachineLearningServices.Inputs.AKSPropertiesArgs
            {
                AgentCount = 4,
            },
            ResourceId = "/subscriptions/34adfa4f-cedf-4dc0-ba29-b6d1a69ab345/resourcegroups/testrg123/providers/Microsoft.ContainerService/managedClusters/compute123-56826-c9b00420020b2",
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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package main
import (
	machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewMachineLearningCompute(ctx, "machineLearningCompute", &machinelearningservices.MachineLearningComputeArgs{
			ComputeName: pulumi.String("compute123"),
			Location:    pulumi.String("eastus"),
			Properties: machinelearningservices.AKS{
				ComputeType: "AKS",
				Description: "some compute",
				Properties: machinelearningservices.AKSProperties{
					AgentCount: 4,
				},
				ResourceId: "/subscriptions/34adfa4f-cedf-4dc0-ba29-b6d1a69ab345/resourcegroups/testrg123/providers/Microsoft.ContainerService/managedClusters/compute123-56826-c9b00420020b2",
			},
			ResourceGroupName: pulumi.String("testrg123"),
			WorkspaceName:     pulumi.String("workspaces123"),
		})
		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.MachineLearningCompute;
import com.pulumi.azurenative.machinelearningservices.MachineLearningComputeArgs;
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 machineLearningCompute = new MachineLearningCompute("machineLearningCompute", MachineLearningComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.ofEntries(
                Map.entry("computeType", "AKS"),
                Map.entry("description", "some compute"),
                Map.entry("properties", Map.of("agentCount", 4)),
                Map.entry("resourceId", "/subscriptions/34adfa4f-cedf-4dc0-ba29-b6d1a69ab345/resourcegroups/testrg123/providers/Microsoft.ContainerService/managedClusters/compute123-56826-c9b00420020b2")
            ))
            .resourceGroupName("testrg123")
            .workspaceName("workspaces123")
            .build());
    }
}
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Update a AML Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var machineLearningCompute = new AzureNative.MachineLearningServices.MachineLearningCompute("machineLearningCompute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.AmlComputeArgs
        {
            ComputeType = "AmlCompute",
            Description = "some compute",
            Properties = new AzureNative.MachineLearningServices.Inputs.AmlComputePropertiesArgs
            {
                ScaleSettings = new AzureNative.MachineLearningServices.Inputs.ScaleSettingsArgs
                {
                    MaxNodeCount = 4,
                    MinNodeCount = 4,
                    NodeIdleTimeBeforeScaleDown = "PT5M",
                },
            },
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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package main
import (
	machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewMachineLearningCompute(ctx, "machineLearningCompute", &machinelearningservices.MachineLearningComputeArgs{
			ComputeName: pulumi.String("compute123"),
			Location:    pulumi.String("eastus"),
			Properties: machinelearningservices.AmlCompute{
				ComputeType: "AmlCompute",
				Description: "some compute",
				Properties: machinelearningservices.AmlComputeProperties{
					ScaleSettings: machinelearningservices.ScaleSettings{
						MaxNodeCount:                4,
						MinNodeCount:                4,
						NodeIdleTimeBeforeScaleDown: "PT5M",
					},
				},
			},
			ResourceGroupName: pulumi.String("testrg123"),
			WorkspaceName:     pulumi.String("workspaces123"),
		})
		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.MachineLearningCompute;
import com.pulumi.azurenative.machinelearningservices.MachineLearningComputeArgs;
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 machineLearningCompute = new MachineLearningCompute("machineLearningCompute", MachineLearningComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.ofEntries(
                Map.entry("computeType", "AmlCompute"),
                Map.entry("description", "some compute"),
                Map.entry("properties", Map.of("scaleSettings", Map.ofEntries(
                    Map.entry("maxNodeCount", 4),
                    Map.entry("minNodeCount", 4),
                    Map.entry("nodeIdleTimeBeforeScaleDown", "PT5M")
                )))
            ))
            .resourceGroupName("testrg123")
            .workspaceName("workspaces123")
            .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:MachineLearningCompute compute123 /subscriptions/34adfa4f-cedf-4dc0-ba29-b6d1a69ab345/resourceGroups/testrg123/providers/Microsoft.MachineLearningServices/workspaces/workspaces123/computes/compute123
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Constructors

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constructor(computeName: Output<String>? = null, identity: Output<IdentityArgs>? = null, location: Output<String>? = null, properties: Output<Any>? = null, resourceGroupName: Output<String>? = null, sku: Output<SkuArgs>? = null, tags: Output<Map<String, String>>? = null, workspaceName: Output<String>? = null)

Properties

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val computeName: Output<String>? = null

Name of the Azure Machine Learning compute.

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val identity: Output<IdentityArgs>? = null

The identity of the resource.

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val location: Output<String>? = null

Specifies the location of the resource.

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val properties: Output<Any>? = null

Compute properties

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val resourceGroupName: Output<String>? = null

Name of the resource group in which workspace is located.

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val sku: Output<SkuArgs>? = null

The sku of the workspace.

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val tags: Output<Map<String, String>>? = null

Contains resource tags defined as key/value pairs.

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val workspaceName: Output<String>? = null

Name of Azure Machine Learning workspace.

Functions

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open override fun toJava(): MachineLearningComputeArgs