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

ComputeArgs

data class ComputeArgs(val computeName: Output<String>? = null, val identity: Output<ManagedServiceIdentityArgs>? = 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<ComputeArgs>

Machine Learning compute object wrapped into ARM resource envelope. Azure REST API version: 2023-04-01. Other available API versions: 2022-01-01-preview, 2023-04-01-preview, 2023-06-01-preview, 2023-08-01-preview, 2023-10-01.

Example Usage

Attach a Kubernetes Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var compute = new AzureNative.MachineLearningServices.Compute("compute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.KubernetesArgs
        {
            ComputeType = "Kubernetes",
            Description = "some compute",
            Properties = new AzureNative.MachineLearningServices.Inputs.KubernetesPropertiesArgs
            {
                DefaultInstanceType = "defaultInstanceType",
                InstanceTypes =
                {
                    { "defaultInstanceType", new AzureNative.MachineLearningServices.Inputs.InstanceTypeSchemaArgs
                    {
                        Resources = new AzureNative.MachineLearningServices.Inputs.InstanceTypeSchemaResourcesArgs
                        {
                            Limits =
                            {
                                { "cpu", "1" },
                                { "memory", "4Gi" },
                                { "nvidia.com/gpu", null },
                            },
                            Requests =
                            {
                                { "cpu", "1" },
                                { "memory", "4Gi" },
                                { "nvidia.com/gpu", null },
                            },
                        },
                    } },
                },
                Namespace = "default",
            },
            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 (
	"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.NewCompute(ctx, "compute", &machinelearningservices.ComputeArgs{
ComputeName: pulumi.String("compute123"),
Location: pulumi.String("eastus"),
Properties: machinelearningservices.Kubernetes{
ComputeType: "Kubernetes",
Description: "some compute",
Properties: machinelearningservices.KubernetesProperties{
DefaultInstanceType: "defaultInstanceType",
InstanceTypes: interface{}{
DefaultInstanceType: machinelearningservices.InstanceTypeSchema{
Resources: machinelearningservices.InstanceTypeSchemaResources{
Limits: interface{}{
Cpu: "1",
Memory: "4Gi",
Nvidia.com/gpu: nil,
},
Requests: interface{}{
Cpu: "1",
Memory: "4Gi",
Nvidia.com/gpu: nil,
},
},
},
},
Namespace: "default",
},
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.Compute;
import com.pulumi.azurenative.machinelearningservices.ComputeArgs;
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 compute = new Compute("compute", ComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.ofEntries(
                Map.entry("computeType", "Kubernetes"),
                Map.entry("description", "some compute"),
                Map.entry("properties", Map.ofEntries(
                    Map.entry("defaultInstanceType", "defaultInstanceType"),
                    Map.entry("instanceTypes", Map.of("defaultInstanceType", Map.of("resources", Map.ofEntries(
                        Map.entry("limits", Map.ofEntries(
                            Map.entry("cpu", "1"),
                            Map.entry("memory", "4Gi"),
                            Map.entry("nvidia.com/gpu", null)
                        )),
                        Map.entry("requests", Map.ofEntries(
                            Map.entry("cpu", "1"),
                            Map.entry("memory", "4Gi"),
                            Map.entry("nvidia.com/gpu", null)
                        ))
                    )))),
                    Map.entry("namespace", "default")
                )),
                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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Create a AML Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var compute = new AzureNative.MachineLearningServices.Compute("compute", 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 (
	"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.NewCompute(ctx, "compute", &machinelearningservices.ComputeArgs{
			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.Compute;
import com.pulumi.azurenative.machinelearningservices.ComputeArgs;
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 compute = new Compute("compute", ComputeArgs.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 compute = new AzureNative.MachineLearningServices.Compute("compute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.DataFactoryArgs
        {
            ComputeType = "DataFactory",
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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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.NewCompute(ctx, "compute", &machinelearningservices.ComputeArgs{
			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.Compute;
import com.pulumi.azurenative.machinelearningservices.ComputeArgs;
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 compute = new Compute("compute", ComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.of("computeType", "DataFactory"))
            .resourceGroupName("testrg123")
            .workspaceName("workspaces123")
            .build());
    }
}
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Create an AKS Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var compute = new AzureNative.MachineLearningServices.Compute("compute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.AKSArgs
        {
            ComputeType = "AKS",
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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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.NewCompute(ctx, "compute", &machinelearningservices.ComputeArgs{
			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.Compute;
import com.pulumi.azurenative.machinelearningservices.ComputeArgs;
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 compute = new Compute("compute", ComputeArgs.builder()
            .computeName("compute123")
            .location("eastus")
            .properties(Map.of("computeType", "AKS"))
            .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 compute = new AzureNative.MachineLearningServices.Compute("compute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.ComputeInstanceArgs
        {
            ComputeType = "ComputeInstance",
            Properties = new AzureNative.MachineLearningServices.Inputs.ComputeInstancePropertiesArgs
            {
                ApplicationSharingPolicy = "Personal",
                ComputeInstanceAuthorizationType = "personal",
                CustomServices = new[]
                {
                    new AzureNative.MachineLearningServices.Inputs.CustomServiceArgs
                    {
                        Docker = new AzureNative.MachineLearningServices.Inputs.DockerArgs
                        {
                            Privileged = true,
                        },
                        Endpoints = new[]
                        {
                            new AzureNative.MachineLearningServices.Inputs.EndpointArgs
                            {
                                Name = "connect",
                                Protocol = "http",
                                Published = 8787,
                                Target = 8787,
                            },
                        },
                        EnvironmentVariables =
                        {
                            { "test_variable", new AzureNative.MachineLearningServices.Inputs.EnvironmentVariableArgs
                            {
                                Type = "local",
                                Value = "test_value",
                            } },
                        },
                        Image = new AzureNative.MachineLearningServices.Inputs.ImageArgs
                        {
                            Reference = "ghcr.io/azure/rocker-rstudio-ml-verse:latest",
                            Type = "docker",
                        },
                        Name = "rstudio",
                        Volumes = new[]
                        {
                            new AzureNative.MachineLearningServices.Inputs.VolumeDefinitionArgs
                            {
                                ReadOnly = false,
                                Source = "/home/azureuser/cloudfiles",
                                Target = "/home/azureuser/cloudfiles",
                                Type = "bind",
                            },
                        },
                    },
                },
                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 = new AzureNative.MachineLearningServices.Inputs.ResourceIdArgs
                {
                    Id = "test-subnet-resource-id",
                },
                VmSize = "STANDARD_NC6",
            },
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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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.NewCompute(ctx, "compute", &machinelearningservices.ComputeArgs{
			ComputeName: pulumi.String("compute123"),
			Location:    pulumi.String("eastus"),
			Properties: machinelearningservices.ComputeInstance{
				ComputeType: "ComputeInstance",
				Properties: machinelearningservices.ComputeInstanceProperties{
					ApplicationSharingPolicy:         "Personal",
					ComputeInstanceAuthorizationType: "personal",
					CustomServices: []machinelearningservices.CustomService{
						{
							Docker: {
								Privileged: true,
							},
							Endpoints: []machinelearningservices.Endpoint{
								{
									Name:      "connect",
									Protocol:  "http",
									Published: 8787,
									Target:    8787,
								},
							},
							EnvironmentVariables: {
								Test_variable: {
									Type:  "local",
									Value: "test_value",
								},
							},
							Image: {
								Reference: "ghcr.io/azure/rocker-rstudio-ml-verse:latest",
								Type:      "docker",
							},
							Name: "rstudio",
							Volumes: []machinelearningservices.VolumeDefinition{
								{
									ReadOnly: false,
									Source:   "/home/azureuser/cloudfiles",
									Target:   "/home/azureuser/cloudfiles",
									Type:     "bind",
								},
							},
						},
					},
					PersonalComputeInstanceSettings: machinelearningservices.PersonalComputeInstanceSettings{
						AssignedUser: machinelearningservices.AssignedUser{
							ObjectId: "00000000-0000-0000-0000-000000000000",
							TenantId: "00000000-0000-0000-0000-000000000000",
						},
					},
					SshSettings: machinelearningservices.ComputeInstanceSshSettings{
						SshPublicAccess: "Disabled",
					},
					Subnet: machinelearningservices.ResourceId{
						Id: "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.Compute;
import com.pulumi.azurenative.machinelearningservices.ComputeArgs;
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 compute = new Compute("compute", ComputeArgs.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("customServices", Map.ofEntries(
                        Map.entry("docker", Map.of("privileged", true)),
                        Map.entry("endpoints", Map.ofEntries(
                            Map.entry("name", "connect"),
                            Map.entry("protocol", "http"),
                            Map.entry("published", 8787),
                            Map.entry("target", 8787)
                        )),
                        Map.entry("environmentVariables", Map.of("test_variable", Map.ofEntries(
                            Map.entry("type", "local"),
                            Map.entry("value", "test_value")
                        ))),
                        Map.entry("image", Map.ofEntries(
                            Map.entry("reference", "ghcr.io/azure/rocker-rstudio-ml-verse:latest"),
                            Map.entry("type", "docker")
                        )),
                        Map.entry("name", "rstudio"),
                        Map.entry("volumes", Map.ofEntries(
                            Map.entry("readOnly", false),
                            Map.entry("source", "/home/azureuser/cloudfiles"),
                            Map.entry("target", "/home/azureuser/cloudfiles"),
                            Map.entry("type", "bind")
                        ))
                    )),
                    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", Map.of("id", "test-subnet-resource-id")),
                    Map.entry("vmSize", "STANDARD_NC6")
                ))
            ))
            .resourceGroupName("testrg123")
            .workspaceName("workspaces123")
            .build());
    }
}
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Create an ComputeInstance Compute with Schedules

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var compute = new AzureNative.MachineLearningServices.Compute("compute", 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",
                    },
                },
                Schedules = new AzureNative.MachineLearningServices.Inputs.ComputeSchedulesArgs
                {
                    ComputeStartStop = new[]
                    {
                        new AzureNative.MachineLearningServices.Inputs.ComputeStartStopScheduleArgs
                        {
                            Action = "Stop",
                            Cron = new AzureNative.MachineLearningServices.Inputs.CronArgs
                            {
                                Expression = "0 18 * * *",
                                StartTime = "2021-04-23T01:30:00",
                                TimeZone = "Pacific Standard Time",
                            },
                            Status = "Enabled",
                            TriggerType = "Cron",
                        },
                    },
                },
                SshSettings = new AzureNative.MachineLearningServices.Inputs.ComputeInstanceSshSettingsArgs
                {
                    SshPublicAccess = "Disabled",
                },
                VmSize = "STANDARD_NC6",
            },
        },
        ResourceGroupName = "testrg123",
        WorkspaceName = "workspaces123",
    });
});
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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.NewCompute(ctx, "compute", &machinelearningservices.ComputeArgs{
			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",
						},
					},
					Schedules: machinelearningservices.ComputeSchedules{
						ComputeStartStop: []machinelearningservices.ComputeStartStopSchedule{
							{
								Action: "Stop",
								Cron: {
									Expression: "0 18 * * *",
									StartTime:  "2021-04-23T01:30:00",
									TimeZone:   "Pacific Standard Time",
								},
								Status:      "Enabled",
								TriggerType: "Cron",
							},
						},
					},
					SshSettings: machinelearningservices.ComputeInstanceSshSettings{
						SshPublicAccess: "Disabled",
					},
					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.Compute;
import com.pulumi.azurenative.machinelearningservices.ComputeArgs;
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 compute = new Compute("compute", ComputeArgs.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("schedules", Map.of("computeStartStop", Map.ofEntries(
                        Map.entry("action", "Stop"),
                        Map.entry("cron", Map.ofEntries(
                            Map.entry("expression", "0 18 * * *"),
                            Map.entry("startTime", "2021-04-23T01:30:00"),
                            Map.entry("timeZone", "Pacific Standard Time")
                        )),
                        Map.entry("status", "Enabled"),
                        Map.entry("triggerType", "Cron")
                    ))),
                    Map.entry("sshSettings", Map.of("sshPublicAccess", "Disabled")),
                    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 compute = new AzureNative.MachineLearningServices.Compute("compute", 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 (
	"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.NewCompute(ctx, "compute", &machinelearningservices.ComputeArgs{
			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.Compute;
import com.pulumi.azurenative.machinelearningservices.ComputeArgs;
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 compute = new Compute("compute", ComputeArgs.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 AML Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var compute = new AzureNative.MachineLearningServices.Compute("compute", 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 (
	"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.NewCompute(ctx, "compute", &machinelearningservices.ComputeArgs{
			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.Compute;
import com.pulumi.azurenative.machinelearningservices.ComputeArgs;
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 compute = new Compute("compute", ComputeArgs.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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Update an AKS Compute

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var compute = new AzureNative.MachineLearningServices.Compute("compute", new()
    {
        ComputeName = "compute123",
        Location = "eastus",
        Properties = new AzureNative.MachineLearningServices.Inputs.AKSArgs
        {
            ComputeType = "AKS",
            Description = "some compute",
            Properties = new AzureNative.MachineLearningServices.Inputs.AKSSchemaPropertiesArgs
            {
                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 (
	"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.NewCompute(ctx, "compute", &machinelearningservices.ComputeArgs{
			ComputeName: pulumi.String("compute123"),
			Location:    pulumi.String("eastus"),
			Properties: machinelearningservices.AKS{
				ComputeType: "AKS",
				Description: "some compute",
				Properties: machinelearningservices.AKSSchemaProperties{
					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.Compute;
import com.pulumi.azurenative.machinelearningservices.ComputeArgs;
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 compute = new Compute("compute", ComputeArgs.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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Import

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

$ pulumi import azure-native:machinelearningservices:Compute compute123 /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}
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Constructors

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fun ComputeArgs(computeName: Output<String>? = null, identity: Output<ManagedServiceIdentityArgs>? = 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)

Functions

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open override fun toJava(): ComputeArgs

Properties

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val computeName: Output<String>? = null

Name of the Azure Machine Learning compute.

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val identity: Output<ManagedServiceIdentityArgs>? = 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

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

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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.