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

Compute

class Compute : KotlinCustomResource

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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Properties

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val id: Output<String>
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val identity: Output<ManagedServiceIdentityResponse>?

The identity of the resource.

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val location: Output<String>?

Specifies the location of the resource.

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val name: Output<String>

The name of the resource

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val properties: Output<Any>

Compute properties

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val pulumiChildResources: Set<KotlinResource>
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val sku: Output<SkuResponse>?

The sku of the workspace.

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val systemData: Output<SystemDataResponse>

Azure Resource Manager metadata containing createdBy and modifiedBy information.

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

Contains resource tags defined as key/value pairs.

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val type: Output<String>

The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"

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val urn: Output<String>