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

OnlineDeployment

class OnlineDeployment : KotlinCustomResource

API Version: 2021-03-01-preview.

Example Usage

CreateOrUpdate K8S Online Deployment.

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var onlineDeployment = new AzureNative.MachineLearningServices.OnlineDeployment("onlineDeployment", new()
    {
        DeploymentName = "testDeployment",
        EndpointName = "testEndpoint",
        Identity = new AzureNative.MachineLearningServices.Inputs.ResourceIdentityArgs
        {
            Type = "UserAssigned",
            UserAssignedIdentities =
            {
                { "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", new AzureNative.MachineLearningServices.Inputs.UserAssignedIdentityMetaArgs
                {
                    ClientId = "string",
                    PrincipalId = "string",
                } },
            },
        },
        Kind = "string",
        Location = "string",
        Properties = new AzureNative.MachineLearningServices.Inputs.K8sOnlineDeploymentArgs
        {
            AppInsightsEnabled = true,
            CodeConfiguration = new AzureNative.MachineLearningServices.Inputs.CodeConfigurationArgs
            {
                CodeId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1",
                ScoringScript = "string",
            },
            ContainerResourceRequirements = new AzureNative.MachineLearningServices.Inputs.ContainerResourceRequirementsArgs
            {
                Cpu = 4,
                CpuLimit = 4,
                MemoryInGB = 64,
                MemoryInGBLimit = 64,
            },
            Description = "string",
            EndpointComputeType = "K8S",
            EnvironmentId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123",
            LivenessProbe = new AzureNative.MachineLearningServices.Inputs.ProbeSettingsArgs
            {
                FailureThreshold = 50,
                InitialDelay = "PT1M",
                Period = "PT1M",
                SuccessThreshold = 50,
                Timeout = "PT1M",
            },
            Model = new AzureNative.MachineLearningServices.Inputs.IdAssetReferenceArgs
            {
                AssetId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123",
                ReferenceType = "Id",
            },
            Properties =
            {
                { "additionalProp1", "string" },
                { "additionalProp2", "string" },
                { "additionalProp3", "string" },
            },
            RequestSettings = new AzureNative.MachineLearningServices.Inputs.OnlineRequestSettingsArgs
            {
                MaxConcurrentRequestsPerInstance = 5,
                MaxQueueWait = "PT1M",
                RequestTimeout = "PT1M",
            },
            ScaleSettings = new AzureNative.MachineLearningServices.Inputs.AutoScaleSettingsArgs
            {
                PollingInterval = "PT1M",
                ScaleType = "Auto",
                TargetUtilizationPercentage = 50,
            },
        },
        ResourceGroupName = "testrg123",
        Tags =
        {
            { "additionalProp1", "string" },
            { "additionalProp2", "string" },
            { "additionalProp3", "string" },
        },
        WorkspaceName = "workspace123",
    });
});
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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.NewOnlineDeployment(ctx, "onlineDeployment", &machinelearningservices.OnlineDeploymentArgs{
			DeploymentName: pulumi.String("testDeployment"),
			EndpointName:   pulumi.String("testEndpoint"),
			Identity: machinelearningservices.ResourceIdentityResponse{
				Type: pulumi.String("UserAssigned"),
				UserAssignedIdentities: machinelearningservices.UserAssignedIdentityMetaMap{
					"/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity": &machinelearningservices.UserAssignedIdentityMetaArgs{
						ClientId:    pulumi.String("string"),
						PrincipalId: pulumi.String("string"),
					},
				},
			},
			Kind:     pulumi.String("string"),
			Location: pulumi.String("string"),
			Properties: machinelearningservices.K8sOnlineDeployment{
				AppInsightsEnabled: true,
				CodeConfiguration: machinelearningservices.CodeConfiguration{
					CodeId:        "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1",
					ScoringScript: "string",
				},
				ContainerResourceRequirements: machinelearningservices.ContainerResourceRequirements{
					Cpu:             4,
					CpuLimit:        4,
					MemoryInGB:      64,
					MemoryInGBLimit: 64,
				},
				Description:         "string",
				EndpointComputeType: "K8S",
				EnvironmentId:       "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123",
				LivenessProbe: machinelearningservices.ProbeSettings{
					FailureThreshold: 50,
					InitialDelay:     "PT1M",
					Period:           "PT1M",
					SuccessThreshold: 50,
					Timeout:          "PT1M",
				},
				Model: machinelearningservices.IdAssetReference{
					AssetId:       "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123",
					ReferenceType: "Id",
				},
				Properties: map[string]interface{}{
					"additionalProp1": "string",
					"additionalProp2": "string",
					"additionalProp3": "string",
				},
				RequestSettings: machinelearningservices.OnlineRequestSettings{
					MaxConcurrentRequestsPerInstance: 5,
					MaxQueueWait:                     "PT1M",
					RequestTimeout:                   "PT1M",
				},
				ScaleSettings: machinelearningservices.AutoScaleSettings{
					PollingInterval:             "PT1M",
					ScaleType:                   "Auto",
					TargetUtilizationPercentage: 50,
				},
			},
			ResourceGroupName: pulumi.String("testrg123"),
			Tags: pulumi.StringMap{
				"additionalProp1": pulumi.String("string"),
				"additionalProp2": pulumi.String("string"),
				"additionalProp3": pulumi.String("string"),
			},
			WorkspaceName: pulumi.String("workspace123"),
		})
		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.OnlineDeployment;
import com.pulumi.azurenative.machinelearningservices.OnlineDeploymentArgs;
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 onlineDeployment = new OnlineDeployment("onlineDeployment", OnlineDeploymentArgs.builder()
            .deploymentName("testDeployment")
            .endpointName("testEndpoint")
            .identity(Map.ofEntries(
                Map.entry("type", "UserAssigned"),
                Map.entry("userAssignedIdentities", Map.of("/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", Map.ofEntries(
                    Map.entry("clientId", "string"),
                    Map.entry("principalId", "string")
                )))
            ))
            .kind("string")
            .location("string")
            .properties(Map.ofEntries(
                Map.entry("appInsightsEnabled", true),
                Map.entry("codeConfiguration", Map.ofEntries(
                    Map.entry("codeId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1"),
                    Map.entry("scoringScript", "string")
                )),
                Map.entry("containerResourceRequirements", Map.ofEntries(
                    Map.entry("cpu", 4),
                    Map.entry("cpuLimit", 4),
                    Map.entry("memoryInGB", 64),
                    Map.entry("memoryInGBLimit", 64)
                )),
                Map.entry("description", "string"),
                Map.entry("endpointComputeType", "K8S"),
                Map.entry("environmentId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123"),
                Map.entry("livenessProbe", Map.ofEntries(
                    Map.entry("failureThreshold", 50),
                    Map.entry("initialDelay", "PT1M"),
                    Map.entry("period", "PT1M"),
                    Map.entry("successThreshold", 50),
                    Map.entry("timeout", "PT1M")
                )),
                Map.entry("model", Map.ofEntries(
                    Map.entry("assetId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123"),
                    Map.entry("referenceType", "Id")
                )),
                Map.entry("properties", K8sOnlineDeploymentArgs.builder()
                    .additionalProp1("string")
                    .additionalProp2("string")
                    .additionalProp3("string")
                    .build()),
                Map.entry("requestSettings", Map.ofEntries(
                    Map.entry("maxConcurrentRequestsPerInstance", 5),
                    Map.entry("maxQueueWait", "PT1M"),
                    Map.entry("requestTimeout", "PT1M")
                )),
                Map.entry("scaleSettings", Map.ofEntries(
                    Map.entry("pollingInterval", "PT1M"),
                    Map.entry("scaleType", "Auto"),
                    Map.entry("targetUtilizationPercentage", 50)
                ))
            ))
            .resourceGroupName("testrg123")
            .tags(Map.ofEntries(
                Map.entry("additionalProp1", "string"),
                Map.entry("additionalProp2", "string"),
                Map.entry("additionalProp3", "string")
            ))
            .workspaceName("workspace123")
            .build());
    }
}
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CreateOrUpdate Managed Online Deployment.

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var onlineDeployment = new AzureNative.MachineLearningServices.OnlineDeployment("onlineDeployment", new()
    {
        DeploymentName = "testDeployment",
        EndpointName = "testEndpoint",
        Identity = new AzureNative.MachineLearningServices.Inputs.ResourceIdentityArgs
        {
            Type = "UserAssigned",
            UserAssignedIdentities =
            {
                { "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", new AzureNative.MachineLearningServices.Inputs.UserAssignedIdentityMetaArgs
                {
                    ClientId = "string",
                    PrincipalId = "string",
                } },
            },
        },
        Kind = "string",
        Location = "string",
        Properties = new AzureNative.MachineLearningServices.Inputs.ManagedOnlineDeploymentArgs
        {
            AppInsightsEnabled = true,
            CodeConfiguration = new AzureNative.MachineLearningServices.Inputs.CodeConfigurationArgs
            {
                CodeId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1",
                ScoringScript = "string",
            },
            Description = "string",
            EndpointComputeType = "Managed",
            EnvironmentId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123",
            LivenessProbe = new AzureNative.MachineLearningServices.Inputs.ProbeSettingsArgs
            {
                FailureThreshold = 50,
                InitialDelay = "PT1M",
                Period = "PT1M",
                SuccessThreshold = 50,
                Timeout = "PT1M",
            },
            Model = new AzureNative.MachineLearningServices.Inputs.IdAssetReferenceArgs
            {
                AssetId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123",
                ReferenceType = "Id",
            },
            Properties =
            {
                { "additionalProp1", "string" },
                { "additionalProp2", "string" },
                { "additionalProp3", "string" },
            },
            RequestSettings = new AzureNative.MachineLearningServices.Inputs.OnlineRequestSettingsArgs
            {
                MaxConcurrentRequestsPerInstance = 5,
                MaxQueueWait = "PT1M",
                RequestTimeout = "PT1M",
            },
            ScaleSettings = new AzureNative.MachineLearningServices.Inputs.AutoScaleSettingsArgs
            {
                PollingInterval = "PT1M",
                ScaleType = "Auto",
                TargetUtilizationPercentage = 50,
            },
        },
        ResourceGroupName = "testrg123",
        Tags =
        {
            { "additionalProp1", "string" },
            { "additionalProp2", "string" },
            { "additionalProp3", "string" },
        },
        WorkspaceName = "workspace123",
    });
});
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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.NewOnlineDeployment(ctx, "onlineDeployment", &machinelearningservices.OnlineDeploymentArgs{
			DeploymentName: pulumi.String("testDeployment"),
			EndpointName:   pulumi.String("testEndpoint"),
			Identity: machinelearningservices.ResourceIdentityResponse{
				Type: pulumi.String("UserAssigned"),
				UserAssignedIdentities: machinelearningservices.UserAssignedIdentityMetaMap{
					"/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity": &machinelearningservices.UserAssignedIdentityMetaArgs{
						ClientId:    pulumi.String("string"),
						PrincipalId: pulumi.String("string"),
					},
				},
			},
			Kind:     pulumi.String("string"),
			Location: pulumi.String("string"),
			Properties: machinelearningservices.ManagedOnlineDeployment{
				AppInsightsEnabled: true,
				CodeConfiguration: machinelearningservices.CodeConfiguration{
					CodeId:        "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1",
					ScoringScript: "string",
				},
				Description:         "string",
				EndpointComputeType: "Managed",
				EnvironmentId:       "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123",
				LivenessProbe: machinelearningservices.ProbeSettings{
					FailureThreshold: 50,
					InitialDelay:     "PT1M",
					Period:           "PT1M",
					SuccessThreshold: 50,
					Timeout:          "PT1M",
				},
				Model: machinelearningservices.IdAssetReference{
					AssetId:       "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123",
					ReferenceType: "Id",
				},
				Properties: map[string]interface{}{
					"additionalProp1": "string",
					"additionalProp2": "string",
					"additionalProp3": "string",
				},
				RequestSettings: machinelearningservices.OnlineRequestSettings{
					MaxConcurrentRequestsPerInstance: 5,
					MaxQueueWait:                     "PT1M",
					RequestTimeout:                   "PT1M",
				},
				ScaleSettings: machinelearningservices.AutoScaleSettings{
					PollingInterval:             "PT1M",
					ScaleType:                   "Auto",
					TargetUtilizationPercentage: 50,
				},
			},
			ResourceGroupName: pulumi.String("testrg123"),
			Tags: pulumi.StringMap{
				"additionalProp1": pulumi.String("string"),
				"additionalProp2": pulumi.String("string"),
				"additionalProp3": pulumi.String("string"),
			},
			WorkspaceName: pulumi.String("workspace123"),
		})
		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.OnlineDeployment;
import com.pulumi.azurenative.machinelearningservices.OnlineDeploymentArgs;
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 onlineDeployment = new OnlineDeployment("onlineDeployment", OnlineDeploymentArgs.builder()
            .deploymentName("testDeployment")
            .endpointName("testEndpoint")
            .identity(Map.ofEntries(
                Map.entry("type", "UserAssigned"),
                Map.entry("userAssignedIdentities", Map.of("/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", Map.ofEntries(
                    Map.entry("clientId", "string"),
                    Map.entry("principalId", "string")
                )))
            ))
            .kind("string")
            .location("string")
            .properties(Map.ofEntries(
                Map.entry("appInsightsEnabled", true),
                Map.entry("codeConfiguration", Map.ofEntries(
                    Map.entry("codeId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1"),
                    Map.entry("scoringScript", "string")
                )),
                Map.entry("description", "string"),
                Map.entry("endpointComputeType", "Managed"),
                Map.entry("environmentId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123"),
                Map.entry("livenessProbe", Map.ofEntries(
                    Map.entry("failureThreshold", 50),
                    Map.entry("initialDelay", "PT1M"),
                    Map.entry("period", "PT1M"),
                    Map.entry("successThreshold", 50),
                    Map.entry("timeout", "PT1M")
                )),
                Map.entry("model", Map.ofEntries(
                    Map.entry("assetId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123"),
                    Map.entry("referenceType", "Id")
                )),
                Map.entry("properties", K8sOnlineDeploymentArgs.builder()
                    .additionalProp1("string")
                    .additionalProp2("string")
                    .additionalProp3("string")
                    .build()),
                Map.entry("requestSettings", Map.ofEntries(
                    Map.entry("maxConcurrentRequestsPerInstance", 5),
                    Map.entry("maxQueueWait", "PT1M"),
                    Map.entry("requestTimeout", "PT1M")
                )),
                Map.entry("scaleSettings", Map.ofEntries(
                    Map.entry("pollingInterval", "PT1M"),
                    Map.entry("scaleType", "Auto"),
                    Map.entry("targetUtilizationPercentage", 50)
                ))
            ))
            .resourceGroupName("testrg123")
            .tags(Map.ofEntries(
                Map.entry("additionalProp1", "string"),
                Map.entry("additionalProp2", "string"),
                Map.entry("additionalProp3", "string")
            ))
            .workspaceName("workspace123")
            .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:OnlineDeployment testDeployment /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/testrg123/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/onlineEndpoints/testEndpoint/deployments/testDeployment
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Properties

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

Service identity associated with a resource.

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val kind: Output<String>?

Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.

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val location: Output<String>

The geo-location where the resource lives

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val name: Output<String>

The name of the resource

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val properties: Output<Either<K8sOnlineDeploymentResponse, ManagedOnlineDeploymentResponse>>

Required Additional attributes of the entity.

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val pulumiChildResources: Set<KotlinResource>
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val systemData: Output<SystemDataResponse>

System data associated with resource provider

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

Resource tags.

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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>