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This is the latest version of Azure Native. Use the Azure Native v2 docs if using the v2 version of this package.
Azure Native v3.2.0 published on Monday, Apr 14, 2025 by Pulumi
pulumi/pulumi-azure-native

azure-native.machinelearningservices.OnlineDeployment

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This is the latest version of Azure Native. Use the Azure Native v2 docs if using the v2 version of this package.
Azure Native v3.2.0 published on Monday, Apr 14, 2025 by Pulumi
pulumi/pulumi-azure-native

Uses Azure REST API version 2024-10-01. In version 2.x of the Azure Native provider, it used API version 2023-04-01.

Other available API versions: 2021-03-01-preview, 2022-02-01-preview, 2022-05-01, 2022-06-01-preview, 2022-10-01, 2022-10-01-preview, 2022-12-01-preview, 2023-02-01-preview, 2023-04-01, 2023-04-01-preview, 2023-06-01-preview, 2023-08-01-preview, 2023-10-01, 2024-01-01-preview, 2024-04-01, 2024-07-01-preview, 2024-10-01-preview, 2025-01-01-preview. These can be accessed by generating a local SDK package using the CLI command pulumi package add azure-native machinelearningservices [ApiVersion]. See the version guide for details.

Import

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

$ pulumi import azure-native:machinelearningservices:OnlineDeployment string /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/deployments/{deploymentName}
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Create OnlineDeployment Resource

Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

Constructor syntax

new OnlineDeployment(name: string, args: OnlineDeploymentArgs, opts?: CustomResourceOptions);
@overload
def OnlineDeployment(resource_name: str,
                     args: OnlineDeploymentArgs,
                     opts: Optional[ResourceOptions] = None)

@overload
def OnlineDeployment(resource_name: str,
                     opts: Optional[ResourceOptions] = None,
                     endpoint_name: Optional[str] = None,
                     online_deployment_properties: Optional[Union[KubernetesOnlineDeploymentArgs, ManagedOnlineDeploymentArgs]] = None,
                     resource_group_name: Optional[str] = None,
                     workspace_name: Optional[str] = None,
                     deployment_name: Optional[str] = None,
                     identity: Optional[ManagedServiceIdentityArgs] = None,
                     kind: Optional[str] = None,
                     location: Optional[str] = None,
                     sku: Optional[SkuArgs] = None,
                     tags: Optional[Mapping[str, str]] = None)
func NewOnlineDeployment(ctx *Context, name string, args OnlineDeploymentArgs, opts ...ResourceOption) (*OnlineDeployment, error)
public OnlineDeployment(string name, OnlineDeploymentArgs args, CustomResourceOptions? opts = null)
public OnlineDeployment(String name, OnlineDeploymentArgs args)
public OnlineDeployment(String name, OnlineDeploymentArgs args, CustomResourceOptions options)

type: azure-native:machinelearningservices:OnlineDeployment
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

Parameters

name This property is required. string
The unique name of the resource.
args This property is required. OnlineDeploymentArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
resource_name This property is required. str
The unique name of the resource.
args This property is required. OnlineDeploymentArgs
The arguments to resource properties.
opts ResourceOptions
Bag of options to control resource's behavior.
ctx Context
Context object for the current deployment.
name This property is required. string
The unique name of the resource.
args This property is required. OnlineDeploymentArgs
The arguments to resource properties.
opts ResourceOption
Bag of options to control resource's behavior.
name This property is required. string
The unique name of the resource.
args This property is required. OnlineDeploymentArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
name This property is required. String
The unique name of the resource.
args This property is required. OnlineDeploymentArgs
The arguments to resource properties.
options CustomResourceOptions
Bag of options to control resource's behavior.

Constructor example

The following reference example uses placeholder values for all input properties.

var onlineDeploymentResource = new AzureNative.MachineLearningServices.OnlineDeployment("onlineDeploymentResource", new()
{
    EndpointName = "string",
    OnlineDeploymentProperties = new AzureNative.MachineLearningServices.Inputs.KubernetesOnlineDeploymentArgs
    {
        EndpointComputeType = "Kubernetes",
        EnvironmentVariables = 
        {
            { "string", "string" },
        },
        LivenessProbe = new AzureNative.MachineLearningServices.Inputs.ProbeSettingsArgs
        {
            FailureThreshold = 0,
            InitialDelay = "string",
            Period = "string",
            SuccessThreshold = 0,
            Timeout = "string",
        },
        DataCollector = new AzureNative.MachineLearningServices.Inputs.DataCollectorArgs
        {
            Collections = 
            {
                { "string", new AzureNative.MachineLearningServices.Inputs.CollectionArgs
                {
                    ClientId = "string",
                    DataCollectionMode = "string",
                    DataId = "string",
                    SamplingRate = 0,
                } },
            },
            RequestLogging = new AzureNative.MachineLearningServices.Inputs.RequestLoggingArgs
            {
                CaptureHeaders = new[]
                {
                    "string",
                },
            },
            RollingRate = "string",
        },
        Description = "string",
        EgressPublicNetworkAccess = "string",
        CodeConfiguration = new AzureNative.MachineLearningServices.Inputs.CodeConfigurationArgs
        {
            ScoringScript = "string",
            CodeId = "string",
        },
        EnvironmentId = "string",
        AppInsightsEnabled = false,
        ContainerResourceRequirements = new AzureNative.MachineLearningServices.Inputs.ContainerResourceRequirementsArgs
        {
            ContainerResourceLimits = new AzureNative.MachineLearningServices.Inputs.ContainerResourceSettingsArgs
            {
                Cpu = "string",
                Gpu = "string",
                Memory = "string",
            },
            ContainerResourceRequests = new AzureNative.MachineLearningServices.Inputs.ContainerResourceSettingsArgs
            {
                Cpu = "string",
                Gpu = "string",
                Memory = "string",
            },
        },
        Model = "string",
        InstanceType = "string",
        ModelMountPath = "string",
        Properties = 
        {
            { "string", "string" },
        },
        ReadinessProbe = new AzureNative.MachineLearningServices.Inputs.ProbeSettingsArgs
        {
            FailureThreshold = 0,
            InitialDelay = "string",
            Period = "string",
            SuccessThreshold = 0,
            Timeout = "string",
        },
        RequestSettings = new AzureNative.MachineLearningServices.Inputs.OnlineRequestSettingsArgs
        {
            MaxConcurrentRequestsPerInstance = 0,
            MaxQueueWait = "string",
            RequestTimeout = "string",
        },
        ScaleSettings = new AzureNative.MachineLearningServices.Inputs.DefaultScaleSettingsArgs
        {
            ScaleType = "Default",
        },
        StartupProbe = new AzureNative.MachineLearningServices.Inputs.ProbeSettingsArgs
        {
            FailureThreshold = 0,
            InitialDelay = "string",
            Period = "string",
            SuccessThreshold = 0,
            Timeout = "string",
        },
    },
    ResourceGroupName = "string",
    WorkspaceName = "string",
    DeploymentName = "string",
    Identity = new AzureNative.MachineLearningServices.Inputs.ManagedServiceIdentityArgs
    {
        Type = "string",
        UserAssignedIdentities = new[]
        {
            "string",
        },
    },
    Kind = "string",
    Location = "string",
    Sku = new AzureNative.MachineLearningServices.Inputs.SkuArgs
    {
        Name = "string",
        Capacity = 0,
        Family = "string",
        Size = "string",
        Tier = AzureNative.MachineLearningServices.SkuTier.Free,
    },
    Tags = 
    {
        { "string", "string" },
    },
});
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example, err := machinelearningservices.NewOnlineDeployment(ctx, "onlineDeploymentResource", &machinelearningservices.OnlineDeploymentArgs{
	EndpointName: pulumi.String("string"),
	OnlineDeploymentProperties: &machinelearningservices.KubernetesOnlineDeploymentArgs{
		EndpointComputeType: pulumi.String("Kubernetes"),
		EnvironmentVariables: pulumi.StringMap{
			"string": pulumi.String("string"),
		},
		LivenessProbe: &machinelearningservices.ProbeSettingsArgs{
			FailureThreshold: pulumi.Int(0),
			InitialDelay:     pulumi.String("string"),
			Period:           pulumi.String("string"),
			SuccessThreshold: pulumi.Int(0),
			Timeout:          pulumi.String("string"),
		},
		DataCollector: &machinelearningservices.DataCollectorArgs{
			Collections: machinelearningservices.CollectionMap{
				"string": &machinelearningservices.CollectionArgs{
					ClientId:           pulumi.String("string"),
					DataCollectionMode: pulumi.String("string"),
					DataId:             pulumi.String("string"),
					SamplingRate:       pulumi.Float64(0),
				},
			},
			RequestLogging: &machinelearningservices.RequestLoggingArgs{
				CaptureHeaders: pulumi.StringArray{
					pulumi.String("string"),
				},
			},
			RollingRate: pulumi.String("string"),
		},
		Description:               pulumi.String("string"),
		EgressPublicNetworkAccess: pulumi.String("string"),
		CodeConfiguration: &machinelearningservices.CodeConfigurationArgs{
			ScoringScript: pulumi.String("string"),
			CodeId:        pulumi.String("string"),
		},
		EnvironmentId:      pulumi.String("string"),
		AppInsightsEnabled: pulumi.Bool(false),
		ContainerResourceRequirements: &machinelearningservices.ContainerResourceRequirementsArgs{
			ContainerResourceLimits: &machinelearningservices.ContainerResourceSettingsArgs{
				Cpu:    pulumi.String("string"),
				Gpu:    pulumi.String("string"),
				Memory: pulumi.String("string"),
			},
			ContainerResourceRequests: &machinelearningservices.ContainerResourceSettingsArgs{
				Cpu:    pulumi.String("string"),
				Gpu:    pulumi.String("string"),
				Memory: pulumi.String("string"),
			},
		},
		Model:          pulumi.String("string"),
		InstanceType:   pulumi.String("string"),
		ModelMountPath: pulumi.String("string"),
		Properties: pulumi.StringMap{
			"string": pulumi.String("string"),
		},
		ReadinessProbe: &machinelearningservices.ProbeSettingsArgs{
			FailureThreshold: pulumi.Int(0),
			InitialDelay:     pulumi.String("string"),
			Period:           pulumi.String("string"),
			SuccessThreshold: pulumi.Int(0),
			Timeout:          pulumi.String("string"),
		},
		RequestSettings: &machinelearningservices.OnlineRequestSettingsArgs{
			MaxConcurrentRequestsPerInstance: pulumi.Int(0),
			MaxQueueWait:                     pulumi.String("string"),
			RequestTimeout:                   pulumi.String("string"),
		},
		ScaleSettings: machinelearningservices.DefaultScaleSettings{
			ScaleType: "Default",
		},
		StartupProbe: &machinelearningservices.ProbeSettingsArgs{
			FailureThreshold: pulumi.Int(0),
			InitialDelay:     pulumi.String("string"),
			Period:           pulumi.String("string"),
			SuccessThreshold: pulumi.Int(0),
			Timeout:          pulumi.String("string"),
		},
	},
	ResourceGroupName: pulumi.String("string"),
	WorkspaceName:     pulumi.String("string"),
	DeploymentName:    pulumi.String("string"),
	Identity: &machinelearningservices.ManagedServiceIdentityArgs{
		Type: pulumi.String("string"),
		UserAssignedIdentities: pulumi.StringArray{
			pulumi.String("string"),
		},
	},
	Kind:     pulumi.String("string"),
	Location: pulumi.String("string"),
	Sku: &machinelearningservices.SkuArgs{
		Name:     pulumi.String("string"),
		Capacity: pulumi.Int(0),
		Family:   pulumi.String("string"),
		Size:     pulumi.String("string"),
		Tier:     machinelearningservices.SkuTierFree,
	},
	Tags: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
})
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var onlineDeploymentResource = new OnlineDeployment("onlineDeploymentResource", OnlineDeploymentArgs.builder()
    .endpointName("string")
    .onlineDeploymentProperties(KubernetesOnlineDeploymentArgs.builder()
        .endpointComputeType("Kubernetes")
        .environmentVariables(Map.of("string", "string"))
        .livenessProbe(ProbeSettingsArgs.builder()
            .failureThreshold(0)
            .initialDelay("string")
            .period("string")
            .successThreshold(0)
            .timeout("string")
            .build())
        .dataCollector(DataCollectorArgs.builder()
            .collections(Map.of("string", Map.ofEntries(
                Map.entry("clientId", "string"),
                Map.entry("dataCollectionMode", "string"),
                Map.entry("dataId", "string"),
                Map.entry("samplingRate", 0)
            )))
            .requestLogging(RequestLoggingArgs.builder()
                .captureHeaders("string")
                .build())
            .rollingRate("string")
            .build())
        .description("string")
        .egressPublicNetworkAccess("string")
        .codeConfiguration(CodeConfigurationArgs.builder()
            .scoringScript("string")
            .codeId("string")
            .build())
        .environmentId("string")
        .appInsightsEnabled(false)
        .containerResourceRequirements(ContainerResourceRequirementsArgs.builder()
            .containerResourceLimits(ContainerResourceSettingsArgs.builder()
                .cpu("string")
                .gpu("string")
                .memory("string")
                .build())
            .containerResourceRequests(ContainerResourceSettingsArgs.builder()
                .cpu("string")
                .gpu("string")
                .memory("string")
                .build())
            .build())
        .model("string")
        .instanceType("string")
        .modelMountPath("string")
        .properties(Map.of("string", "string"))
        .readinessProbe(ProbeSettingsArgs.builder()
            .failureThreshold(0)
            .initialDelay("string")
            .period("string")
            .successThreshold(0)
            .timeout("string")
            .build())
        .requestSettings(OnlineRequestSettingsArgs.builder()
            .maxConcurrentRequestsPerInstance(0)
            .maxQueueWait("string")
            .requestTimeout("string")
            .build())
        .scaleSettings(DefaultScaleSettingsArgs.builder()
            .scaleType("Default")
            .build())
        .startupProbe(ProbeSettingsArgs.builder()
            .failureThreshold(0)
            .initialDelay("string")
            .period("string")
            .successThreshold(0)
            .timeout("string")
            .build())
        .build())
    .resourceGroupName("string")
    .workspaceName("string")
    .deploymentName("string")
    .identity(ManagedServiceIdentityArgs.builder()
        .type("string")
        .userAssignedIdentities("string")
        .build())
    .kind("string")
    .location("string")
    .sku(SkuArgs.builder()
        .name("string")
        .capacity(0)
        .family("string")
        .size("string")
        .tier("Free")
        .build())
    .tags(Map.of("string", "string"))
    .build());
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online_deployment_resource = azure_native.machinelearningservices.OnlineDeployment("onlineDeploymentResource",
    endpoint_name="string",
    online_deployment_properties={
        "endpoint_compute_type": "Kubernetes",
        "environment_variables": {
            "string": "string",
        },
        "liveness_probe": {
            "failure_threshold": 0,
            "initial_delay": "string",
            "period": "string",
            "success_threshold": 0,
            "timeout": "string",
        },
        "data_collector": {
            "collections": {
                "string": {
                    "client_id": "string",
                    "data_collection_mode": "string",
                    "data_id": "string",
                    "sampling_rate": 0,
                },
            },
            "request_logging": {
                "capture_headers": ["string"],
            },
            "rolling_rate": "string",
        },
        "description": "string",
        "egress_public_network_access": "string",
        "code_configuration": {
            "scoring_script": "string",
            "code_id": "string",
        },
        "environment_id": "string",
        "app_insights_enabled": False,
        "container_resource_requirements": {
            "container_resource_limits": {
                "cpu": "string",
                "gpu": "string",
                "memory": "string",
            },
            "container_resource_requests": {
                "cpu": "string",
                "gpu": "string",
                "memory": "string",
            },
        },
        "model": "string",
        "instance_type": "string",
        "model_mount_path": "string",
        "properties": {
            "string": "string",
        },
        "readiness_probe": {
            "failure_threshold": 0,
            "initial_delay": "string",
            "period": "string",
            "success_threshold": 0,
            "timeout": "string",
        },
        "request_settings": {
            "max_concurrent_requests_per_instance": 0,
            "max_queue_wait": "string",
            "request_timeout": "string",
        },
        "scale_settings": {
            "scale_type": "Default",
        },
        "startup_probe": {
            "failure_threshold": 0,
            "initial_delay": "string",
            "period": "string",
            "success_threshold": 0,
            "timeout": "string",
        },
    },
    resource_group_name="string",
    workspace_name="string",
    deployment_name="string",
    identity={
        "type": "string",
        "user_assigned_identities": ["string"],
    },
    kind="string",
    location="string",
    sku={
        "name": "string",
        "capacity": 0,
        "family": "string",
        "size": "string",
        "tier": azure_native.machinelearningservices.SkuTier.FREE,
    },
    tags={
        "string": "string",
    })
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const onlineDeploymentResource = new azure_native.machinelearningservices.OnlineDeployment("onlineDeploymentResource", {
    endpointName: "string",
    onlineDeploymentProperties: {
        endpointComputeType: "Kubernetes",
        environmentVariables: {
            string: "string",
        },
        livenessProbe: {
            failureThreshold: 0,
            initialDelay: "string",
            period: "string",
            successThreshold: 0,
            timeout: "string",
        },
        dataCollector: {
            collections: {
                string: {
                    clientId: "string",
                    dataCollectionMode: "string",
                    dataId: "string",
                    samplingRate: 0,
                },
            },
            requestLogging: {
                captureHeaders: ["string"],
            },
            rollingRate: "string",
        },
        description: "string",
        egressPublicNetworkAccess: "string",
        codeConfiguration: {
            scoringScript: "string",
            codeId: "string",
        },
        environmentId: "string",
        appInsightsEnabled: false,
        containerResourceRequirements: {
            containerResourceLimits: {
                cpu: "string",
                gpu: "string",
                memory: "string",
            },
            containerResourceRequests: {
                cpu: "string",
                gpu: "string",
                memory: "string",
            },
        },
        model: "string",
        instanceType: "string",
        modelMountPath: "string",
        properties: {
            string: "string",
        },
        readinessProbe: {
            failureThreshold: 0,
            initialDelay: "string",
            period: "string",
            successThreshold: 0,
            timeout: "string",
        },
        requestSettings: {
            maxConcurrentRequestsPerInstance: 0,
            maxQueueWait: "string",
            requestTimeout: "string",
        },
        scaleSettings: {
            scaleType: "Default",
        },
        startupProbe: {
            failureThreshold: 0,
            initialDelay: "string",
            period: "string",
            successThreshold: 0,
            timeout: "string",
        },
    },
    resourceGroupName: "string",
    workspaceName: "string",
    deploymentName: "string",
    identity: {
        type: "string",
        userAssignedIdentities: ["string"],
    },
    kind: "string",
    location: "string",
    sku: {
        name: "string",
        capacity: 0,
        family: "string",
        size: "string",
        tier: azure_native.machinelearningservices.SkuTier.Free,
    },
    tags: {
        string: "string",
    },
});
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type: azure-native:machinelearningservices:OnlineDeployment
properties:
    deploymentName: string
    endpointName: string
    identity:
        type: string
        userAssignedIdentities:
            - string
    kind: string
    location: string
    onlineDeploymentProperties:
        appInsightsEnabled: false
        codeConfiguration:
            codeId: string
            scoringScript: string
        containerResourceRequirements:
            containerResourceLimits:
                cpu: string
                gpu: string
                memory: string
            containerResourceRequests:
                cpu: string
                gpu: string
                memory: string
        dataCollector:
            collections:
                string:
                    clientId: string
                    dataCollectionMode: string
                    dataId: string
                    samplingRate: 0
            requestLogging:
                captureHeaders:
                    - string
            rollingRate: string
        description: string
        egressPublicNetworkAccess: string
        endpointComputeType: Kubernetes
        environmentId: string
        environmentVariables:
            string: string
        instanceType: string
        livenessProbe:
            failureThreshold: 0
            initialDelay: string
            period: string
            successThreshold: 0
            timeout: string
        model: string
        modelMountPath: string
        properties:
            string: string
        readinessProbe:
            failureThreshold: 0
            initialDelay: string
            period: string
            successThreshold: 0
            timeout: string
        requestSettings:
            maxConcurrentRequestsPerInstance: 0
            maxQueueWait: string
            requestTimeout: string
        scaleSettings:
            scaleType: Default
        startupProbe:
            failureThreshold: 0
            initialDelay: string
            period: string
            successThreshold: 0
            timeout: string
    resourceGroupName: string
    sku:
        capacity: 0
        family: string
        name: string
        size: string
        tier: Free
    tags:
        string: string
    workspaceName: string
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OnlineDeployment Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

The OnlineDeployment resource accepts the following input properties:

EndpointName
This property is required.
Changes to this property will trigger replacement.
string
Inference endpoint name.
OnlineDeploymentProperties This property is required. Pulumi.AzureNative.MachineLearningServices.Inputs.KubernetesOnlineDeployment | Pulumi.AzureNative.MachineLearningServices.Inputs.ManagedOnlineDeployment
[Required] Additional attributes of the entity.
ResourceGroupName
This property is required.
Changes to this property will trigger replacement.
string
The name of the resource group. The name is case insensitive.
WorkspaceName
This property is required.
Changes to this property will trigger replacement.
string
Name of Azure Machine Learning workspace.
DeploymentName Changes to this property will trigger replacement. string
Inference Endpoint Deployment name.
Identity Pulumi.AzureNative.MachineLearningServices.Inputs.ManagedServiceIdentity
Managed service identity (system assigned and/or user assigned identities)
Kind string
Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
Location Changes to this property will trigger replacement. string
The geo-location where the resource lives
Sku Pulumi.AzureNative.MachineLearningServices.Inputs.Sku
Sku details required for ARM contract for Autoscaling.
Tags Dictionary<string, string>
Resource tags.
EndpointName
This property is required.
Changes to this property will trigger replacement.
string
Inference endpoint name.
OnlineDeploymentProperties This property is required. KubernetesOnlineDeploymentArgs | ManagedOnlineDeploymentArgs
[Required] Additional attributes of the entity.
ResourceGroupName
This property is required.
Changes to this property will trigger replacement.
string
The name of the resource group. The name is case insensitive.
WorkspaceName
This property is required.
Changes to this property will trigger replacement.
string
Name of Azure Machine Learning workspace.
DeploymentName Changes to this property will trigger replacement. string
Inference Endpoint Deployment name.
Identity ManagedServiceIdentityArgs
Managed service identity (system assigned and/or user assigned identities)
Kind string
Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
Location Changes to this property will trigger replacement. string
The geo-location where the resource lives
Sku SkuArgs
Sku details required for ARM contract for Autoscaling.
Tags map[string]string
Resource tags.
endpointName
This property is required.
Changes to this property will trigger replacement.
String
Inference endpoint name.
onlineDeploymentProperties This property is required. KubernetesOnlineDeployment | ManagedOnlineDeployment
[Required] Additional attributes of the entity.
resourceGroupName
This property is required.
Changes to this property will trigger replacement.
String
The name of the resource group. The name is case insensitive.
workspaceName
This property is required.
Changes to this property will trigger replacement.
String
Name of Azure Machine Learning workspace.
deploymentName Changes to this property will trigger replacement. String
Inference Endpoint Deployment name.
identity ManagedServiceIdentity
Managed service identity (system assigned and/or user assigned identities)
kind String
Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
location Changes to this property will trigger replacement. String
The geo-location where the resource lives
sku Sku
Sku details required for ARM contract for Autoscaling.
tags Map<String,String>
Resource tags.
endpointName
This property is required.
Changes to this property will trigger replacement.
string
Inference endpoint name.
onlineDeploymentProperties This property is required. KubernetesOnlineDeployment | ManagedOnlineDeployment
[Required] Additional attributes of the entity.
resourceGroupName
This property is required.
Changes to this property will trigger replacement.
string
The name of the resource group. The name is case insensitive.
workspaceName
This property is required.
Changes to this property will trigger replacement.
string
Name of Azure Machine Learning workspace.
deploymentName Changes to this property will trigger replacement. string
Inference Endpoint Deployment name.
identity ManagedServiceIdentity
Managed service identity (system assigned and/or user assigned identities)
kind string
Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
location Changes to this property will trigger replacement. string
The geo-location where the resource lives
sku Sku
Sku details required for ARM contract for Autoscaling.
tags {[key: string]: string}
Resource tags.
endpoint_name
This property is required.
Changes to this property will trigger replacement.
str
Inference endpoint name.
online_deployment_properties This property is required. KubernetesOnlineDeploymentArgs | ManagedOnlineDeploymentArgs
[Required] Additional attributes of the entity.
resource_group_name
This property is required.
Changes to this property will trigger replacement.
str
The name of the resource group. The name is case insensitive.
workspace_name
This property is required.
Changes to this property will trigger replacement.
str
Name of Azure Machine Learning workspace.
deployment_name Changes to this property will trigger replacement. str
Inference Endpoint Deployment name.
identity ManagedServiceIdentityArgs
Managed service identity (system assigned and/or user assigned identities)
kind str
Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
location Changes to this property will trigger replacement. str
The geo-location where the resource lives
sku SkuArgs
Sku details required for ARM contract for Autoscaling.
tags Mapping[str, str]
Resource tags.
endpointName
This property is required.
Changes to this property will trigger replacement.
String
Inference endpoint name.
onlineDeploymentProperties This property is required. Property Map | Property Map
[Required] Additional attributes of the entity.
resourceGroupName
This property is required.
Changes to this property will trigger replacement.
String
The name of the resource group. The name is case insensitive.
workspaceName
This property is required.
Changes to this property will trigger replacement.
String
Name of Azure Machine Learning workspace.
deploymentName Changes to this property will trigger replacement. String
Inference Endpoint Deployment name.
identity Property Map
Managed service identity (system assigned and/or user assigned identities)
kind String
Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
location Changes to this property will trigger replacement. String
The geo-location where the resource lives
sku Property Map
Sku details required for ARM contract for Autoscaling.
tags Map<String>
Resource tags.

Outputs

All input properties are implicitly available as output properties. Additionally, the OnlineDeployment resource produces the following output properties:

AzureApiVersion string
The Azure API version of the resource.
Id string
The provider-assigned unique ID for this managed resource.
Name string
The name of the resource
SystemData Pulumi.AzureNative.MachineLearningServices.Outputs.SystemDataResponse
Azure Resource Manager metadata containing createdBy and modifiedBy information.
Type string
The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
AzureApiVersion string
The Azure API version of the resource.
Id string
The provider-assigned unique ID for this managed resource.
Name string
The name of the resource
SystemData SystemDataResponse
Azure Resource Manager metadata containing createdBy and modifiedBy information.
Type string
The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
azureApiVersion String
The Azure API version of the resource.
id String
The provider-assigned unique ID for this managed resource.
name String
The name of the resource
systemData SystemDataResponse
Azure Resource Manager metadata containing createdBy and modifiedBy information.
type String
The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
azureApiVersion string
The Azure API version of the resource.
id string
The provider-assigned unique ID for this managed resource.
name string
The name of the resource
systemData SystemDataResponse
Azure Resource Manager metadata containing createdBy and modifiedBy information.
type string
The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
azure_api_version str
The Azure API version of the resource.
id str
The provider-assigned unique ID for this managed resource.
name str
The name of the resource
system_data SystemDataResponse
Azure Resource Manager metadata containing createdBy and modifiedBy information.
type str
The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
azureApiVersion String
The Azure API version of the resource.
id String
The provider-assigned unique ID for this managed resource.
name String
The name of the resource
systemData Property Map
Azure Resource Manager metadata containing createdBy and modifiedBy information.
type String
The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"

Supporting Types

CodeConfiguration
, CodeConfigurationArgs

ScoringScript This property is required. string
[Required] The script to execute on startup. eg. "score.py"
CodeId string
ARM resource ID of the code asset.
ScoringScript This property is required. string
[Required] The script to execute on startup. eg. "score.py"
CodeId string
ARM resource ID of the code asset.
scoringScript This property is required. String
[Required] The script to execute on startup. eg. "score.py"
codeId String
ARM resource ID of the code asset.
scoringScript This property is required. string
[Required] The script to execute on startup. eg. "score.py"
codeId string
ARM resource ID of the code asset.
scoring_script This property is required. str
[Required] The script to execute on startup. eg. "score.py"
code_id str
ARM resource ID of the code asset.
scoringScript This property is required. String
[Required] The script to execute on startup. eg. "score.py"
codeId String
ARM resource ID of the code asset.

CodeConfigurationResponse
, CodeConfigurationResponseArgs

ScoringScript This property is required. string
[Required] The script to execute on startup. eg. "score.py"
CodeId string
ARM resource ID of the code asset.
ScoringScript This property is required. string
[Required] The script to execute on startup. eg. "score.py"
CodeId string
ARM resource ID of the code asset.
scoringScript This property is required. String
[Required] The script to execute on startup. eg. "score.py"
codeId String
ARM resource ID of the code asset.
scoringScript This property is required. string
[Required] The script to execute on startup. eg. "score.py"
codeId string
ARM resource ID of the code asset.
scoring_script This property is required. str
[Required] The script to execute on startup. eg. "score.py"
code_id str
ARM resource ID of the code asset.
scoringScript This property is required. String
[Required] The script to execute on startup. eg. "score.py"
codeId String
ARM resource ID of the code asset.

Collection
, CollectionArgs

ClientId string
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
DataCollectionMode string | Pulumi.AzureNative.MachineLearningServices.DataCollectionMode
Enable or disable data collection.
DataId string
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
SamplingRate double
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
ClientId string
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
DataCollectionMode string | DataCollectionMode
Enable or disable data collection.
DataId string
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
SamplingRate float64
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
clientId String
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
dataCollectionMode String | DataCollectionMode
Enable or disable data collection.
dataId String
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
samplingRate Double
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
clientId string
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
dataCollectionMode string | DataCollectionMode
Enable or disable data collection.
dataId string
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
samplingRate number
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
client_id str
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
data_collection_mode str | DataCollectionMode
Enable or disable data collection.
data_id str
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
sampling_rate float
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
clientId String
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
dataCollectionMode String | "Enabled" | "Disabled"
Enable or disable data collection.
dataId String
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
samplingRate Number
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.

CollectionResponse
, CollectionResponseArgs

ClientId string
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
DataCollectionMode string
Enable or disable data collection.
DataId string
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
SamplingRate double
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
ClientId string
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
DataCollectionMode string
Enable or disable data collection.
DataId string
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
SamplingRate float64
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
clientId String
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
dataCollectionMode String
Enable or disable data collection.
dataId String
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
samplingRate Double
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
clientId string
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
dataCollectionMode string
Enable or disable data collection.
dataId string
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
samplingRate number
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
client_id str
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
data_collection_mode str
Enable or disable data collection.
data_id str
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
sampling_rate float
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.
clientId String
The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.
dataCollectionMode String
Enable or disable data collection.
dataId String
The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.
samplingRate Number
The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.

ContainerResourceRequirements
, ContainerResourceRequirementsArgs

containerResourceLimits Property Map
Container resource limit info:
containerResourceRequests Property Map
Container resource request info:

ContainerResourceRequirementsResponse
, ContainerResourceRequirementsResponseArgs

containerResourceLimits Property Map
Container resource limit info:
containerResourceRequests Property Map
Container resource request info:

ContainerResourceSettings
, ContainerResourceSettingsArgs

Cpu string
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Gpu string
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Memory string
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Cpu string
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Gpu string
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Memory string
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
cpu String
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
gpu String
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
memory String
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
cpu string
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
gpu string
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
memory string
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
cpu str
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
gpu str
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
memory str
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
cpu String
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
gpu String
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
memory String
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/

ContainerResourceSettingsResponse
, ContainerResourceSettingsResponseArgs

Cpu string
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Gpu string
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Memory string
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Cpu string
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Gpu string
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
Memory string
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
cpu String
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
gpu String
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
memory String
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
cpu string
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
gpu string
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
memory string
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
cpu str
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
gpu str
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
memory str
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
cpu String
Number of vCPUs request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
gpu String
Number of Nvidia GPU cards request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/
memory String
Memory size request/limit for container. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/

DataCollectionMode
, DataCollectionModeArgs

Enabled
Enabled
Disabled
Disabled
DataCollectionModeEnabled
Enabled
DataCollectionModeDisabled
Disabled
Enabled
Enabled
Disabled
Disabled
Enabled
Enabled
Disabled
Disabled
ENABLED
Enabled
DISABLED
Disabled
"Enabled"
Enabled
"Disabled"
Disabled

DataCollector
, DataCollectorArgs

Collections This property is required. Dictionary<string, Pulumi.AzureNative.MachineLearningServices.Inputs.Collection>
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
RequestLogging Pulumi.AzureNative.MachineLearningServices.Inputs.RequestLogging
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
RollingRate string | Pulumi.AzureNative.MachineLearningServices.RollingRateType
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
Collections This property is required. map[string]Collection
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
RequestLogging RequestLogging
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
RollingRate string | RollingRateType
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
collections This property is required. Map<String,Collection>
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
requestLogging RequestLogging
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
rollingRate String | RollingRateType
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
collections This property is required. {[key: string]: Collection}
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
requestLogging RequestLogging
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
rollingRate string | RollingRateType
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
collections This property is required. Mapping[str, Collection]
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
request_logging RequestLogging
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
rolling_rate str | RollingRateType
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
collections This property is required. Map<Property Map>
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
requestLogging Property Map
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
rollingRate String | "Year" | "Month" | "Day" | "Hour" | "Minute"
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.

DataCollectorResponse
, DataCollectorResponseArgs

Collections This property is required. Dictionary<string, Pulumi.AzureNative.MachineLearningServices.Inputs.CollectionResponse>
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
RequestLogging Pulumi.AzureNative.MachineLearningServices.Inputs.RequestLoggingResponse
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
RollingRate string
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
Collections This property is required. map[string]CollectionResponse
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
RequestLogging RequestLoggingResponse
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
RollingRate string
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
collections This property is required. Map<String,CollectionResponse>
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
requestLogging RequestLoggingResponse
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
rollingRate String
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
collections This property is required. {[key: string]: CollectionResponse}
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
requestLogging RequestLoggingResponse
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
rollingRate string
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
collections This property is required. Mapping[str, CollectionResponse]
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
request_logging RequestLoggingResponse
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
rolling_rate str
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.
collections This property is required. Map<Property Map>
[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string. Model data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.
requestLogging Property Map
The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.
rollingRate String
When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file. If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/. If it's day, all data will be collected in blob path /yyyy/MM/dd/. The other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.

DefaultScaleSettings
, DefaultScaleSettingsArgs

DefaultScaleSettingsResponse
, DefaultScaleSettingsResponseArgs

EgressPublicNetworkAccessType
, EgressPublicNetworkAccessTypeArgs

Enabled
Enabled
Disabled
Disabled
EgressPublicNetworkAccessTypeEnabled
Enabled
EgressPublicNetworkAccessTypeDisabled
Disabled
Enabled
Enabled
Disabled
Disabled
Enabled
Enabled
Disabled
Disabled
ENABLED
Enabled
DISABLED
Disabled
"Enabled"
Enabled
"Disabled"
Disabled

KubernetesOnlineDeployment
, KubernetesOnlineDeploymentArgs

AppInsightsEnabled bool
If true, enables Application Insights logging.
CodeConfiguration Pulumi.AzureNative.MachineLearningServices.Inputs.CodeConfiguration
Code configuration for the endpoint deployment.
ContainerResourceRequirements Pulumi.AzureNative.MachineLearningServices.Inputs.ContainerResourceRequirements
The resource requirements for the container (cpu and memory).
DataCollector Pulumi.AzureNative.MachineLearningServices.Inputs.DataCollector
The mdc configuration, we disable mdc when it's null.
Description string
Description of the endpoint deployment.
EgressPublicNetworkAccess string | Pulumi.AzureNative.MachineLearningServices.EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
EnvironmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
EnvironmentVariables Dictionary<string, string>
Environment variables configuration for the deployment.
InstanceType string
Compute instance type. Default: Standard_F4s_v2.
LivenessProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettings
Liveness probe monitors the health of the container regularly.
Model string
The URI path to the model.
ModelMountPath string
The path to mount the model in custom container.
Properties Dictionary<string, string>
Property dictionary. Properties can be added, but not removed or altered.
ReadinessProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
RequestSettings Pulumi.AzureNative.MachineLearningServices.Inputs.OnlineRequestSettings
Request settings for the deployment.
ScaleSettings Pulumi.AzureNative.MachineLearningServices.Inputs.DefaultScaleSettings | Pulumi.AzureNative.MachineLearningServices.Inputs.TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
StartupProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettings
Startup probe verify whether an application within a container has started successfully.
AppInsightsEnabled bool
If true, enables Application Insights logging.
CodeConfiguration CodeConfiguration
Code configuration for the endpoint deployment.
ContainerResourceRequirements ContainerResourceRequirements
The resource requirements for the container (cpu and memory).
DataCollector DataCollector
The mdc configuration, we disable mdc when it's null.
Description string
Description of the endpoint deployment.
EgressPublicNetworkAccess string | EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
EnvironmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
EnvironmentVariables map[string]string
Environment variables configuration for the deployment.
InstanceType string
Compute instance type. Default: Standard_F4s_v2.
LivenessProbe ProbeSettings
Liveness probe monitors the health of the container regularly.
Model string
The URI path to the model.
ModelMountPath string
The path to mount the model in custom container.
Properties map[string]string
Property dictionary. Properties can be added, but not removed or altered.
ReadinessProbe ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
RequestSettings OnlineRequestSettings
Request settings for the deployment.
ScaleSettings DefaultScaleSettings | TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
StartupProbe ProbeSettings
Startup probe verify whether an application within a container has started successfully.
appInsightsEnabled Boolean
If true, enables Application Insights logging.
codeConfiguration CodeConfiguration
Code configuration for the endpoint deployment.
containerResourceRequirements ContainerResourceRequirements
The resource requirements for the container (cpu and memory).
dataCollector DataCollector
The mdc configuration, we disable mdc when it's null.
description String
Description of the endpoint deployment.
egressPublicNetworkAccess String | EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId String
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables Map<String,String>
Environment variables configuration for the deployment.
instanceType String
Compute instance type. Default: Standard_F4s_v2.
livenessProbe ProbeSettings
Liveness probe monitors the health of the container regularly.
model String
The URI path to the model.
modelMountPath String
The path to mount the model in custom container.
properties Map<String,String>
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings OnlineRequestSettings
Request settings for the deployment.
scaleSettings DefaultScaleSettings | TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe ProbeSettings
Startup probe verify whether an application within a container has started successfully.
appInsightsEnabled boolean
If true, enables Application Insights logging.
codeConfiguration CodeConfiguration
Code configuration for the endpoint deployment.
containerResourceRequirements ContainerResourceRequirements
The resource requirements for the container (cpu and memory).
dataCollector DataCollector
The mdc configuration, we disable mdc when it's null.
description string
Description of the endpoint deployment.
egressPublicNetworkAccess string | EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables {[key: string]: string}
Environment variables configuration for the deployment.
instanceType string
Compute instance type. Default: Standard_F4s_v2.
livenessProbe ProbeSettings
Liveness probe monitors the health of the container regularly.
model string
The URI path to the model.
modelMountPath string
The path to mount the model in custom container.
properties {[key: string]: string}
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings OnlineRequestSettings
Request settings for the deployment.
scaleSettings DefaultScaleSettings | TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe ProbeSettings
Startup probe verify whether an application within a container has started successfully.
app_insights_enabled bool
If true, enables Application Insights logging.
code_configuration CodeConfiguration
Code configuration for the endpoint deployment.
container_resource_requirements ContainerResourceRequirements
The resource requirements for the container (cpu and memory).
data_collector DataCollector
The mdc configuration, we disable mdc when it's null.
description str
Description of the endpoint deployment.
egress_public_network_access str | EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environment_id str
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environment_variables Mapping[str, str]
Environment variables configuration for the deployment.
instance_type str
Compute instance type. Default: Standard_F4s_v2.
liveness_probe ProbeSettings
Liveness probe monitors the health of the container regularly.
model str
The URI path to the model.
model_mount_path str
The path to mount the model in custom container.
properties Mapping[str, str]
Property dictionary. Properties can be added, but not removed or altered.
readiness_probe ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
request_settings OnlineRequestSettings
Request settings for the deployment.
scale_settings DefaultScaleSettings | TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startup_probe ProbeSettings
Startup probe verify whether an application within a container has started successfully.
appInsightsEnabled Boolean
If true, enables Application Insights logging.
codeConfiguration Property Map
Code configuration for the endpoint deployment.
containerResourceRequirements Property Map
The resource requirements for the container (cpu and memory).
dataCollector Property Map
The mdc configuration, we disable mdc when it's null.
description String
Description of the endpoint deployment.
egressPublicNetworkAccess String | "Enabled" | "Disabled"
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId String
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables Map<String>
Environment variables configuration for the deployment.
instanceType String
Compute instance type. Default: Standard_F4s_v2.
livenessProbe Property Map
Liveness probe monitors the health of the container regularly.
model String
The URI path to the model.
modelMountPath String
The path to mount the model in custom container.
properties Map<String>
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe Property Map
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings Property Map
Request settings for the deployment.
scaleSettings Property Map | Property Map
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe Property Map
Startup probe verify whether an application within a container has started successfully.

KubernetesOnlineDeploymentResponse
, KubernetesOnlineDeploymentResponseArgs

ProvisioningState This property is required. string
Provisioning state for the endpoint deployment.
AppInsightsEnabled bool
If true, enables Application Insights logging.
CodeConfiguration Pulumi.AzureNative.MachineLearningServices.Inputs.CodeConfigurationResponse
Code configuration for the endpoint deployment.
ContainerResourceRequirements Pulumi.AzureNative.MachineLearningServices.Inputs.ContainerResourceRequirementsResponse
The resource requirements for the container (cpu and memory).
DataCollector Pulumi.AzureNative.MachineLearningServices.Inputs.DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
Description string
Description of the endpoint deployment.
EgressPublicNetworkAccess string
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
EnvironmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
EnvironmentVariables Dictionary<string, string>
Environment variables configuration for the deployment.
InstanceType string
Compute instance type. Default: Standard_F4s_v2.
LivenessProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
Model string
The URI path to the model.
ModelMountPath string
The path to mount the model in custom container.
Properties Dictionary<string, string>
Property dictionary. Properties can be added, but not removed or altered.
ReadinessProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
RequestSettings Pulumi.AzureNative.MachineLearningServices.Inputs.OnlineRequestSettingsResponse
Request settings for the deployment.
ScaleSettings Pulumi.AzureNative.MachineLearningServices.Inputs.DefaultScaleSettingsResponse | Pulumi.AzureNative.MachineLearningServices.Inputs.TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
StartupProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
ProvisioningState This property is required. string
Provisioning state for the endpoint deployment.
AppInsightsEnabled bool
If true, enables Application Insights logging.
CodeConfiguration CodeConfigurationResponse
Code configuration for the endpoint deployment.
ContainerResourceRequirements ContainerResourceRequirementsResponse
The resource requirements for the container (cpu and memory).
DataCollector DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
Description string
Description of the endpoint deployment.
EgressPublicNetworkAccess string
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
EnvironmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
EnvironmentVariables map[string]string
Environment variables configuration for the deployment.
InstanceType string
Compute instance type. Default: Standard_F4s_v2.
LivenessProbe ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
Model string
The URI path to the model.
ModelMountPath string
The path to mount the model in custom container.
Properties map[string]string
Property dictionary. Properties can be added, but not removed or altered.
ReadinessProbe ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
RequestSettings OnlineRequestSettingsResponse
Request settings for the deployment.
ScaleSettings DefaultScaleSettingsResponse | TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
StartupProbe ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
provisioningState This property is required. String
Provisioning state for the endpoint deployment.
appInsightsEnabled Boolean
If true, enables Application Insights logging.
codeConfiguration CodeConfigurationResponse
Code configuration for the endpoint deployment.
containerResourceRequirements ContainerResourceRequirementsResponse
The resource requirements for the container (cpu and memory).
dataCollector DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
description String
Description of the endpoint deployment.
egressPublicNetworkAccess String
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId String
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables Map<String,String>
Environment variables configuration for the deployment.
instanceType String
Compute instance type. Default: Standard_F4s_v2.
livenessProbe ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
model String
The URI path to the model.
modelMountPath String
The path to mount the model in custom container.
properties Map<String,String>
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings OnlineRequestSettingsResponse
Request settings for the deployment.
scaleSettings DefaultScaleSettingsResponse | TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
provisioningState This property is required. string
Provisioning state for the endpoint deployment.
appInsightsEnabled boolean
If true, enables Application Insights logging.
codeConfiguration CodeConfigurationResponse
Code configuration for the endpoint deployment.
containerResourceRequirements ContainerResourceRequirementsResponse
The resource requirements for the container (cpu and memory).
dataCollector DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
description string
Description of the endpoint deployment.
egressPublicNetworkAccess string
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables {[key: string]: string}
Environment variables configuration for the deployment.
instanceType string
Compute instance type. Default: Standard_F4s_v2.
livenessProbe ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
model string
The URI path to the model.
modelMountPath string
The path to mount the model in custom container.
properties {[key: string]: string}
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings OnlineRequestSettingsResponse
Request settings for the deployment.
scaleSettings DefaultScaleSettingsResponse | TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
provisioning_state This property is required. str
Provisioning state for the endpoint deployment.
app_insights_enabled bool
If true, enables Application Insights logging.
code_configuration CodeConfigurationResponse
Code configuration for the endpoint deployment.
container_resource_requirements ContainerResourceRequirementsResponse
The resource requirements for the container (cpu and memory).
data_collector DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
description str
Description of the endpoint deployment.
egress_public_network_access str
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environment_id str
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environment_variables Mapping[str, str]
Environment variables configuration for the deployment.
instance_type str
Compute instance type. Default: Standard_F4s_v2.
liveness_probe ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
model str
The URI path to the model.
model_mount_path str
The path to mount the model in custom container.
properties Mapping[str, str]
Property dictionary. Properties can be added, but not removed or altered.
readiness_probe ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
request_settings OnlineRequestSettingsResponse
Request settings for the deployment.
scale_settings DefaultScaleSettingsResponse | TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startup_probe ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
provisioningState This property is required. String
Provisioning state for the endpoint deployment.
appInsightsEnabled Boolean
If true, enables Application Insights logging.
codeConfiguration Property Map
Code configuration for the endpoint deployment.
containerResourceRequirements Property Map
The resource requirements for the container (cpu and memory).
dataCollector Property Map
The mdc configuration, we disable mdc when it's null.
description String
Description of the endpoint deployment.
egressPublicNetworkAccess String
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId String
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables Map<String>
Environment variables configuration for the deployment.
instanceType String
Compute instance type. Default: Standard_F4s_v2.
livenessProbe Property Map
Liveness probe monitors the health of the container regularly.
model String
The URI path to the model.
modelMountPath String
The path to mount the model in custom container.
properties Map<String>
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe Property Map
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings Property Map
Request settings for the deployment.
scaleSettings Property Map | Property Map
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe Property Map
Startup probe verify whether an application within a container has started successfully.

ManagedOnlineDeployment
, ManagedOnlineDeploymentArgs

AppInsightsEnabled bool
If true, enables Application Insights logging.
CodeConfiguration Pulumi.AzureNative.MachineLearningServices.Inputs.CodeConfiguration
Code configuration for the endpoint deployment.
DataCollector Pulumi.AzureNative.MachineLearningServices.Inputs.DataCollector
The mdc configuration, we disable mdc when it's null.
Description string
Description of the endpoint deployment.
EgressPublicNetworkAccess string | Pulumi.AzureNative.MachineLearningServices.EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
EnvironmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
EnvironmentVariables Dictionary<string, string>
Environment variables configuration for the deployment.
InstanceType string
Compute instance type. Default: Standard_F4s_v2.
LivenessProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettings
Liveness probe monitors the health of the container regularly.
Model string
The URI path to the model.
ModelMountPath string
The path to mount the model in custom container.
Properties Dictionary<string, string>
Property dictionary. Properties can be added, but not removed or altered.
ReadinessProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
RequestSettings Pulumi.AzureNative.MachineLearningServices.Inputs.OnlineRequestSettings
Request settings for the deployment.
ScaleSettings Pulumi.AzureNative.MachineLearningServices.Inputs.DefaultScaleSettings | Pulumi.AzureNative.MachineLearningServices.Inputs.TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
StartupProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettings
Startup probe verify whether an application within a container has started successfully.
AppInsightsEnabled bool
If true, enables Application Insights logging.
CodeConfiguration CodeConfiguration
Code configuration for the endpoint deployment.
DataCollector DataCollector
The mdc configuration, we disable mdc when it's null.
Description string
Description of the endpoint deployment.
EgressPublicNetworkAccess string | EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
EnvironmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
EnvironmentVariables map[string]string
Environment variables configuration for the deployment.
InstanceType string
Compute instance type. Default: Standard_F4s_v2.
LivenessProbe ProbeSettings
Liveness probe monitors the health of the container regularly.
Model string
The URI path to the model.
ModelMountPath string
The path to mount the model in custom container.
Properties map[string]string
Property dictionary. Properties can be added, but not removed or altered.
ReadinessProbe ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
RequestSettings OnlineRequestSettings
Request settings for the deployment.
ScaleSettings DefaultScaleSettings | TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
StartupProbe ProbeSettings
Startup probe verify whether an application within a container has started successfully.
appInsightsEnabled Boolean
If true, enables Application Insights logging.
codeConfiguration CodeConfiguration
Code configuration for the endpoint deployment.
dataCollector DataCollector
The mdc configuration, we disable mdc when it's null.
description String
Description of the endpoint deployment.
egressPublicNetworkAccess String | EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId String
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables Map<String,String>
Environment variables configuration for the deployment.
instanceType String
Compute instance type. Default: Standard_F4s_v2.
livenessProbe ProbeSettings
Liveness probe monitors the health of the container regularly.
model String
The URI path to the model.
modelMountPath String
The path to mount the model in custom container.
properties Map<String,String>
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings OnlineRequestSettings
Request settings for the deployment.
scaleSettings DefaultScaleSettings | TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe ProbeSettings
Startup probe verify whether an application within a container has started successfully.
appInsightsEnabled boolean
If true, enables Application Insights logging.
codeConfiguration CodeConfiguration
Code configuration for the endpoint deployment.
dataCollector DataCollector
The mdc configuration, we disable mdc when it's null.
description string
Description of the endpoint deployment.
egressPublicNetworkAccess string | EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables {[key: string]: string}
Environment variables configuration for the deployment.
instanceType string
Compute instance type. Default: Standard_F4s_v2.
livenessProbe ProbeSettings
Liveness probe monitors the health of the container regularly.
model string
The URI path to the model.
modelMountPath string
The path to mount the model in custom container.
properties {[key: string]: string}
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings OnlineRequestSettings
Request settings for the deployment.
scaleSettings DefaultScaleSettings | TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe ProbeSettings
Startup probe verify whether an application within a container has started successfully.
app_insights_enabled bool
If true, enables Application Insights logging.
code_configuration CodeConfiguration
Code configuration for the endpoint deployment.
data_collector DataCollector
The mdc configuration, we disable mdc when it's null.
description str
Description of the endpoint deployment.
egress_public_network_access str | EgressPublicNetworkAccessType
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environment_id str
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environment_variables Mapping[str, str]
Environment variables configuration for the deployment.
instance_type str
Compute instance type. Default: Standard_F4s_v2.
liveness_probe ProbeSettings
Liveness probe monitors the health of the container regularly.
model str
The URI path to the model.
model_mount_path str
The path to mount the model in custom container.
properties Mapping[str, str]
Property dictionary. Properties can be added, but not removed or altered.
readiness_probe ProbeSettings
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
request_settings OnlineRequestSettings
Request settings for the deployment.
scale_settings DefaultScaleSettings | TargetUtilizationScaleSettings
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startup_probe ProbeSettings
Startup probe verify whether an application within a container has started successfully.
appInsightsEnabled Boolean
If true, enables Application Insights logging.
codeConfiguration Property Map
Code configuration for the endpoint deployment.
dataCollector Property Map
The mdc configuration, we disable mdc when it's null.
description String
Description of the endpoint deployment.
egressPublicNetworkAccess String | "Enabled" | "Disabled"
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId String
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables Map<String>
Environment variables configuration for the deployment.
instanceType String
Compute instance type. Default: Standard_F4s_v2.
livenessProbe Property Map
Liveness probe monitors the health of the container regularly.
model String
The URI path to the model.
modelMountPath String
The path to mount the model in custom container.
properties Map<String>
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe Property Map
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings Property Map
Request settings for the deployment.
scaleSettings Property Map | Property Map
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe Property Map
Startup probe verify whether an application within a container has started successfully.

ManagedOnlineDeploymentResponse
, ManagedOnlineDeploymentResponseArgs

ProvisioningState This property is required. string
Provisioning state for the endpoint deployment.
AppInsightsEnabled bool
If true, enables Application Insights logging.
CodeConfiguration Pulumi.AzureNative.MachineLearningServices.Inputs.CodeConfigurationResponse
Code configuration for the endpoint deployment.
DataCollector Pulumi.AzureNative.MachineLearningServices.Inputs.DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
Description string
Description of the endpoint deployment.
EgressPublicNetworkAccess string
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
EnvironmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
EnvironmentVariables Dictionary<string, string>
Environment variables configuration for the deployment.
InstanceType string
Compute instance type. Default: Standard_F4s_v2.
LivenessProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
Model string
The URI path to the model.
ModelMountPath string
The path to mount the model in custom container.
Properties Dictionary<string, string>
Property dictionary. Properties can be added, but not removed or altered.
ReadinessProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
RequestSettings Pulumi.AzureNative.MachineLearningServices.Inputs.OnlineRequestSettingsResponse
Request settings for the deployment.
ScaleSettings Pulumi.AzureNative.MachineLearningServices.Inputs.DefaultScaleSettingsResponse | Pulumi.AzureNative.MachineLearningServices.Inputs.TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
StartupProbe Pulumi.AzureNative.MachineLearningServices.Inputs.ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
ProvisioningState This property is required. string
Provisioning state for the endpoint deployment.
AppInsightsEnabled bool
If true, enables Application Insights logging.
CodeConfiguration CodeConfigurationResponse
Code configuration for the endpoint deployment.
DataCollector DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
Description string
Description of the endpoint deployment.
EgressPublicNetworkAccess string
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
EnvironmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
EnvironmentVariables map[string]string
Environment variables configuration for the deployment.
InstanceType string
Compute instance type. Default: Standard_F4s_v2.
LivenessProbe ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
Model string
The URI path to the model.
ModelMountPath string
The path to mount the model in custom container.
Properties map[string]string
Property dictionary. Properties can be added, but not removed or altered.
ReadinessProbe ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
RequestSettings OnlineRequestSettingsResponse
Request settings for the deployment.
ScaleSettings DefaultScaleSettingsResponse | TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
StartupProbe ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
provisioningState This property is required. String
Provisioning state for the endpoint deployment.
appInsightsEnabled Boolean
If true, enables Application Insights logging.
codeConfiguration CodeConfigurationResponse
Code configuration for the endpoint deployment.
dataCollector DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
description String
Description of the endpoint deployment.
egressPublicNetworkAccess String
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId String
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables Map<String,String>
Environment variables configuration for the deployment.
instanceType String
Compute instance type. Default: Standard_F4s_v2.
livenessProbe ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
model String
The URI path to the model.
modelMountPath String
The path to mount the model in custom container.
properties Map<String,String>
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings OnlineRequestSettingsResponse
Request settings for the deployment.
scaleSettings DefaultScaleSettingsResponse | TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
provisioningState This property is required. string
Provisioning state for the endpoint deployment.
appInsightsEnabled boolean
If true, enables Application Insights logging.
codeConfiguration CodeConfigurationResponse
Code configuration for the endpoint deployment.
dataCollector DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
description string
Description of the endpoint deployment.
egressPublicNetworkAccess string
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId string
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables {[key: string]: string}
Environment variables configuration for the deployment.
instanceType string
Compute instance type. Default: Standard_F4s_v2.
livenessProbe ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
model string
The URI path to the model.
modelMountPath string
The path to mount the model in custom container.
properties {[key: string]: string}
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings OnlineRequestSettingsResponse
Request settings for the deployment.
scaleSettings DefaultScaleSettingsResponse | TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
provisioning_state This property is required. str
Provisioning state for the endpoint deployment.
app_insights_enabled bool
If true, enables Application Insights logging.
code_configuration CodeConfigurationResponse
Code configuration for the endpoint deployment.
data_collector DataCollectorResponse
The mdc configuration, we disable mdc when it's null.
description str
Description of the endpoint deployment.
egress_public_network_access str
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environment_id str
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environment_variables Mapping[str, str]
Environment variables configuration for the deployment.
instance_type str
Compute instance type. Default: Standard_F4s_v2.
liveness_probe ProbeSettingsResponse
Liveness probe monitors the health of the container regularly.
model str
The URI path to the model.
model_mount_path str
The path to mount the model in custom container.
properties Mapping[str, str]
Property dictionary. Properties can be added, but not removed or altered.
readiness_probe ProbeSettingsResponse
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
request_settings OnlineRequestSettingsResponse
Request settings for the deployment.
scale_settings DefaultScaleSettingsResponse | TargetUtilizationScaleSettingsResponse
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startup_probe ProbeSettingsResponse
Startup probe verify whether an application within a container has started successfully.
provisioningState This property is required. String
Provisioning state for the endpoint deployment.
appInsightsEnabled Boolean
If true, enables Application Insights logging.
codeConfiguration Property Map
Code configuration for the endpoint deployment.
dataCollector Property Map
The mdc configuration, we disable mdc when it's null.
description String
Description of the endpoint deployment.
egressPublicNetworkAccess String
If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.
environmentId String
ARM resource ID or AssetId of the environment specification for the endpoint deployment.
environmentVariables Map<String>
Environment variables configuration for the deployment.
instanceType String
Compute instance type. Default: Standard_F4s_v2.
livenessProbe Property Map
Liveness probe monitors the health of the container regularly.
model String
The URI path to the model.
modelMountPath String
The path to mount the model in custom container.
properties Map<String>
Property dictionary. Properties can be added, but not removed or altered.
readinessProbe Property Map
Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.
requestSettings Property Map
Request settings for the deployment.
scaleSettings Property Map | Property Map
Scale settings for the deployment. If it is null or not provided, it defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment and to DefaultScaleSettings for ManagedOnlineDeployment.
startupProbe Property Map
Startup probe verify whether an application within a container has started successfully.

ManagedServiceIdentity
, ManagedServiceIdentityArgs

Type This property is required. string | Pulumi.AzureNative.MachineLearningServices.ManagedServiceIdentityType
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
UserAssignedIdentities List<string>
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
Type This property is required. string | ManagedServiceIdentityType
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
UserAssignedIdentities []string
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
type This property is required. String | ManagedServiceIdentityType
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
userAssignedIdentities List<String>
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
type This property is required. string | ManagedServiceIdentityType
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
userAssignedIdentities string[]
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
type This property is required. str | ManagedServiceIdentityType
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
user_assigned_identities Sequence[str]
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
type This property is required. String | "None" | "SystemAssigned" | "UserAssigned" | "SystemAssigned,UserAssigned"
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
userAssignedIdentities List<String>
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.

ManagedServiceIdentityResponse
, ManagedServiceIdentityResponseArgs

PrincipalId This property is required. string
The service principal ID of the system assigned identity. This property will only be provided for a system assigned identity.
TenantId This property is required. string
The tenant ID of the system assigned identity. This property will only be provided for a system assigned identity.
Type This property is required. string
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
UserAssignedIdentities Dictionary<string, Pulumi.AzureNative.MachineLearningServices.Inputs.UserAssignedIdentityResponse>
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
PrincipalId This property is required. string
The service principal ID of the system assigned identity. This property will only be provided for a system assigned identity.
TenantId This property is required. string
The tenant ID of the system assigned identity. This property will only be provided for a system assigned identity.
Type This property is required. string
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
UserAssignedIdentities map[string]UserAssignedIdentityResponse
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
principalId This property is required. String
The service principal ID of the system assigned identity. This property will only be provided for a system assigned identity.
tenantId This property is required. String
The tenant ID of the system assigned identity. This property will only be provided for a system assigned identity.
type This property is required. String
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
userAssignedIdentities Map<String,UserAssignedIdentityResponse>
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
principalId This property is required. string
The service principal ID of the system assigned identity. This property will only be provided for a system assigned identity.
tenantId This property is required. string
The tenant ID of the system assigned identity. This property will only be provided for a system assigned identity.
type This property is required. string
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
userAssignedIdentities {[key: string]: UserAssignedIdentityResponse}
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
principal_id This property is required. str
The service principal ID of the system assigned identity. This property will only be provided for a system assigned identity.
tenant_id This property is required. str
The tenant ID of the system assigned identity. This property will only be provided for a system assigned identity.
type This property is required. str
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
user_assigned_identities Mapping[str, UserAssignedIdentityResponse]
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.
principalId This property is required. String
The service principal ID of the system assigned identity. This property will only be provided for a system assigned identity.
tenantId This property is required. String
The tenant ID of the system assigned identity. This property will only be provided for a system assigned identity.
type This property is required. String
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed).
userAssignedIdentities Map<Property Map>
The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.

ManagedServiceIdentityType
, ManagedServiceIdentityTypeArgs

None
None
SystemAssigned
SystemAssigned
UserAssigned
UserAssigned
SystemAssigned_UserAssigned
SystemAssigned,UserAssigned
ManagedServiceIdentityTypeNone
None
ManagedServiceIdentityTypeSystemAssigned
SystemAssigned
ManagedServiceIdentityTypeUserAssigned
UserAssigned
ManagedServiceIdentityType_SystemAssigned_UserAssigned
SystemAssigned,UserAssigned
None
None
SystemAssigned
SystemAssigned
UserAssigned
UserAssigned
SystemAssigned_UserAssigned
SystemAssigned,UserAssigned
None
None
SystemAssigned
SystemAssigned
UserAssigned
UserAssigned
SystemAssigned_UserAssigned
SystemAssigned,UserAssigned
NONE
None
SYSTEM_ASSIGNED
SystemAssigned
USER_ASSIGNED
UserAssigned
SYSTEM_ASSIGNED_USER_ASSIGNED
SystemAssigned,UserAssigned
"None"
None
"SystemAssigned"
SystemAssigned
"UserAssigned"
UserAssigned
"SystemAssigned,UserAssigned"
SystemAssigned,UserAssigned

OnlineRequestSettings
, OnlineRequestSettingsArgs

MaxConcurrentRequestsPerInstance int
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
MaxQueueWait string
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
RequestTimeout string
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
MaxConcurrentRequestsPerInstance int
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
MaxQueueWait string
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
RequestTimeout string
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
maxConcurrentRequestsPerInstance Integer
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
maxQueueWait String
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
requestTimeout String
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
maxConcurrentRequestsPerInstance number
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
maxQueueWait string
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
requestTimeout string
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
max_concurrent_requests_per_instance int
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
max_queue_wait str
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
request_timeout str
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
maxConcurrentRequestsPerInstance Number
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
maxQueueWait String
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
requestTimeout String
The scoring timeout in ISO 8601 format. Defaults to 5000ms.

OnlineRequestSettingsResponse
, OnlineRequestSettingsResponseArgs

MaxConcurrentRequestsPerInstance int
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
MaxQueueWait string
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
RequestTimeout string
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
MaxConcurrentRequestsPerInstance int
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
MaxQueueWait string
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
RequestTimeout string
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
maxConcurrentRequestsPerInstance Integer
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
maxQueueWait String
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
requestTimeout String
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
maxConcurrentRequestsPerInstance number
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
maxQueueWait string
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
requestTimeout string
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
max_concurrent_requests_per_instance int
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
max_queue_wait str
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
request_timeout str
The scoring timeout in ISO 8601 format. Defaults to 5000ms.
maxConcurrentRequestsPerInstance Number
The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.
maxQueueWait String
(Deprecated for Managed Online Endpoints) The maximum amount of time a request will stay in the queue in ISO 8601 format. Defaults to 500ms. (Now increase request_timeout_ms to account for any networking/queue delays)
requestTimeout String
The scoring timeout in ISO 8601 format. Defaults to 5000ms.

ProbeSettings
, ProbeSettingsArgs

FailureThreshold int
The number of failures to allow before returning an unhealthy status.
InitialDelay string
The delay before the first probe in ISO 8601 format.
Period string
The length of time between probes in ISO 8601 format.
SuccessThreshold int
The number of successful probes before returning a healthy status.
Timeout string
The probe timeout in ISO 8601 format.
FailureThreshold int
The number of failures to allow before returning an unhealthy status.
InitialDelay string
The delay before the first probe in ISO 8601 format.
Period string
The length of time between probes in ISO 8601 format.
SuccessThreshold int
The number of successful probes before returning a healthy status.
Timeout string
The probe timeout in ISO 8601 format.
failureThreshold Integer
The number of failures to allow before returning an unhealthy status.
initialDelay String
The delay before the first probe in ISO 8601 format.
period String
The length of time between probes in ISO 8601 format.
successThreshold Integer
The number of successful probes before returning a healthy status.
timeout String
The probe timeout in ISO 8601 format.
failureThreshold number
The number of failures to allow before returning an unhealthy status.
initialDelay string
The delay before the first probe in ISO 8601 format.
period string
The length of time between probes in ISO 8601 format.
successThreshold number
The number of successful probes before returning a healthy status.
timeout string
The probe timeout in ISO 8601 format.
failure_threshold int
The number of failures to allow before returning an unhealthy status.
initial_delay str
The delay before the first probe in ISO 8601 format.
period str
The length of time between probes in ISO 8601 format.
success_threshold int
The number of successful probes before returning a healthy status.
timeout str
The probe timeout in ISO 8601 format.
failureThreshold Number
The number of failures to allow before returning an unhealthy status.
initialDelay String
The delay before the first probe in ISO 8601 format.
period String
The length of time between probes in ISO 8601 format.
successThreshold Number
The number of successful probes before returning a healthy status.
timeout String
The probe timeout in ISO 8601 format.

ProbeSettingsResponse
, ProbeSettingsResponseArgs

FailureThreshold int
The number of failures to allow before returning an unhealthy status.
InitialDelay string
The delay before the first probe in ISO 8601 format.
Period string
The length of time between probes in ISO 8601 format.
SuccessThreshold int
The number of successful probes before returning a healthy status.
Timeout string
The probe timeout in ISO 8601 format.
FailureThreshold int
The number of failures to allow before returning an unhealthy status.
InitialDelay string
The delay before the first probe in ISO 8601 format.
Period string
The length of time between probes in ISO 8601 format.
SuccessThreshold int
The number of successful probes before returning a healthy status.
Timeout string
The probe timeout in ISO 8601 format.
failureThreshold Integer
The number of failures to allow before returning an unhealthy status.
initialDelay String
The delay before the first probe in ISO 8601 format.
period String
The length of time between probes in ISO 8601 format.
successThreshold Integer
The number of successful probes before returning a healthy status.
timeout String
The probe timeout in ISO 8601 format.
failureThreshold number
The number of failures to allow before returning an unhealthy status.
initialDelay string
The delay before the first probe in ISO 8601 format.
period string
The length of time between probes in ISO 8601 format.
successThreshold number
The number of successful probes before returning a healthy status.
timeout string
The probe timeout in ISO 8601 format.
failure_threshold int
The number of failures to allow before returning an unhealthy status.
initial_delay str
The delay before the first probe in ISO 8601 format.
period str
The length of time between probes in ISO 8601 format.
success_threshold int
The number of successful probes before returning a healthy status.
timeout str
The probe timeout in ISO 8601 format.
failureThreshold Number
The number of failures to allow before returning an unhealthy status.
initialDelay String
The delay before the first probe in ISO 8601 format.
period String
The length of time between probes in ISO 8601 format.
successThreshold Number
The number of successful probes before returning a healthy status.
timeout String
The probe timeout in ISO 8601 format.

RequestLogging
, RequestLoggingArgs

CaptureHeaders List<string>
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
CaptureHeaders []string
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
captureHeaders List<String>
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
captureHeaders string[]
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
capture_headers Sequence[str]
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
captureHeaders List<String>
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.

RequestLoggingResponse
, RequestLoggingResponseArgs

CaptureHeaders List<string>
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
CaptureHeaders []string
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
captureHeaders List<String>
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
captureHeaders string[]
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
capture_headers Sequence[str]
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.
captureHeaders List<String>
For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.

RollingRateType
, RollingRateTypeArgs

Year
Year
Month
Month
Day
Day
Hour
Hour
Minute
Minute
RollingRateTypeYear
Year
RollingRateTypeMonth
Month
RollingRateTypeDay
Day
RollingRateTypeHour
Hour
RollingRateTypeMinute
Minute
Year
Year
Month
Month
Day
Day
Hour
Hour
Minute
Minute
Year
Year
Month
Month
Day
Day
Hour
Hour
Minute
Minute
YEAR
Year
MONTH
Month
DAY
Day
HOUR
Hour
MINUTE
Minute
"Year"
Year
"Month"
Month
"Day"
Day
"Hour"
Hour
"Minute"
Minute

Sku
, SkuArgs

Name This property is required. string
The name of the SKU. Ex - P3. It is typically a letter+number code
Capacity int
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
Family string
If the service has different generations of hardware, for the same SKU, then that can be captured here.
Size string
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
Tier Pulumi.AzureNative.MachineLearningServices.SkuTier
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
Name This property is required. string
The name of the SKU. Ex - P3. It is typically a letter+number code
Capacity int
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
Family string
If the service has different generations of hardware, for the same SKU, then that can be captured here.
Size string
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
Tier SkuTier
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
name This property is required. String
The name of the SKU. Ex - P3. It is typically a letter+number code
capacity Integer
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family String
If the service has different generations of hardware, for the same SKU, then that can be captured here.
size String
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier SkuTier
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
name This property is required. string
The name of the SKU. Ex - P3. It is typically a letter+number code
capacity number
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family string
If the service has different generations of hardware, for the same SKU, then that can be captured here.
size string
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier SkuTier
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
name This property is required. str
The name of the SKU. Ex - P3. It is typically a letter+number code
capacity int
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family str
If the service has different generations of hardware, for the same SKU, then that can be captured here.
size str
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier SkuTier
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
name This property is required. String
The name of the SKU. Ex - P3. It is typically a letter+number code
capacity Number
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family String
If the service has different generations of hardware, for the same SKU, then that can be captured here.
size String
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier "Free" | "Basic" | "Standard" | "Premium"
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.

SkuResponse
, SkuResponseArgs

Name This property is required. string
The name of the SKU. Ex - P3. It is typically a letter+number code
Capacity int
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
Family string
If the service has different generations of hardware, for the same SKU, then that can be captured here.
Size string
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
Tier string
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
Name This property is required. string
The name of the SKU. Ex - P3. It is typically a letter+number code
Capacity int
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
Family string
If the service has different generations of hardware, for the same SKU, then that can be captured here.
Size string
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
Tier string
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
name This property is required. String
The name of the SKU. Ex - P3. It is typically a letter+number code
capacity Integer
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family String
If the service has different generations of hardware, for the same SKU, then that can be captured here.
size String
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier String
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
name This property is required. string
The name of the SKU. Ex - P3. It is typically a letter+number code
capacity number
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family string
If the service has different generations of hardware, for the same SKU, then that can be captured here.
size string
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier string
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
name This property is required. str
The name of the SKU. Ex - P3. It is typically a letter+number code
capacity int
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family str
If the service has different generations of hardware, for the same SKU, then that can be captured here.
size str
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier str
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.
name This property is required. String
The name of the SKU. Ex - P3. It is typically a letter+number code
capacity Number
If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family String
If the service has different generations of hardware, for the same SKU, then that can be captured here.
size String
The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier String
This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.

SkuTier
, SkuTierArgs

Free
Free
Basic
Basic
Standard
Standard
Premium
Premium
SkuTierFree
Free
SkuTierBasic
Basic
SkuTierStandard
Standard
SkuTierPremium
Premium
Free
Free
Basic
Basic
Standard
Standard
Premium
Premium
Free
Free
Basic
Basic
Standard
Standard
Premium
Premium
FREE
Free
BASIC
Basic
STANDARD
Standard
PREMIUM
Premium
"Free"
Free
"Basic"
Basic
"Standard"
Standard
"Premium"
Premium

SystemDataResponse
, SystemDataResponseArgs

CreatedAt string
The timestamp of resource creation (UTC).
CreatedBy string
The identity that created the resource.
CreatedByType string
The type of identity that created the resource.
LastModifiedAt string
The timestamp of resource last modification (UTC)
LastModifiedBy string
The identity that last modified the resource.
LastModifiedByType string
The type of identity that last modified the resource.
CreatedAt string
The timestamp of resource creation (UTC).
CreatedBy string
The identity that created the resource.
CreatedByType string
The type of identity that created the resource.
LastModifiedAt string
The timestamp of resource last modification (UTC)
LastModifiedBy string
The identity that last modified the resource.
LastModifiedByType string
The type of identity that last modified the resource.
createdAt String
The timestamp of resource creation (UTC).
createdBy String
The identity that created the resource.
createdByType String
The type of identity that created the resource.
lastModifiedAt String
The timestamp of resource last modification (UTC)
lastModifiedBy String
The identity that last modified the resource.
lastModifiedByType String
The type of identity that last modified the resource.
createdAt string
The timestamp of resource creation (UTC).
createdBy string
The identity that created the resource.
createdByType string
The type of identity that created the resource.
lastModifiedAt string
The timestamp of resource last modification (UTC)
lastModifiedBy string
The identity that last modified the resource.
lastModifiedByType string
The type of identity that last modified the resource.
created_at str
The timestamp of resource creation (UTC).
created_by str
The identity that created the resource.
created_by_type str
The type of identity that created the resource.
last_modified_at str
The timestamp of resource last modification (UTC)
last_modified_by str
The identity that last modified the resource.
last_modified_by_type str
The type of identity that last modified the resource.
createdAt String
The timestamp of resource creation (UTC).
createdBy String
The identity that created the resource.
createdByType String
The type of identity that created the resource.
lastModifiedAt String
The timestamp of resource last modification (UTC)
lastModifiedBy String
The identity that last modified the resource.
lastModifiedByType String
The type of identity that last modified the resource.

TargetUtilizationScaleSettings
, TargetUtilizationScaleSettingsArgs

MaxInstances int
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
MinInstances int
The minimum number of instances to always be present.
PollingInterval string
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
TargetUtilizationPercentage int
Target CPU usage for the autoscaler.
MaxInstances int
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
MinInstances int
The minimum number of instances to always be present.
PollingInterval string
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
TargetUtilizationPercentage int
Target CPU usage for the autoscaler.
maxInstances Integer
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
minInstances Integer
The minimum number of instances to always be present.
pollingInterval String
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
targetUtilizationPercentage Integer
Target CPU usage for the autoscaler.
maxInstances number
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
minInstances number
The minimum number of instances to always be present.
pollingInterval string
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
targetUtilizationPercentage number
Target CPU usage for the autoscaler.
max_instances int
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
min_instances int
The minimum number of instances to always be present.
polling_interval str
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
target_utilization_percentage int
Target CPU usage for the autoscaler.
maxInstances Number
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
minInstances Number
The minimum number of instances to always be present.
pollingInterval String
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
targetUtilizationPercentage Number
Target CPU usage for the autoscaler.

TargetUtilizationScaleSettingsResponse
, TargetUtilizationScaleSettingsResponseArgs

MaxInstances int
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
MinInstances int
The minimum number of instances to always be present.
PollingInterval string
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
TargetUtilizationPercentage int
Target CPU usage for the autoscaler.
MaxInstances int
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
MinInstances int
The minimum number of instances to always be present.
PollingInterval string
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
TargetUtilizationPercentage int
Target CPU usage for the autoscaler.
maxInstances Integer
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
minInstances Integer
The minimum number of instances to always be present.
pollingInterval String
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
targetUtilizationPercentage Integer
Target CPU usage for the autoscaler.
maxInstances number
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
minInstances number
The minimum number of instances to always be present.
pollingInterval string
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
targetUtilizationPercentage number
Target CPU usage for the autoscaler.
max_instances int
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
min_instances int
The minimum number of instances to always be present.
polling_interval str
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
target_utilization_percentage int
Target CPU usage for the autoscaler.
maxInstances Number
The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.
minInstances Number
The minimum number of instances to always be present.
pollingInterval String
The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.
targetUtilizationPercentage Number
Target CPU usage for the autoscaler.

UserAssignedIdentityResponse
, UserAssignedIdentityResponseArgs

ClientId This property is required. string
The client ID of the assigned identity.
PrincipalId This property is required. string
The principal ID of the assigned identity.
TenantId string
The tenant ID of the user assigned identity.
ClientId This property is required. string
The client ID of the assigned identity.
PrincipalId This property is required. string
The principal ID of the assigned identity.
TenantId string
The tenant ID of the user assigned identity.
clientId This property is required. String
The client ID of the assigned identity.
principalId This property is required. String
The principal ID of the assigned identity.
tenantId String
The tenant ID of the user assigned identity.
clientId This property is required. string
The client ID of the assigned identity.
principalId This property is required. string
The principal ID of the assigned identity.
tenantId string
The tenant ID of the user assigned identity.
client_id This property is required. str
The client ID of the assigned identity.
principal_id This property is required. str
The principal ID of the assigned identity.
tenant_id str
The tenant ID of the user assigned identity.
clientId This property is required. String
The client ID of the assigned identity.
principalId This property is required. String
The principal ID of the assigned identity.
tenantId String
The tenant ID of the user assigned identity.

Package Details

Repository
Azure Native pulumi/pulumi-azure-native
License
Apache-2.0
This is the latest version of Azure Native. Use the Azure Native v2 docs if using the v2 version of this package.
Azure Native v3.2.0 published on Monday, Apr 14, 2025 by Pulumi
pulumi/pulumi-azure-native