Online
data class OnlineDeploymentArgs(val deploymentName: Output<String>? = null, val endpointName: Output<String>? = null, val identity: Output<ResourceIdentityArgs>? = null, val kind: Output<String>? = null, val location: Output<String>? = null, val properties: Output<Either<K8sOnlineDeploymentArgs, ManagedOnlineDeploymentArgs>>? = null, val resourceGroupName: Output<String>? = null, val tags: Output<Map<String, String>>? = null, val workspaceName: Output<String>? = null) : ConvertibleToJava<OnlineDeploymentArgs>
API Version: 2021-03-01-preview.
Example Usage
CreateOrUpdate K8S Online Deployment.
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
var onlineDeployment = new AzureNative.MachineLearningServices.OnlineDeployment("onlineDeployment", new()
{
DeploymentName = "testDeployment",
EndpointName = "testEndpoint",
Identity = new AzureNative.MachineLearningServices.Inputs.ResourceIdentityArgs
{
Type = "UserAssigned",
UserAssignedIdentities =
{
{ "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", new AzureNative.MachineLearningServices.Inputs.UserAssignedIdentityMetaArgs
{
ClientId = "string",
PrincipalId = "string",
} },
},
},
Kind = "string",
Location = "string",
Properties = new AzureNative.MachineLearningServices.Inputs.K8sOnlineDeploymentArgs
{
AppInsightsEnabled = true,
CodeConfiguration = new AzureNative.MachineLearningServices.Inputs.CodeConfigurationArgs
{
CodeId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1",
ScoringScript = "string",
},
ContainerResourceRequirements = new AzureNative.MachineLearningServices.Inputs.ContainerResourceRequirementsArgs
{
Cpu = 4,
CpuLimit = 4,
MemoryInGB = 64,
MemoryInGBLimit = 64,
},
Description = "string",
EndpointComputeType = "K8S",
EnvironmentId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123",
LivenessProbe = new AzureNative.MachineLearningServices.Inputs.ProbeSettingsArgs
{
FailureThreshold = 50,
InitialDelay = "PT1M",
Period = "PT1M",
SuccessThreshold = 50,
Timeout = "PT1M",
},
Model = new AzureNative.MachineLearningServices.Inputs.IdAssetReferenceArgs
{
AssetId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123",
ReferenceType = "Id",
},
Properties =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
RequestSettings = new AzureNative.MachineLearningServices.Inputs.OnlineRequestSettingsArgs
{
MaxConcurrentRequestsPerInstance = 5,
MaxQueueWait = "PT1M",
RequestTimeout = "PT1M",
},
ScaleSettings = new AzureNative.MachineLearningServices.Inputs.AutoScaleSettingsArgs
{
PollingInterval = "PT1M",
ScaleType = "Auto",
TargetUtilizationPercentage = 50,
},
},
ResourceGroupName = "testrg123",
Tags =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
WorkspaceName = "workspace123",
});
});Content copied to clipboard
package main
import (
machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := machinelearningservices.NewOnlineDeployment(ctx, "onlineDeployment", &machinelearningservices.OnlineDeploymentArgs{
DeploymentName: pulumi.String("testDeployment"),
EndpointName: pulumi.String("testEndpoint"),
Identity: machinelearningservices.ResourceIdentityResponse{
Type: pulumi.String("UserAssigned"),
UserAssignedIdentities: machinelearningservices.UserAssignedIdentityMetaMap{
"/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity": &machinelearningservices.UserAssignedIdentityMetaArgs{
ClientId: pulumi.String("string"),
PrincipalId: pulumi.String("string"),
},
},
},
Kind: pulumi.String("string"),
Location: pulumi.String("string"),
Properties: machinelearningservices.K8sOnlineDeployment{
AppInsightsEnabled: true,
CodeConfiguration: machinelearningservices.CodeConfiguration{
CodeId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1",
ScoringScript: "string",
},
ContainerResourceRequirements: machinelearningservices.ContainerResourceRequirements{
Cpu: 4,
CpuLimit: 4,
MemoryInGB: 64,
MemoryInGBLimit: 64,
},
Description: "string",
EndpointComputeType: "K8S",
EnvironmentId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123",
LivenessProbe: machinelearningservices.ProbeSettings{
FailureThreshold: 50,
InitialDelay: "PT1M",
Period: "PT1M",
SuccessThreshold: 50,
Timeout: "PT1M",
},
Model: machinelearningservices.IdAssetReference{
AssetId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123",
ReferenceType: "Id",
},
Properties: map[string]interface{}{
"additionalProp1": "string",
"additionalProp2": "string",
"additionalProp3": "string",
},
RequestSettings: machinelearningservices.OnlineRequestSettings{
MaxConcurrentRequestsPerInstance: 5,
MaxQueueWait: "PT1M",
RequestTimeout: "PT1M",
},
ScaleSettings: machinelearningservices.AutoScaleSettings{
PollingInterval: "PT1M",
ScaleType: "Auto",
TargetUtilizationPercentage: 50,
},
},
ResourceGroupName: pulumi.String("testrg123"),
Tags: pulumi.StringMap{
"additionalProp1": pulumi.String("string"),
"additionalProp2": pulumi.String("string"),
"additionalProp3": pulumi.String("string"),
},
WorkspaceName: pulumi.String("workspace123"),
})
if err != nil {
return err
}
return nil
})
}Content copied to clipboard
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.machinelearningservices.OnlineDeployment;
import com.pulumi.azurenative.machinelearningservices.OnlineDeploymentArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var onlineDeployment = new OnlineDeployment("onlineDeployment", OnlineDeploymentArgs.builder()
.deploymentName("testDeployment")
.endpointName("testEndpoint")
.identity(Map.ofEntries(
Map.entry("type", "UserAssigned"),
Map.entry("userAssignedIdentities", Map.of("/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", Map.ofEntries(
Map.entry("clientId", "string"),
Map.entry("principalId", "string")
)))
))
.kind("string")
.location("string")
.properties(Map.ofEntries(
Map.entry("appInsightsEnabled", true),
Map.entry("codeConfiguration", Map.ofEntries(
Map.entry("codeId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1"),
Map.entry("scoringScript", "string")
)),
Map.entry("containerResourceRequirements", Map.ofEntries(
Map.entry("cpu", 4),
Map.entry("cpuLimit", 4),
Map.entry("memoryInGB", 64),
Map.entry("memoryInGBLimit", 64)
)),
Map.entry("description", "string"),
Map.entry("endpointComputeType", "K8S"),
Map.entry("environmentId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123"),
Map.entry("livenessProbe", Map.ofEntries(
Map.entry("failureThreshold", 50),
Map.entry("initialDelay", "PT1M"),
Map.entry("period", "PT1M"),
Map.entry("successThreshold", 50),
Map.entry("timeout", "PT1M")
)),
Map.entry("model", Map.ofEntries(
Map.entry("assetId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123"),
Map.entry("referenceType", "Id")
)),
Map.entry("properties", K8sOnlineDeploymentArgs.builder()
.additionalProp1("string")
.additionalProp2("string")
.additionalProp3("string")
.build()),
Map.entry("requestSettings", Map.ofEntries(
Map.entry("maxConcurrentRequestsPerInstance", 5),
Map.entry("maxQueueWait", "PT1M"),
Map.entry("requestTimeout", "PT1M")
)),
Map.entry("scaleSettings", Map.ofEntries(
Map.entry("pollingInterval", "PT1M"),
Map.entry("scaleType", "Auto"),
Map.entry("targetUtilizationPercentage", 50)
))
))
.resourceGroupName("testrg123")
.tags(Map.ofEntries(
Map.entry("additionalProp1", "string"),
Map.entry("additionalProp2", "string"),
Map.entry("additionalProp3", "string")
))
.workspaceName("workspace123")
.build());
}
}Content copied to clipboard
CreateOrUpdate Managed Online Deployment.
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
var onlineDeployment = new AzureNative.MachineLearningServices.OnlineDeployment("onlineDeployment", new()
{
DeploymentName = "testDeployment",
EndpointName = "testEndpoint",
Identity = new AzureNative.MachineLearningServices.Inputs.ResourceIdentityArgs
{
Type = "UserAssigned",
UserAssignedIdentities =
{
{ "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", new AzureNative.MachineLearningServices.Inputs.UserAssignedIdentityMetaArgs
{
ClientId = "string",
PrincipalId = "string",
} },
},
},
Kind = "string",
Location = "string",
Properties = new AzureNative.MachineLearningServices.Inputs.ManagedOnlineDeploymentArgs
{
AppInsightsEnabled = true,
CodeConfiguration = new AzureNative.MachineLearningServices.Inputs.CodeConfigurationArgs
{
CodeId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1",
ScoringScript = "string",
},
Description = "string",
EndpointComputeType = "Managed",
EnvironmentId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123",
LivenessProbe = new AzureNative.MachineLearningServices.Inputs.ProbeSettingsArgs
{
FailureThreshold = 50,
InitialDelay = "PT1M",
Period = "PT1M",
SuccessThreshold = 50,
Timeout = "PT1M",
},
Model = new AzureNative.MachineLearningServices.Inputs.IdAssetReferenceArgs
{
AssetId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123",
ReferenceType = "Id",
},
Properties =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
RequestSettings = new AzureNative.MachineLearningServices.Inputs.OnlineRequestSettingsArgs
{
MaxConcurrentRequestsPerInstance = 5,
MaxQueueWait = "PT1M",
RequestTimeout = "PT1M",
},
ScaleSettings = new AzureNative.MachineLearningServices.Inputs.AutoScaleSettingsArgs
{
PollingInterval = "PT1M",
ScaleType = "Auto",
TargetUtilizationPercentage = 50,
},
},
ResourceGroupName = "testrg123",
Tags =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
WorkspaceName = "workspace123",
});
});Content copied to clipboard
package main
import (
machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := machinelearningservices.NewOnlineDeployment(ctx, "onlineDeployment", &machinelearningservices.OnlineDeploymentArgs{
DeploymentName: pulumi.String("testDeployment"),
EndpointName: pulumi.String("testEndpoint"),
Identity: machinelearningservices.ResourceIdentityResponse{
Type: pulumi.String("UserAssigned"),
UserAssignedIdentities: machinelearningservices.UserAssignedIdentityMetaMap{
"/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity": &machinelearningservices.UserAssignedIdentityMetaArgs{
ClientId: pulumi.String("string"),
PrincipalId: pulumi.String("string"),
},
},
},
Kind: pulumi.String("string"),
Location: pulumi.String("string"),
Properties: machinelearningservices.ManagedOnlineDeployment{
AppInsightsEnabled: true,
CodeConfiguration: machinelearningservices.CodeConfiguration{
CodeId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1",
ScoringScript: "string",
},
Description: "string",
EndpointComputeType: "Managed",
EnvironmentId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123",
LivenessProbe: machinelearningservices.ProbeSettings{
FailureThreshold: 50,
InitialDelay: "PT1M",
Period: "PT1M",
SuccessThreshold: 50,
Timeout: "PT1M",
},
Model: machinelearningservices.IdAssetReference{
AssetId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123",
ReferenceType: "Id",
},
Properties: map[string]interface{}{
"additionalProp1": "string",
"additionalProp2": "string",
"additionalProp3": "string",
},
RequestSettings: machinelearningservices.OnlineRequestSettings{
MaxConcurrentRequestsPerInstance: 5,
MaxQueueWait: "PT1M",
RequestTimeout: "PT1M",
},
ScaleSettings: machinelearningservices.AutoScaleSettings{
PollingInterval: "PT1M",
ScaleType: "Auto",
TargetUtilizationPercentage: 50,
},
},
ResourceGroupName: pulumi.String("testrg123"),
Tags: pulumi.StringMap{
"additionalProp1": pulumi.String("string"),
"additionalProp2": pulumi.String("string"),
"additionalProp3": pulumi.String("string"),
},
WorkspaceName: pulumi.String("workspace123"),
})
if err != nil {
return err
}
return nil
})
}Content copied to clipboard
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.machinelearningservices.OnlineDeployment;
import com.pulumi.azurenative.machinelearningservices.OnlineDeploymentArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var onlineDeployment = new OnlineDeployment("onlineDeployment", OnlineDeploymentArgs.builder()
.deploymentName("testDeployment")
.endpointName("testEndpoint")
.identity(Map.ofEntries(
Map.entry("type", "UserAssigned"),
Map.entry("userAssignedIdentities", Map.of("/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", Map.ofEntries(
Map.entry("clientId", "string"),
Map.entry("principalId", "string")
)))
))
.kind("string")
.location("string")
.properties(Map.ofEntries(
Map.entry("appInsightsEnabled", true),
Map.entry("codeConfiguration", Map.ofEntries(
Map.entry("codeId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/code123/versions/1"),
Map.entry("scoringScript", "string")
)),
Map.entry("description", "string"),
Map.entry("endpointComputeType", "Managed"),
Map.entry("environmentId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/env123"),
Map.entry("livenessProbe", Map.ofEntries(
Map.entry("failureThreshold", 50),
Map.entry("initialDelay", "PT1M"),
Map.entry("period", "PT1M"),
Map.entry("successThreshold", 50),
Map.entry("timeout", "PT1M")
)),
Map.entry("model", Map.ofEntries(
Map.entry("assetId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/model123"),
Map.entry("referenceType", "Id")
)),
Map.entry("properties", K8sOnlineDeploymentArgs.builder()
.additionalProp1("string")
.additionalProp2("string")
.additionalProp3("string")
.build()),
Map.entry("requestSettings", Map.ofEntries(
Map.entry("maxConcurrentRequestsPerInstance", 5),
Map.entry("maxQueueWait", "PT1M"),
Map.entry("requestTimeout", "PT1M")
)),
Map.entry("scaleSettings", Map.ofEntries(
Map.entry("pollingInterval", "PT1M"),
Map.entry("scaleType", "Auto"),
Map.entry("targetUtilizationPercentage", 50)
))
))
.resourceGroupName("testrg123")
.tags(Map.ofEntries(
Map.entry("additionalProp1", "string"),
Map.entry("additionalProp2", "string"),
Map.entry("additionalProp3", "string")
))
.workspaceName("workspace123")
.build());
}
}Content copied to clipboard
Import
An existing resource can be imported using its type token, name, and identifier, e.g.
$ pulumi import azure-native:machinelearningservices:OnlineDeployment testDeployment /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/testrg123/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/onlineEndpoints/testEndpoint/deployments/testDeploymentContent copied to clipboard
Constructors
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constructor(deploymentName: Output<String>? = null, endpointName: Output<String>? = null, identity: Output<ResourceIdentityArgs>? = null, kind: Output<String>? = null, location: Output<String>? = null, properties: Output<Either<K8sOnlineDeploymentArgs, ManagedOnlineDeploymentArgs>>? = null, resourceGroupName: Output<String>? = null, tags: Output<Map<String, String>>? = null, workspaceName: Output<String>? = null)
Properties
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Inference Endpoint Deployment name.
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Inference endpoint name.
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Service identity associated with a resource.
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Required Additional attributes of the entity.
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The name of the resource group. The name is case insensitive.
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Name of Azure Machine Learning workspace.