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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.
@file:Suppress("NAME_SHADOWING", "DEPRECATION")
package com.pulumi.azurenative.machinelearning.kotlin
import com.pulumi.azurenative.machinelearning.kotlin.outputs.WebServicePropertiesForGraphResponse
import com.pulumi.azurenative.machinelearning.kotlin.outputs.WebServicePropertiesForGraphResponse.Companion.toKotlin
import com.pulumi.core.Output
import com.pulumi.kotlin.KotlinCustomResource
import com.pulumi.kotlin.PulumiTagMarker
import com.pulumi.kotlin.ResourceMapper
import com.pulumi.kotlin.options.CustomResourceOptions
import com.pulumi.kotlin.options.CustomResourceOptionsBuilder
import com.pulumi.resources.Resource
import kotlin.Boolean
import kotlin.String
import kotlin.Suppress
import kotlin.Unit
import kotlin.collections.Map
/**
* Builder for [WebService].
*/
@PulumiTagMarker
public class WebServiceResourceBuilder internal constructor() {
public var name: String? = null
public var args: WebServiceArgs = WebServiceArgs()
public var opts: CustomResourceOptions = CustomResourceOptions()
/**
* @param name The _unique_ name of the resulting resource.
*/
public fun name(`value`: String) {
this.name = value
}
/**
* @param block The arguments to use to populate this resource's properties.
*/
public suspend fun args(block: suspend WebServiceArgsBuilder.() -> Unit) {
val builder = WebServiceArgsBuilder()
block(builder)
this.args = builder.build()
}
/**
* @param block A bag of options that control this resource's behavior.
*/
public suspend fun opts(block: suspend CustomResourceOptionsBuilder.() -> Unit) {
this.opts = com.pulumi.kotlin.options.CustomResourceOptions.opts(block)
}
internal fun build(): WebService {
val builtJavaResource =
com.pulumi.azurenative.machinelearning.WebService(
this.name,
this.args.toJava(),
this.opts.toJava(),
)
return WebService(builtJavaResource)
}
}
/**
* Instance of an Azure ML web service resource.
* Azure REST API version: 2017-01-01. Prior API version in Azure Native 1.x: 2017-01-01.
* Other available API versions: 2016-05-01-preview.
* ## Example Usage
* ### PUT WebService
* ```csharp
* using System.Collections.Generic;
* using System.Linq;
* using Pulumi;
* using AzureNative = Pulumi.AzureNative;
* return await Deployment.RunAsync(() =>
* {
* var webService = new AzureNative.MachineLearning.WebService("webService", new()
* {
* Location = "West US",
* Properties = new AzureNative.MachineLearning.Inputs.WebServicePropertiesForGraphArgs
* {
* Assets =
* {
* { "asset1", new AzureNative.MachineLearning.Inputs.AssetItemArgs
* {
* LocationInfo = new AzureNative.MachineLearning.Inputs.BlobLocationArgs
* {
* Credentials = "",
* Uri = "aml://module/moduleId-1",
* },
* Name = "Execute R Script",
* Type = AzureNative.MachineLearning.AssetType.Module,
* } },
* { "asset2", new AzureNative.MachineLearning.Inputs.AssetItemArgs
* {
* LocationInfo = new AzureNative.MachineLearning.Inputs.BlobLocationArgs
* {
* Credentials = "",
* Uri = "aml://module/moduleId-2",
* },
* Name = "Import Data",
* Type = AzureNative.MachineLearning.AssetType.Module,
* } },
* },
* CommitmentPlan = new AzureNative.MachineLearning.Inputs.CommitmentPlanArgs
* {
* Id = "/subscriptions/subscriptionId/resourceGroups/resourceGroupName/providers/Microsoft.MachineLearning/commitmentPlans/commitmentPlanName",
* },
* Description = "Web Service Description",
* Diagnostics = new AzureNative.MachineLearning.Inputs.DiagnosticsConfigurationArgs
* {
* Level = AzureNative.MachineLearning.DiagnosticsLevel.None,
* },
* ExampleRequest = new AzureNative.MachineLearning.Inputs.ExampleRequestArgs
* {
* Inputs =
* {
* { "input1", new[]
* {
* new[]
* {
* "age",
* },
* new[]
* {
* "workclass",
* },
* new[]
* {
* "fnlwgt",
* },
* new[]
* {
* "education",
* },
* new[]
* {
* "education-num",
* },
* } },
* },
* },
* ExposeSampleData = true,
* Input = new AzureNative.MachineLearning.Inputs.ServiceInputOutputSpecificationArgs
* {
* Description = "",
* Properties =
* {
* { "input1", new AzureNative.MachineLearning.Inputs.TableSpecificationArgs
* {
* Description = "",
* Properties =
* {
* { "column_name", new AzureNative.MachineLearning.Inputs.ColumnSpecificationArgs
* {
* Type = AzureNative.MachineLearning.ColumnType.String,
* XMsIsnullable = false,
* } },
* },
* Title = "",
* Type = "object",
* } },
* },
* Title = "",
* Type = "object",
* },
* MachineLearningWorkspace = new AzureNative.MachineLearning.Inputs.MachineLearningWorkspaceArgs
* {
* Id = "workspaceId",
* },
* Output = new AzureNative.MachineLearning.Inputs.ServiceInputOutputSpecificationArgs
* {
* Description = "",
* Properties =
* {
* { "output1", new AzureNative.MachineLearning.Inputs.TableSpecificationArgs
* {
* Description = "",
* Properties =
* {
* { "age", new AzureNative.MachineLearning.Inputs.ColumnSpecificationArgs
* {
* Format = AzureNative.MachineLearning.ColumnFormat.Int32,
* Type = AzureNative.MachineLearning.ColumnType.Integer,
* XMsIsnullable = true,
* } },
* { "workclass", new AzureNative.MachineLearning.Inputs.ColumnSpecificationArgs
* {
* Type = AzureNative.MachineLearning.ColumnType.String,
* XMsIsnullable = false,
* } },
* },
* Title = "",
* Type = "object",
* } },
* },
* Title = "",
* Type = "object",
* },
* Package = new AzureNative.MachineLearning.Inputs.GraphPackageArgs
* {
* Edges = new[]
* {
* new AzureNative.MachineLearning.Inputs.GraphEdgeArgs
* {
* SourceNodeId = "node2",
* SourcePortId = "Results dataset",
* TargetNodeId = "node1",
* TargetPortId = "Dataset2",
* },
* new AzureNative.MachineLearning.Inputs.GraphEdgeArgs
* {
* SourceNodeId = "node3",
* TargetNodeId = "node1",
* TargetPortId = "Dataset1",
* },
* new AzureNative.MachineLearning.Inputs.GraphEdgeArgs
* {
* SourceNodeId = "node1",
* SourcePortId = "Result Dataset",
* TargetNodeId = "node4",
* },
* },
* GraphParameters = null,
* Nodes =
* {
* { "node1", new AzureNative.MachineLearning.Inputs.GraphNodeArgs
* {
* AssetId = "asset1",
* Parameters =
* {
* { "R Script", new AzureNative.MachineLearning.Inputs.WebServiceParameterArgs
* {
* CertificateThumbprint = "",
* Value = "The R Script",
* } },
* { "R Version", new AzureNative.MachineLearning.Inputs.WebServiceParameterArgs
* {
* CertificateThumbprint = "",
* Value = "CRAN R 3.1.0",
* } },
* },
* } },
* { "node2", new AzureNative.MachineLearning.Inputs.GraphNodeArgs
* {
* AssetId = "asset2",
* Parameters =
* {
* { "Account Key", new AzureNative.MachineLearning.Inputs.WebServiceParameterArgs
* {
* CertificateThumbprint = "TheThumbprint",
* Value = "Encrypted Key",
* } },
* { "Account Name", new AzureNative.MachineLearning.Inputs.WebServiceParameterArgs
* {
* CertificateThumbprint = "",
* Value = "accountName",
* } },
* { "Please Specify Authentication Type", new AzureNative.MachineLearning.Inputs.WebServiceParameterArgs
* {
* CertificateThumbprint = "",
* Value = "Account",
* } },
* { "Please Specify Data Source", new AzureNative.MachineLearning.Inputs.WebServiceParameterArgs
* {
* CertificateThumbprint = "",
* Value = "AzureBlobStorage",
* } },
* },
* } },
* { "node3", new AzureNative.MachineLearning.Inputs.GraphNodeArgs
* {
* InputId = "input1",
* } },
* { "node4", new AzureNative.MachineLearning.Inputs.GraphNodeArgs
* {
* OutputId = "output1",
* } },
* },
* },
* PackageType = "Graph",
* Parameters = null,
* PayloadsInBlobStorage = false,
* ReadOnly = false,
* RealtimeConfiguration = new AzureNative.MachineLearning.Inputs.RealtimeConfigurationArgs
* {
* MaxConcurrentCalls = 4,
* },
* StorageAccount = new AzureNative.MachineLearning.Inputs.StorageAccountArgs
* {
* Key = "Storage_Key",
* Name = "Storage_Name",
* },
* Title = "Web Service Title",
* },
* ResourceGroupName = "OneResourceGroupName",
* Tags =
* {
* { "tag1", "value1" },
* { "tag2", "value2" },
* },
* WebServiceName = "TargetWebServiceName",
* });
* });
* ```
* ```go
* package main
* import (
* machinelearning "github.com/pulumi/pulumi-azure-native-sdk/machinelearning/v2"
* "github.com/pulumi/pulumi/sdk/v3/go/pulumi"
* )
* func main() {
* pulumi.Run(func(ctx *pulumi.Context) error {
* _, err := machinelearning.NewWebService(ctx, "webService", &machinelearning.WebServiceArgs{
* Location: pulumi.String("West US"),
* Properties: &machinelearning.WebServicePropertiesForGraphArgs{
* Assets: machinelearning.AssetItemMap{
* "asset1": &machinelearning.AssetItemArgs{
* LocationInfo: &machinelearning.BlobLocationArgs{
* Credentials: pulumi.String(""),
* Uri: pulumi.String("aml://module/moduleId-1"),
* },
* Name: pulumi.String("Execute R Script"),
* Type: pulumi.String(machinelearning.AssetTypeModule),
* },
* "asset2": &machinelearning.AssetItemArgs{
* LocationInfo: &machinelearning.BlobLocationArgs{
* Credentials: pulumi.String(""),
* Uri: pulumi.String("aml://module/moduleId-2"),
* },
* Name: pulumi.String("Import Data"),
* Type: pulumi.String(machinelearning.AssetTypeModule),
* },
* },
* CommitmentPlan: &machinelearning.CommitmentPlanTypeArgs{
* Id: pulumi.String("/subscriptions/subscriptionId/resourceGroups/resourceGroupName/providers/Microsoft.MachineLearning/commitmentPlans/commitmentPlanName"),
* },
* Description: pulumi.String("Web Service Description"),
* Diagnostics: &machinelearning.DiagnosticsConfigurationArgs{
* Level: pulumi.String(machinelearning.DiagnosticsLevelNone),
* },
* ExampleRequest: &machinelearning.ExampleRequestArgs{
* Inputs: pulumi.ArrayArrayMap{
* "input1": pulumi.ArrayArray{
* pulumi.Array{
* pulumi.Any("age"),
* },
* pulumi.Array{
* pulumi.Any("workclass"),
* },
* pulumi.Array{
* pulumi.Any("fnlwgt"),
* },
* pulumi.Array{
* pulumi.Any("education"),
* },
* pulumi.Array{
* pulumi.Any("education-num"),
* },
* },
* },
* },
* ExposeSampleData: pulumi.Bool(true),
* Input: &machinelearning.ServiceInputOutputSpecificationArgs{
* Description: pulumi.String(""),
* Properties: machinelearning.TableSpecificationMap{
* "input1": &machinelearning.TableSpecificationArgs{
* Description: pulumi.String(""),
* Properties: machinelearning.ColumnSpecificationMap{
* "column_name": &machinelearning.ColumnSpecificationArgs{
* Type: pulumi.String(machinelearning.ColumnTypeString),
* XMsIsnullable: pulumi.Bool(false),
* },
* },
* Title: pulumi.String(""),
* Type: pulumi.String("object"),
* },
* },
* Title: pulumi.String(""),
* Type: pulumi.String("object"),
* },
* MachineLearningWorkspace: &machinelearning.MachineLearningWorkspaceArgs{
* Id: pulumi.String("workspaceId"),
* },
* Output: &machinelearning.ServiceInputOutputSpecificationArgs{
* Description: pulumi.String(""),
* Properties: machinelearning.TableSpecificationMap{
* "output1": &machinelearning.TableSpecificationArgs{
* Description: pulumi.String(""),
* Properties: machinelearning.ColumnSpecificationMap{
* "age": &machinelearning.ColumnSpecificationArgs{
* Format: pulumi.String(machinelearning.ColumnFormatInt32),
* Type: pulumi.String(machinelearning.ColumnTypeInteger),
* XMsIsnullable: pulumi.Bool(true),
* },
* "workclass": &machinelearning.ColumnSpecificationArgs{
* Type: pulumi.String(machinelearning.ColumnTypeString),
* XMsIsnullable: pulumi.Bool(false),
* },
* },
* Title: pulumi.String(""),
* Type: pulumi.String("object"),
* },
* },
* Title: pulumi.String(""),
* Type: pulumi.String("object"),
* },
* Package: &machinelearning.GraphPackageArgs{
* Edges: machinelearning.GraphEdgeArray{
* &machinelearning.GraphEdgeArgs{
* SourceNodeId: pulumi.String("node2"),
* SourcePortId: pulumi.String("Results dataset"),
* TargetNodeId: pulumi.String("node1"),
* TargetPortId: pulumi.String("Dataset2"),
* },
* &machinelearning.GraphEdgeArgs{
* SourceNodeId: pulumi.String("node3"),
* TargetNodeId: pulumi.String("node1"),
* TargetPortId: pulumi.String("Dataset1"),
* },
* &machinelearning.GraphEdgeArgs{
* SourceNodeId: pulumi.String("node1"),
* SourcePortId: pulumi.String("Result Dataset"),
* TargetNodeId: pulumi.String("node4"),
* },
* },
* GraphParameters: nil,
* Nodes: machinelearning.GraphNodeMap{
* "node1": &machinelearning.GraphNodeArgs{
* AssetId: pulumi.String("asset1"),
* Parameters: machinelearning.WebServiceParameterMap{
* "R Script": &machinelearning.WebServiceParameterArgs{
* CertificateThumbprint: pulumi.String(""),
* Value: pulumi.Any("The R Script"),
* },
* "R Version": &machinelearning.WebServiceParameterArgs{
* CertificateThumbprint: pulumi.String(""),
* Value: pulumi.Any("CRAN R 3.1.0"),
* },
* },
* },
* "node2": &machinelearning.GraphNodeArgs{
* AssetId: pulumi.String("asset2"),
* Parameters: machinelearning.WebServiceParameterMap{
* "Account Key": &machinelearning.WebServiceParameterArgs{
* CertificateThumbprint: pulumi.String("TheThumbprint"),
* Value: pulumi.Any("Encrypted Key"),
* },
* "Account Name": &machinelearning.WebServiceParameterArgs{
* CertificateThumbprint: pulumi.String(""),
* Value: pulumi.Any("accountName"),
* },
* "Please Specify Authentication Type": &machinelearning.WebServiceParameterArgs{
* CertificateThumbprint: pulumi.String(""),
* Value: pulumi.Any("Account"),
* },
* "Please Specify Data Source": &machinelearning.WebServiceParameterArgs{
* CertificateThumbprint: pulumi.String(""),
* Value: pulumi.Any("AzureBlobStorage"),
* },
* },
* },
* "node3": &machinelearning.GraphNodeArgs{
* InputId: pulumi.String("input1"),
* },
* "node4": &machinelearning.GraphNodeArgs{
* OutputId: pulumi.String("output1"),
* },
* },
* },
* PackageType: pulumi.String("Graph"),
* Parameters: nil,
* PayloadsInBlobStorage: pulumi.Bool(false),
* ReadOnly: pulumi.Bool(false),
* RealtimeConfiguration: &machinelearning.RealtimeConfigurationArgs{
* MaxConcurrentCalls: pulumi.Int(4),
* },
* StorageAccount: &machinelearning.StorageAccountArgs{
* Key: pulumi.String("Storage_Key"),
* Name: pulumi.String("Storage_Name"),
* },
* Title: pulumi.String("Web Service Title"),
* },
* ResourceGroupName: pulumi.String("OneResourceGroupName"),
* Tags: pulumi.StringMap{
* "tag1": pulumi.String("value1"),
* "tag2": pulumi.String("value2"),
* },
* WebServiceName: pulumi.String("TargetWebServiceName"),
* })
* if err != nil {
* return err
* }
* return nil
* })
* }
* ```
* ```java
* package generated_program;
* import com.pulumi.Context;
* import com.pulumi.Pulumi;
* import com.pulumi.core.Output;
* import com.pulumi.azurenative.machinelearning.WebService;
* import com.pulumi.azurenative.machinelearning.WebServiceArgs;
* import com.pulumi.azurenative.machinelearning.inputs.WebServicePropertiesForGraphArgs;
* import com.pulumi.azurenative.machinelearning.inputs.CommitmentPlanArgs;
* import com.pulumi.azurenative.machinelearning.inputs.DiagnosticsConfigurationArgs;
* import com.pulumi.azurenative.machinelearning.inputs.ExampleRequestArgs;
* import com.pulumi.azurenative.machinelearning.inputs.ServiceInputOutputSpecificationArgs;
* import com.pulumi.azurenative.machinelearning.inputs.MachineLearningWorkspaceArgs;
* import com.pulumi.azurenative.machinelearning.inputs.GraphPackageArgs;
* import com.pulumi.azurenative.machinelearning.inputs.RealtimeConfigurationArgs;
* import com.pulumi.azurenative.machinelearning.inputs.StorageAccountArgs;
* 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 webService = new WebService("webService", WebServiceArgs.builder()
* .location("West US")
* .properties(WebServicePropertiesForGraphArgs.builder()
* .assets(Map.ofEntries(
* Map.entry("asset1", Map.ofEntries(
* Map.entry("locationInfo", Map.ofEntries(
* Map.entry("credentials", ""),
* Map.entry("uri", "aml://module/moduleId-1")
* )),
* Map.entry("name", "Execute R Script"),
* Map.entry("type", "Module")
* )),
* Map.entry("asset2", Map.ofEntries(
* Map.entry("locationInfo", Map.ofEntries(
* Map.entry("credentials", ""),
* Map.entry("uri", "aml://module/moduleId-2")
* )),
* Map.entry("name", "Import Data"),
* Map.entry("type", "Module")
* ))
* ))
* .commitmentPlan(CommitmentPlanArgs.builder()
* .id("/subscriptions/subscriptionId/resourceGroups/resourceGroupName/providers/Microsoft.MachineLearning/commitmentPlans/commitmentPlanName")
* .build())
* .description("Web Service Description")
* .diagnostics(DiagnosticsConfigurationArgs.builder()
* .level("None")
* .build())
* .exampleRequest(ExampleRequestArgs.builder()
* .inputs(Map.of("input1",
* "age",
* "workclass",
* "fnlwgt",
* "education",
* "education-num"))
* .build())
* .exposeSampleData(true)
* .input(ServiceInputOutputSpecificationArgs.builder()
* .description("")
* .properties(Map.of("input1", Map.ofEntries(
* Map.entry("description", ""),
* Map.entry("properties", Map.of("column_name", Map.ofEntries(
* Map.entry("type", "String"),
* Map.entry("xMsIsnullable", false)
* ))),
* Map.entry("title", ""),
* Map.entry("type", "object")
* )))
* .title("")
* .type("object")
* .build())
* .machineLearningWorkspace(MachineLearningWorkspaceArgs.builder()
* .id("workspaceId")
* .build())
* .output(ServiceInputOutputSpecificationArgs.builder()
* .description("")
* .properties(Map.of("output1", Map.ofEntries(
* Map.entry("description", ""),
* Map.entry("properties", Map.ofEntries(
* Map.entry("age", Map.ofEntries(
* Map.entry("format", "Int32"),
* Map.entry("type", "Integer"),
* Map.entry("xMsIsnullable", true)
* )),
* Map.entry("workclass", Map.ofEntries(
* Map.entry("type", "String"),
* Map.entry("xMsIsnullable", false)
* ))
* )),
* Map.entry("title", ""),
* Map.entry("type", "object")
* )))
* .title("")
* .type("object")
* .build())
* .package_(GraphPackageArgs.builder()
* .edges(
* GraphEdgeArgs.builder()
* .sourceNodeId("node2")
* .sourcePortId("Results dataset")
* .targetNodeId("node1")
* .targetPortId("Dataset2")
* .build(),
* GraphEdgeArgs.builder()
* .sourceNodeId("node3")
* .targetNodeId("node1")
* .targetPortId("Dataset1")
* .build(),
* GraphEdgeArgs.builder()
* .sourceNodeId("node1")
* .sourcePortId("Result Dataset")
* .targetNodeId("node4")
* .build())
* .graphParameters()
* .nodes(Map.ofEntries(
* Map.entry("node1", Map.ofEntries(
* Map.entry("assetId", "asset1"),
* Map.entry("parameters", Map.ofEntries(
* Map.entry("R Script", Map.ofEntries(
* Map.entry("certificateThumbprint", ""),
* Map.entry("value", "The R Script")
* )),
* Map.entry("R Version", Map.ofEntries(
* Map.entry("certificateThumbprint", ""),
* Map.entry("value", "CRAN R 3.1.0")
* ))
* ))
* )),
* Map.entry("node2", Map.ofEntries(
* Map.entry("assetId", "asset2"),
* Map.entry("parameters", Map.ofEntries(
* Map.entry("Account Key", Map.ofEntries(
* Map.entry("certificateThumbprint", "TheThumbprint"),
* Map.entry("value", "Encrypted Key")
* )),
* Map.entry("Account Name", Map.ofEntries(
* Map.entry("certificateThumbprint", ""),
* Map.entry("value", "accountName")
* )),
* Map.entry("Please Specify Authentication Type", Map.ofEntries(
* Map.entry("certificateThumbprint", ""),
* Map.entry("value", "Account")
* )),
* Map.entry("Please Specify Data Source", Map.ofEntries(
* Map.entry("certificateThumbprint", ""),
* Map.entry("value", "AzureBlobStorage")
* ))
* ))
* )),
* Map.entry("node3", Map.of("inputId", "input1")),
* Map.entry("node4", Map.of("outputId", "output1"))
* ))
* .build())
* .packageType("Graph")
* .parameters()
* .payloadsInBlobStorage(false)
* .readOnly(false)
* .realtimeConfiguration(RealtimeConfigurationArgs.builder()
* .maxConcurrentCalls(4)
* .build())
* .storageAccount(StorageAccountArgs.builder()
* .key("Storage_Key")
* .name("Storage_Name")
* .build())
* .title("Web Service Title")
* .build())
* .resourceGroupName("OneResourceGroupName")
* .tags(Map.ofEntries(
* Map.entry("tag1", "value1"),
* Map.entry("tag2", "value2")
* ))
* .webServiceName("TargetWebServiceName")
* .build());
* }
* }
* ```
* ## Import
* An existing resource can be imported using its type token, name, and identifier, e.g.
* ```sh
* $ pulumi import azure-native:machinelearning:WebService myresource1 /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearning/webServices/{webServiceName}
* ```
*/
public class WebService internal constructor(
override val javaResource: com.pulumi.azurenative.machinelearning.WebService,
) : KotlinCustomResource(javaResource, WebServiceMapper) {
/**
* Specifies the location of the resource.
*/
public val location: Output
get() = javaResource.location().applyValue({ args0 -> args0 })
/**
* Specifies the name of the resource.
*/
public val name: Output
get() = javaResource.name().applyValue({ args0 -> args0 })
/**
* Contains the property payload that describes the web service.
*/
public val properties: Output
get() = javaResource.properties().applyValue({ args0 -> args0.let({ args0 -> toKotlin(args0) }) })
/**
* Contains resource tags defined as key/value pairs.
*/
public val tags: Output>?
get() = javaResource.tags().applyValue({ args0 ->
args0.map({ args0 ->
args0.map({ args0 ->
args0.key.to(args0.value)
}).toMap()
}).orElse(null)
})
/**
* Specifies the type of the resource.
*/
public val type: Output
get() = javaResource.type().applyValue({ args0 -> args0 })
}
public object WebServiceMapper : ResourceMapper {
override fun supportsMappingOfType(javaResource: Resource): Boolean =
com.pulumi.azurenative.machinelearning.WebService::class == javaResource::class
override fun map(javaResource: Resource): WebService = WebService(
javaResource as
com.pulumi.azurenative.machinelearning.WebService,
)
}
/**
* @see [WebService].
* @param name The _unique_ name of the resulting resource.
* @param block Builder for [WebService].
*/
public suspend fun webService(name: String, block: suspend WebServiceResourceBuilder.() -> Unit): WebService {
val builder = WebServiceResourceBuilder()
builder.name(name)
block(builder)
return builder.build()
}
/**
* @see [WebService].
* @param name The _unique_ name of the resulting resource.
*/
public fun webService(name: String): WebService {
val builder = WebServiceResourceBuilder()
builder.name(name)
return builder.build()
}
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