getWorkspace

import * as pulumi from "@pulumi/pulumi";
import * as azure from "@pulumi/azure";
const existing = azure.machinelearning.getWorkspace({
    name: "example-workspace",
    resourceGroupName: "example-resources",
});
export const id = existingAzurermMachineLearningWorkspace.id;

import pulumi
import pulumi_azure as azure
existing = azure.machinelearning.get_workspace(name="example-workspace",
    resource_group_name="example-resources")
pulumi.export("id", existing_azurerm_machine_learning_workspace["id"])

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Azure = Pulumi.Azure;
return await Deployment.RunAsync(() =>
{
    var existing = Azure.MachineLearning.GetWorkspace.Invoke(new()
    {
        Name = "example-workspace",
        ResourceGroupName = "example-resources",
    });
    return new Dictionary<string, object?>
    {
        ["id"] = existingAzurermMachineLearningWorkspace.Id,
    };
});

package main
import (
	"github.com/pulumi/pulumi-azure/sdk/v6/go/azure/machinelearning"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearning.LookupWorkspace(ctx, &machinelearning.LookupWorkspaceArgs{
			Name:              "example-workspace",
			ResourceGroupName: "example-resources",
		}, nil)
		if err != nil {
			return err
		}
		ctx.Export("id", existingAzurermMachineLearningWorkspace.Id)
		return nil
	})
}

package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azure.machinelearning.MachinelearningFunctions;
import com.pulumi.azure.machinelearning.inputs.GetWorkspaceArgs;
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) {
        final var existing = MachinelearningFunctions.getWorkspace(GetWorkspaceArgs.builder()
            .name("example-workspace")
            .resourceGroupName("example-resources")
            .build());
        ctx.export("id", existingAzurermMachineLearningWorkspace.id());
    }
}

variables:
  existing:
    fn::invoke:
      function: azure:machinelearning:getWorkspace
      arguments:
        name: example-workspace
        resourceGroupName: example-resources
outputs:
  id: ${existingAzurermMachineLearningWorkspace.id}