Managed Network Provisions - Provision Managed Network

Dienst:

Machine Learning

API-Version:

2024-04-01

Stellt das verwaltete Netzwerk eines Maschinellen Lernarbeitsbereichs bereit.

POST https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/provisionManagedNetwork?api-version=2024-04-01

URI-Parameter

Name	In	Erforderlich	Typ	Beschreibung
resourceGroupName	path	True	string minLength: 1 maxLength: 90	Der Name der Ressourcengruppe. Bei dem Namen wird die Groß-/Kleinschreibung nicht beachtet.
subscriptionId	path	True	string minLength: 1	Die ID des Zielabonnements.
workspaceName	path	True	string pattern: ^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$	Name des Azure Machine Learning-Arbeitsbereichs.
api-version	query	True	string minLength: 1	Die API-Version, die für diesen Vorgang verwendet werden soll.

Anforderungstext

Name	Typ	Beschreibung
includeSpark	boolean

Antworten

Name	Typ	Beschreibung
200 OK	ManagedNetworkProvisionStatus	Die Anforderung war erfolgreich; die Anforderung war wohlgeformt und richtig empfangen.
202 Accepted		Angenommen Header Location: string Retry-After: integer
Other Status Codes	ErrorResponse	Fehler

Sicherheit

azure_auth

Azure Active Directory OAuth2-Fluss.

Typ: oauth2
Ablauf: implicit
Autorisierungs-URL: https://login.microsoftonline.com/common/oauth2/authorize

Bereiche

Name	Beschreibung
user_impersonation	Identitätswechsel ihres Benutzerkontos

Beispiele

Provision ManagedNetwork

Beispielanforderung

HTTP

POST https://management.azure.com/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/test-rg/providers/Microsoft.MachineLearningServices/workspaces/aml-workspace-name/provisionManagedNetwork?api-version=2024-04-01

{
  "includeSpark": false
}

Java

import com.azure.resourcemanager.machinelearning.models.ManagedNetworkProvisionOptions;

/**
 * Samples for ManagedNetworkProvisions ProvisionManagedNetwork.
 */
public final class Main {
    /*
     * x-ms-original-file:
     * specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2024-04-01/
     * examples/ManagedNetwork/provision.json
     */
    /**
     * Sample code: Provision ManagedNetwork.
     * 
     * @param manager Entry point to MachineLearningManager.
     */
    public static void
        provisionManagedNetwork(com.azure.resourcemanager.machinelearning.MachineLearningManager manager) {
        manager.managedNetworkProvisions().provisionManagedNetwork("test-rg", "aml-workspace-name",
            new ManagedNetworkProvisionOptions().withIncludeSpark(false), com.azure.core.util.Context.NONE);
    }
}

To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue

Go

package armmachinelearning_test

import (
	"context"
	"log"

	"github.com/Azure/azure-sdk-for-go/sdk/azcore/to"
	"github.com/Azure/azure-sdk-for-go/sdk/azidentity"
	"github.com/Azure/azure-sdk-for-go/sdk/resourcemanager/machinelearning/armmachinelearning/v4"
)

// Generated from example definition: https://github.com/Azure/azure-rest-api-specs/blob/9778042723206fbc582306dcb407bddbd73df005/specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2024-04-01/examples/ManagedNetwork/provision.json
func ExampleManagedNetworkProvisionsClient_BeginProvisionManagedNetwork() {
	cred, err := azidentity.NewDefaultAzureCredential(nil)
	if err != nil {
		log.Fatalf("failed to obtain a credential: %v", err)
	}
	ctx := context.Background()
	clientFactory, err := armmachinelearning.NewClientFactory("<subscription-id>", cred, nil)
	if err != nil {
		log.Fatalf("failed to create client: %v", err)
	}
	poller, err := clientFactory.NewManagedNetworkProvisionsClient().BeginProvisionManagedNetwork(ctx, "test-rg", "aml-workspace-name", &armmachinelearning.ManagedNetworkProvisionsClientBeginProvisionManagedNetworkOptions{Body: &armmachinelearning.ManagedNetworkProvisionOptions{
		IncludeSpark: to.Ptr(false),
	},
	})
	if err != nil {
		log.Fatalf("failed to finish the request: %v", err)
	}
	res, err := poller.PollUntilDone(ctx, nil)
	if err != nil {
		log.Fatalf("failed to pull the result: %v", err)
	}
	// You could use response here. We use blank identifier for just demo purposes.
	_ = res
	// If the HTTP response code is 200 as defined in example definition, your response structure would look as follows. Please pay attention that all the values in the output are fake values for just demo purposes.
	// res.ManagedNetworkProvisionStatus = armmachinelearning.ManagedNetworkProvisionStatus{
	// 	SparkReady: to.Ptr(true),
	// 	Status: to.Ptr(armmachinelearning.ManagedNetworkStatusActive),
	// }
}

To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue

JavaScript

const { AzureMachineLearningServicesManagementClient } = require("@azure/arm-machinelearning");
const { DefaultAzureCredential } = require("@azure/identity");

/**
 * This sample demonstrates how to Provisions the managed network of a machine learning workspace.
 *
 * @summary Provisions the managed network of a machine learning workspace.
 * x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2024-04-01/examples/ManagedNetwork/provision.json
 */
async function provisionManagedNetwork() {
  const subscriptionId =
    process.env["MACHINELEARNING_SUBSCRIPTION_ID"] || "00000000-1111-2222-3333-444444444444";
  const resourceGroupName = process.env["MACHINELEARNING_RESOURCE_GROUP"] || "test-rg";
  const workspaceName = "aml-workspace-name";
  const body = { includeSpark: false };
  const options = { body };
  const credential = new DefaultAzureCredential();
  const client = new AzureMachineLearningServicesManagementClient(credential, subscriptionId);
  const result = await client.managedNetworkProvisions.beginProvisionManagedNetworkAndWait(
    resourceGroupName,
    workspaceName,
    options,
  );
  console.log(result);
}

To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue

dotnet

using Azure;
using Azure.ResourceManager;
using System;
using System.Threading.Tasks;
using Azure.Core;
using Azure.Identity;
using Azure.ResourceManager.MachineLearning.Models;
using Azure.ResourceManager.MachineLearning;

// Generated from example definition: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2024-04-01/examples/ManagedNetwork/provision.json
// this example is just showing the usage of "ManagedNetworkProvisions_ProvisionManagedNetwork" operation, for the dependent resources, they will have to be created separately.

// get your azure access token, for more details of how Azure SDK get your access token, please refer to https://learn.microsoft.com/en-us/dotnet/azure/sdk/authentication?tabs=command-line
TokenCredential cred = new DefaultAzureCredential();
// authenticate your client
ArmClient client = new ArmClient(cred);

// this example assumes you already have this MachineLearningWorkspaceResource created on azure
// for more information of creating MachineLearningWorkspaceResource, please refer to the document of MachineLearningWorkspaceResource
string subscriptionId = "00000000-1111-2222-3333-444444444444";
string resourceGroupName = "test-rg";
string workspaceName = "aml-workspace-name";
ResourceIdentifier machineLearningWorkspaceResourceId = MachineLearningWorkspaceResource.CreateResourceIdentifier(subscriptionId, resourceGroupName, workspaceName);
MachineLearningWorkspaceResource machineLearningWorkspace = client.GetMachineLearningWorkspaceResource(machineLearningWorkspaceResourceId);

// invoke the operation
ManagedNetworkProvisionContent content = new ManagedNetworkProvisionContent
{
    IncludeSpark = false,
};
ArmOperation<ManagedNetworkProvisionStatus> lro = await machineLearningWorkspace.ProvisionManagedNetworkManagedNetworkProvisionAsync(WaitUntil.Completed, content: content);
ManagedNetworkProvisionStatus result = lro.Value;

Console.WriteLine($"Succeeded: {result}");

To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue

Beispiel für eine Antwort

Statuscode:

202

Location: location_url_to_poll_for_status

Statuscode:

200

{
  "status": "Active",
  "sparkReady": true
}

Definitionen

Name	Beschreibung
ErrorAdditionalInfo	Der Ressourcenverwaltungsfehler zusätzliche Informationen.
ErrorDetail	Das Fehlerdetails.
ErrorResponse	Fehlerantwort
ManagedNetworkProvisionOptions	Verwaltete Netzwerkbereitstellungsoptionen für verwaltetes Netzwerk eines Machine Learning-Arbeitsbereichs.
ManagedNetworkProvisionStatus	Status der Bereitstellung für das verwaltete Netzwerk eines Machine Learning-Arbeitsbereichs.
ManagedNetworkStatus	Status für das verwaltete Netzwerk eines Maschinellen Lernarbeitsbereichs.

ErrorAdditionalInfo

Objekt

Der Ressourcenverwaltungsfehler zusätzliche Informationen.

Name	Typ	Beschreibung
info	object	Die zusätzlichen Informationen.
type	string	Der zusätzliche Informationstyp.

ErrorDetail

Objekt

Das Fehlerdetails.

Name	Typ	Beschreibung
additionalInfo	ErrorAdditionalInfo[]	Die zusätzlichen Informationen des Fehlers.
code	string	Der Fehlercode.
details	ErrorDetail[]	Die Fehlerdetails.
message	string	Die Fehlermeldung.
target	string	Das Fehlerziel.

ErrorResponse

Objekt

Fehlerantwort

Name	Typ	Beschreibung
error	ErrorDetail	Das Fehlerobjekt.

ManagedNetworkProvisionOptions

Objekt

Verwaltete Netzwerkbereitstellungsoptionen für verwaltetes Netzwerk eines Machine Learning-Arbeitsbereichs.

Name	Typ	Beschreibung
includeSpark	boolean

ManagedNetworkProvisionStatus

Objekt

Status der Bereitstellung für das verwaltete Netzwerk eines Machine Learning-Arbeitsbereichs.

Name	Typ	Beschreibung
sparkReady	boolean
status	ManagedNetworkStatus	Status für das verwaltete Netzwerk eines Maschinellen Lernarbeitsbereichs.

ManagedNetworkStatus

Enumeration

Status für das verwaltete Netzwerk eines Maschinellen Lernarbeitsbereichs.

Wert	Beschreibung
Active
Inactive