Machine Learning 컴퓨팅(스토리지 키, 서비스 자격 증명 등)과 관련된 비밀을 가져옵니다.
POST https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/listKeys?api-version=2024-04-01
URI 매개 변수
| Name |
In(다음 안에) |
필수 |
형식 |
Description |
|
computeName
|
path |
True
|
string
|
Azure Machine Learning 컴퓨팅의 이름입니다.
|
|
resourceGroupName
|
path |
True
|
string
|
리소스 그룹의 이름. 이름은 대소문자를 구분하지 않습니다.
|
|
subscriptionId
|
path |
True
|
string
|
대상 구독의 ID입니다.
|
|
workspaceName
|
path |
True
|
string
|
Azure Machine Learning 작업 영역의 이름입니다.
regex 패턴: ^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$
|
|
api-version
|
query |
True
|
string
|
이 작업에 사용할 API 버전입니다.
|
응답
| Name |
형식 |
Description |
|
200 OK
|
ComputeSecrets:
|
성공.
|
|
Other Status Codes
|
ErrorResponse
|
작업이 실패한 이유를 설명하는 오류 응답입니다.
|
보안
azure_auth
Azure Active Directory OAuth2 Flow.
형식:
oauth2
Flow:
implicit
권한 부여 URL:
https://login.microsoftonline.com/common/oauth2/authorize
범위
| Name |
Description |
|
user_impersonation
|
사용자 계정 가장
|
예제
List AKS Compute Keys
샘플 요청
POST https://management.azure.com/subscriptions/34adfa4f-cedf-4dc0-ba29-b6d1a69ab345/resourceGroups/testrg123/providers/Microsoft.MachineLearningServices/workspaces/workspaces123/computes/compute123/listKeys?api-version=2024-04-01
/**
* Samples for Compute ListKeys.
*/
public final class Main {
/*
* x-ms-original-file:
* specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2024-04-01/
* examples/Compute/listKeys.json
*/
/**
* Sample code: List AKS Compute Keys.
*
* @param manager Entry point to MachineLearningManager.
*/
public static void listAKSComputeKeys(com.azure.resourcemanager.machinelearning.MachineLearningManager manager) {
manager.computes().listKeysWithResponse("testrg123", "workspaces123", "compute123",
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
package armmachinelearning_test
import (
"context"
"log"
"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/Compute/listKeys.json
func ExampleComputeClient_ListKeys() {
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)
}
res, err := clientFactory.NewComputeClient().ListKeys(ctx, "testrg123", "workspaces123", "compute123", nil)
if err != nil {
log.Fatalf("failed to finish the request: %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 = armmachinelearning.ComputeClientListKeysResponse{
// ComputeSecretsClassification: &armmachinelearning.AksComputeSecrets{
// AdminKubeConfig: to.Ptr("admin kube config..."),
// ImagePullSecretName: to.Ptr("the image pull secret name"),
// UserKubeConfig: to.Ptr("user kube config..."),
// ComputeType: to.Ptr(armmachinelearning.ComputeTypeAKS),
// },
// }
}
To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue
const { AzureMachineLearningServicesManagementClient } = require("@azure/arm-machinelearning");
const { DefaultAzureCredential } = require("@azure/identity");
/**
* This sample demonstrates how to Gets secrets related to Machine Learning compute (storage keys, service credentials, etc).
*
* @summary Gets secrets related to Machine Learning compute (storage keys, service credentials, etc).
* x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2024-04-01/examples/Compute/listKeys.json
*/
async function listAksComputeKeys() {
const subscriptionId =
process.env["MACHINELEARNING_SUBSCRIPTION_ID"] || "34adfa4f-cedf-4dc0-ba29-b6d1a69ab345";
const resourceGroupName = process.env["MACHINELEARNING_RESOURCE_GROUP"] || "testrg123";
const workspaceName = "workspaces123";
const computeName = "compute123";
const credential = new DefaultAzureCredential();
const client = new AzureMachineLearningServicesManagementClient(credential, subscriptionId);
const result = await client.computeOperations.listKeys(
resourceGroupName,
workspaceName,
computeName,
);
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
using Azure;
using Azure.ResourceManager;
using System;
using System.Threading.Tasks;
using System.Xml;
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/Compute/listKeys.json
// this example is just showing the usage of "Compute_ListKeys" 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 MachineLearningComputeResource created on azure
// for more information of creating MachineLearningComputeResource, please refer to the document of MachineLearningComputeResource
string subscriptionId = "34adfa4f-cedf-4dc0-ba29-b6d1a69ab345";
string resourceGroupName = "testrg123";
string workspaceName = "workspaces123";
string computeName = "compute123";
ResourceIdentifier machineLearningComputeResourceId = MachineLearningComputeResource.CreateResourceIdentifier(subscriptionId, resourceGroupName, workspaceName, computeName);
MachineLearningComputeResource machineLearningCompute = client.GetMachineLearningComputeResource(machineLearningComputeResourceId);
// invoke the operation
MachineLearningComputeSecrets result = await machineLearningCompute.GetKeysAsync();
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
샘플 응답
{
"computeType": "AKS",
"userKubeConfig": "user kube config...",
"adminKubeConfig": "admin kube config...",
"imagePullSecretName": "the image pull secret name"
}
정의
AksComputeSecrets
AKS 기반 Machine Learning 컴퓨팅과 관련된 비밀입니다.
| Name |
형식 |
Description |
|
adminKubeConfig
|
string
|
Kubernetes 클러스터에 연결하는 데 사용할 수 있는 kubeconfig 파일의 콘텐츠입니다.
|
|
computeType
|
string:
AKS
|
컴퓨팅 유형
|
|
imagePullSecretName
|
string
|
이미지 레지스트리 끌어오기 비밀입니다.
|
|
userKubeConfig
|
string
|
Kubernetes 클러스터에 연결하는 데 사용할 수 있는 kubeconfig 파일의 콘텐츠입니다.
|
ComputeType
컴퓨팅 유형
| Name |
형식 |
Description |
|
AKS
|
string
|
|
|
AmlCompute
|
string
|
|
|
ComputeInstance
|
string
|
|
|
DataFactory
|
string
|
|
|
DataLakeAnalytics
|
string
|
|
|
Databricks
|
string
|
|
|
HDInsight
|
string
|
|
|
Kubernetes
|
string
|
|
|
SynapseSpark
|
string
|
|
|
VirtualMachine
|
string
|
|
DatabricksComputeSecrets
Databricks를 기반으로 하는 Machine Learning 컴퓨팅과 관련된 비밀입니다.
| Name |
형식 |
Description |
|
computeType
|
string:
Databricks
|
컴퓨팅 유형
|
|
databricksAccessToken
|
string
|
databricks 계정에 대한 액세스 토큰입니다.
|
ErrorAdditionalInfo
리소스 관리 오류 추가 정보입니다.
| Name |
형식 |
Description |
|
info
|
object
|
추가 정보입니다.
|
|
type
|
string
|
추가 정보 유형입니다.
|
ErrorDetail
오류 세부 정보입니다.
| Name |
형식 |
Description |
|
additionalInfo
|
ErrorAdditionalInfo[]
|
오류 추가 정보입니다.
|
|
code
|
string
|
오류 코드입니다.
|
|
details
|
ErrorDetail[]
|
오류 세부 정보입니다.
|
|
message
|
string
|
오류 메시지입니다.
|
|
target
|
string
|
오류 대상입니다.
|
ErrorResponse
오류 응답
VirtualMachineSecrets
AKS 기반 Machine Learning 컴퓨팅과 관련된 비밀입니다.
VirtualMachineSshCredentials
가상 머신에 대한 자격 증명 관리
| Name |
형식 |
Description |
|
password
|
string
|
관리자 계정의 암호
|
|
privateKeyData
|
string
|
프라이빗 키 데이터
|
|
publicKeyData
|
string
|
공개 키 데이터
|
|
username
|
string
|
관리자 계정의 사용자 이름
|