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AWS SageMaker AI 任務的 受管政策 - Amazon SageMaker AI

本文為英文版的機器翻譯版本,如內容有任何歧義或不一致之處,概以英文版為準。

AWS SageMaker AI 任務的 受管政策

此 AWS 受管政策授予 SageMaker AI 任務執行角色所需的許可,以存取 Amazon S3 中的資料、透過 Amazon API Gateway AgentCore 叫用代理程式、使用 MLflow 追蹤實驗、發佈模型套件、將日誌寫入 CloudWatch、叫用 Lambda 函數和管理 Amazon VPC 網路介面。

AWS 受管政策:AmazonSageMakerJobFullAccess

此政策提供許可,讓 SageMaker AI 任務執行角色存取執行訓練、處理和轉換任務所需的資源。您可以將此政策連接至用作 SageMaker AI 任務執行角色的 IAM 角色。

許可詳細資訊

此政策包含以下許可。

  • s3 – 允許 SageMaker AI 任務從 讀取輸入資料、將輸出資料寫入 ,以及列出 Amazon S3 儲存貯體的內容。僅限於相同帳戶中的資源。

  • kms – 允許 SageMaker AI 任務解密和產生資料金鑰,以使用客戶受管 AWS KMS 金鑰對 Amazon S3 物件進行伺服器端加密。DecryptGenerateDataKey動作只能透過 kms:ViaService限制為 Amazon S3。 DescribeKey 不受kms:ViaService限制。僅限於相同帳戶中的資源。

  • sagemaker (中樞) – 允許描述中樞內容,例如預先建置的模型和演算法。僅限於相同帳戶中的資源。

  • sagemaker (模型套件) – 允許為模型登錄工作流程建立、存取和描述模型套件和模型套件群組。僅限於相同帳戶中的資源。

  • sagemakersagemaker-mlflow – 允許任務使用 MLflow 進行實驗追蹤,包括建立實驗和執行、記錄指標、擷取結果和管理追蹤。僅限於相同帳戶中的資源。

  • bedrock-agentcore – 允許任務透過 Amazon API Gateway AgentCore 執行期叫用 AI 代理程式、停止執行期工作階段,以及取得執行期詳細資訊。僅限於相同帳戶中的資源。

  • ec2 – 允許管理在 Amazon VPC 模式下執行之任務的 Amazon VPC 網路介面,包括建立、刪除和描述網路介面和相關的 Amazon VPC 資源。ec2:CreateTags 動作僅限於 CreateNetworkInterface動作。僅限於相同帳戶中的資源。

  • logs – 允許建立日誌群組、日誌串流,以及將日誌事件寫入 Amazon CloudWatch Logs。僅限於字/aws/sagemaker/*首為 的日誌群組。僅限於相同帳戶中的資源。

  • lambda – 允許在相同帳戶中叫用 Lambda 函數。

{ "Version": "2012-10-17", "Statement": [ { "Sid": "S3Permissions", "Effect": "Allow", "Action": [ "s3:GetObject", "s3:PutObject", "s3:ListBucket" ], "Resource": "*", "Condition": { "StringEquals": { "s3:ResourceAccount": "${aws:PrincipalAccount}" } } }, { "Sid": "KMSPermissions", "Effect": "Allow", "Action": [ "kms:Decrypt", "kms:GenerateDataKey" ], "Resource": "arn:aws:kms:*:*:key/*", "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" }, "StringLike": { "kms:ViaService": "s3.*.amazonaws.com" } } }, { "Sid": "KMSDescribeKey", "Effect": "Allow", "Action": "kms:DescribeKey", "Resource": "arn:aws:kms:*:*:key/*", "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" } } }, { "Sid": "SageMakerHubPermissions", "Effect": "Allow", "Action": [ "sagemaker:DescribeHubContent" ], "Resource": [ "arn:aws:sagemaker:*:*:hub/*", "arn:aws:sagemaker:*:*:hub-content/*" ], "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" } } }, { "Sid": "SageMakerModelPackagePermissions", "Effect": "Allow", "Action": [ "sagemaker:AccessModelPackage", "sagemaker:CreateModelPackage", "sagemaker:DescribeModelPackage", "sagemaker:DescribeModelPackageGroup" ], "Resource": [ "arn:aws:sagemaker:*:*:model-package/*", "arn:aws:sagemaker:*:*:model-package-group/*" ], "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" } } }, { "Sid": "MLflowPermissions", "Effect": "Allow", "Action": [ "sagemaker:DescribeMlflowApp", "sagemaker:CallMlflowAppApi", "sagemaker-mlflow:CreateExperiment", "sagemaker-mlflow:CreateRun", "sagemaker-mlflow:UpdateRun", "sagemaker-mlflow:LogBatch", "sagemaker-mlflow:GetExperimentByName", "sagemaker-mlflow:GetMetricHistory", "sagemaker-mlflow:GetRun", "sagemaker-mlflow:StartTrace", "sagemaker-mlflow:EndTrace", "sagemaker-mlflow:SearchTraces", "sagemaker-mlflow:ListArtifacts" ], "Resource": [ "arn:aws:sagemaker:*:*:mlflow-app/*" ], "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" } } }, { "Sid": "BedrockAgentCorePermissions", "Effect": "Allow", "Action": [ "bedrock-agentcore:InvokeAgentRuntime", "bedrock-agentcore:StopRuntimeSession", "bedrock-agentcore:GetAgentRuntime" ], "Resource": "arn:aws:bedrock-agentcore:*:*:runtime/*", "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" } } }, { "Sid": "EC2NetworkPermissions", "Effect": "Allow", "Action": [ "ec2:CreateNetworkInterface", "ec2:CreateNetworkInterfacePermission", "ec2:DescribeNetworkInterfaces", "ec2:DescribeVpcs", "ec2:DescribeSubnets", "ec2:DescribeSecurityGroups", "ec2:DescribeDhcpOptions" ], "Resource": "*", "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" } } }, { "Sid": "EC2NetworkInterfaceTagPermissions", "Effect": "Allow", "Action": [ "ec2:CreateTags" ], "Resource": "arn:aws:ec2:*:*:network-interface/*", "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}", "ec2:CreateAction": "CreateNetworkInterface" } } }, { "Sid": "EC2NetworkInterfaceDeletePermissions", "Effect": "Allow", "Action": [ "ec2:DeleteNetworkInterface", "ec2:DeleteNetworkInterfacePermission" ], "Resource": "*", "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" } } }, { "Sid": "CloudWatchLogsPermissions", "Effect": "Allow", "Action": [ "logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents", "logs:DescribeLogStreams" ], "Resource": "arn:aws:logs:*:*:log-group:/aws/sagemaker/*", "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" } } }, { "Sid": "LambdaPermissions", "Effect": "Allow", "Action": [ "lambda:InvokeFunction" ], "Resource": "arn:aws:lambda:*:*:function:*", "Condition": { "StringEquals": { "aws:ResourceAccount": "${aws:PrincipalAccount}" } } } ] }

如需詳細資訊,請參閱《 AWS 受管政策參考指南》中的 AmazonSageMakerJobFullAccess

Amazon SageMaker AI 更新至 SageMaker AI 任務受管政策

檢視自此服務開始追蹤這些變更以來SageMaker AI 任務受 AWS 管政策更新的詳細資訊。

政策 版本 變更 日期

AmazonSageMakerJobFullAccess – 新政策

1

初始政策

2026 年 6 月 4 日