问题描述
我已经创建了一些 Azure机器学习工作区，并将它们与经典"存储帐户相关联；但希望将它们与非经典"(或任何术语)存储帐户相关联.
I've created some Azure Machine Learning Workspaces and associated them with "classic" storage accounts; but would like to have them associated with "not-classic" (or whatever the term is) storage accounts.
是否有一种方法可以将存储帐户从经典"转换为标准，或更改与机器学习工作区相关联的存储帐户?
Is there a way to convert the storage accounts from "classic", or to change the storage account associated with a Machine Learning Workspace?
推荐答案
到目前为止，还没有自动将经典"存储帐户转换为"Azure资源管理器(ARM)"存储帐户的方法.今天，您需要将数据从传统存储帐户复制到新存储帐户.
As of today, there's no automatic way of converting a "Classic" storage account into "Azure Resource Manager (ARM)" storage account. Today, you would need to copy data from a classic storage account to a new storage account.
话虽如此，两种存储帐户中的数据存储方式没有什么不同.它们都支持通过帐户名称/密钥和/或共享访问签名进行连接.区别在于如何管理这些存储帐户本身.在ARM存储帐户中，您可以分配基于角色的细粒度访问控制(RBAC)，以控制用户在管理存储帐户方面可以执行的操作(例如更新，删除，查看/重新生成密钥).
Having said that, there's no difference in how the data is stored in both kinds of storage accounts. Both of them support connecting via account name/key and/or shared access signature. The difference is how these storage account themselves are managed. In ARM storage accounts, you can assign granular role-based access control (RBAC) to control what a user can do as far as managing the storage accounts (like updating, deleting, viewing/regenerating keys).
关于您有关在ML工作空间中使用新存储帐户的问题，我认为今天不可能(尽管我可能错了).原因是，ML仍然是通过旧的门户网站进行管理的，而该门户网站没有管理ARM存储帐户的功能.
Regarding your question about using new storage accounts with ML workspace, I don't think it's possible today (I may be wrong though). Reason being, ML is still managed via old portal which doesn't have the capability to manage ARM storage accounts.
这篇关于将Azure“经典"转换为储存帐户的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！