Which authentication method uses tokens or service principals in Azure Machine Learning?

Credential-based authentication is the method that uses tokens or service principals within Azure Machine Learning. This type of authentication allows applications or services to authenticate using a set of credentials without requiring user interaction. In Azure, a service principal is an identity created for use with applications, hosted services, and automated tools, effectively enabling your application to log in to Azure resources securely.

When you use credential-based authentication, you often obtain a token that can be used to authorize API requests, making it crucial for services to interact with Azure's resources seamlessly. This method is particularly robust because it can manage permissions and security more effectively, often integrating with Azure Active Directory to provide secure access controls.

In contrast, identity-based authentication typically involves user credentials and interactions, requiring users to log in directly, which does not inherently use tokens for automated access. Session-based authentication relies on sessions that can expire over time, while API key authentication uses simpler key-value pairs instead of tokens or service principals, making it less versatile in complex Azure environments. Hence, focusing on credential-based authentication in Azure Machine Learning emphasizes the importance of using secure, automated methods to ensure seamless interactions with services and data.