Azure Data Lake Storage Gen2 (ADLS Gen2) offers robust security features, but directly incorporating its Access Control Lists (ACLs) into Azure AI Search indexes can be tricky. Fear not, data wizards! This guide explores two methods to achieve this:

Method 1: Custom Code with Azure SDKs (For Granular Control)

This approach empowers you with fine-grained access control information by writing custom code.

Prerequisites:

• Gear Up: You'll need .NET 3.0 or later and an Azure setup with:
  • An Azure AI Search service
  • A storage account with ADLS Gen2 enabled
• Code Companions: заручиться поддержкой библиотек (zaruchit'sya podderzhkoy bibliotek - enlist the support of libraries) in Russian:
  • Azure Search SDK: https://www.nuget.org/packages/Microsoft.Azure.Search/
  • Azure Storage SDK: https://www.nuget.org/packages/Azure.Storage.Blobs/

Deployment Dynasty:

1. Code Crusaders: Craft code to connect to both Azure Search and your ADLS Gen2 storage account.
2. ACL Acquisition: Design logic to retrieve ACL information for specific files or folders within ADLS Gen2.
3. Data Doctoring: Process the retrieved ACL data into a format friendly for indexing (e.g., convert user IDs to readable names).
4. Indexing Infusion: Utilize the Azure Search SDK to index the content of the file alongside the processed ACL information as additional fields within your index schema.

Resources:

• Code Comrade: A code sample demonstrating similar concepts: https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/storage/Azure.Storage.Files.DataLake/README.md

Method 2: Managed Identity with Azure AD (Preview - For Simpler Approach)

This method (currently in preview) leverages managed identities and Azure AD for authentication, offering some visibility into access permissions during indexing.

Prerequisites:

• Azure Arsenal: Ensure you have:
  • An Azure Search service with a managed identity enabled
  • A storage account with ADLS Gen2 enabled
  • Azure AD configuration for access control

Deployment Dynasty:

1. Managed Identity Marvels: Configure a managed identity for your Azure Search service.
2. Azure AD Adept: Set up Azure AD access control for the specific data you want to index in ADLS Gen2.
3. Indexing Inferences: During indexing, Azure Search might leverage its managed identity and Azure AD configuration to infer some access permission information. However, the level of detail might be limited compared to the custom code approach.

Note: This functionality is a preview and might have limitations. Stay tuned to Microsoft documentation for the latest updates.

Consider These Carefully:

• Coding Complexity: Both approaches require some development effort. Choose the method that best suits your needs.
• Security Stronghold: Ensure proper access controls are in place for both Azure Search and ADLS Gen2 to safeguard sensitive data.

Choosing Your Champion:

For the most control over ACL information, the custom code approach with Azure SDKs reigns supreme. If you prefer a potentially simpler option with a preview feature and are comfortable with a less detailed access permission view, the managed identity with Azure AD approach might be your champion.

Remember:

• Target the right keywords when searching for more information online. Consider "Azure Search index ADLS Gen2 ACLs" or similar phrases to find relevant resources.

By following these steps and considering these factors, you can empower your Azure AI Search indexes with valuable access control information from ADLS Gen2.