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v3.9.16
  • 🏠Deep Lake Docs
  • List of ML Datasets
  • 🏗️SETUP
    • Installation
    • User Authentication
      • Workload Identities (Azure Only)
    • Storage and Credentials
      • Storage Options
      • Setting up Deep Lake in Your Cloud
        • Microsoft Azure
          • Configure Azure SSO on Activeloop
          • Provisioning Federated Credentials
          • Enabling CORS
        • Google Cloud
          • Provisioning Federated Credentials
          • Enabling CORS
        • Amazon Web Services
          • Provisioning Role-Based Access
          • Enabling CORS
  • 📚Examples
    • Deep Learning
      • Deep Learning Quickstart
      • Deep Learning Guide
        • Step 1: Hello World
        • Step 2: Creating Deep Lake Datasets
        • Step 3: Understanding Compression
        • Step 4: Accessing and Updating Data
        • Step 5: Visualizing Datasets
        • Step 6: Using Activeloop Storage
        • Step 7: Connecting Deep Lake Datasets to ML Frameworks
        • Step 8: Parallel Computing
        • Step 9: Dataset Version Control
        • Step 10: Dataset Filtering
      • Deep Learning Tutorials
        • Creating Datasets
          • Creating Complex Datasets
          • Creating Object Detection Datasets
          • Creating Time-Series Datasets
          • Creating Datasets with Sequences
          • Creating Video Datasets
        • Training Models
          • Splitting Datasets for Training
          • Training an Image Classification Model in PyTorch
          • Training Models Using MMDetection
          • Training Models Using PyTorch Lightning
          • Training on AWS SageMaker
          • Training an Object Detection and Segmentation Model in PyTorch
        • Updating Datasets
        • Data Processing Using Parallel Computing
      • Deep Learning Playbooks
        • Querying, Training and Editing Datasets with Data Lineage
        • Evaluating Model Performance
        • Training Reproducibility Using Deep Lake and Weights & Biases
        • Working with Videos
      • Deep Lake Dataloaders
      • API Summary
    • RAG
      • RAG Quickstart
      • RAG Tutorials
        • Vector Store Basics
        • Vector Search Options
          • LangChain API
          • Deep Lake Vector Store API
          • Managed Database REST API
        • Customizing Your Vector Store
        • Image Similarity Search
        • Improving Search Accuracy using Deep Memory
      • LangChain Integration
      • LlamaIndex Integration
      • Managed Tensor Database
        • REST API
        • Migrating Datasets to the Tensor Database
      • Deep Memory
        • How it Works
    • Tensor Query Language (TQL)
      • TQL Syntax
      • Index for ANN Search
        • Caching and Optimization
      • Sampling Datasets
  • 🔬Technical Details
    • Best Practices
      • Creating Datasets at Scale
      • Training Models at Scale
      • Storage Synchronization and "with" Context
      • Restoring Corrupted Datasets
      • Concurrent Writes
        • Concurrency Using Zookeeper Locks
    • Deep Lake Data Format
      • Tensor Relationships
      • Version Control and Querying
    • Dataset Visualization
      • Visualizer Integration
    • Shuffling in Dataloaders
    • How to Contribute
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  • Setting up Federated Credentials in Microsoft Azure
  • Step 1: Register Application Credentials with the Microsoft Identity Platform
  • Step 2a: Apply the Application Credentials to your Azure storage account
  • Step 2b: Apply the Application Credentials to a specific Azure container in your Azure storage account
  • IMPORTANT TO PERFORM STEPS BELOW TO COMPLETE 2b - PLEASE DO NOT SKIP

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  1. SETUP
  2. Storage and Credentials
  3. Setting up Deep Lake in Your Cloud
  4. Microsoft Azure

Provisioning Federated Credentials

How to setup Federated Credentials in Azure

PreviousConfigure Azure SSO on ActiveloopNextEnabling CORS

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Setting up Federated Credentials in Microsoft Azure

The most secure method for connecting data from your Azure storage to Deep Lake is using Federated Credentials, which are set up using the steps below:

Step 1: Register Application Credentials with the Microsoft Identity Platform

1. Login to the Azure account where the App will be registered and where the data is stored.

2. Go to the App Registrations page in the Azure UI, which can be done by searching "App registrations" in the console.

3. Click on Register an application or New registration.

4. Enter the Name and Supported account type (Personal Microsoft Accounts are not supported) and click Register

5. In the application console, click Certificates & secrets.

6. Click on Federated credentials and Add credential.

7. Click on Select scenario and select Other issuer.

8. Enter the following information in the form, and click Add.

  • Issuer: https://cognito-identity.amazonaws.com

    • This is for trusting Activeloop's Cognito issuer. There's no need to create AWS Cognito by the user.

  • Subject identifier: us-east-1:7bc30eb1-bac6-494b-bf53-5747849d45aa

  • Name: enter a name with your choice

  • Description (optional): enter description a with your choice

  • Audience: us-east-1:57e5de2f-e2ec-4514-b9b0-f3bb8c4283c3

Step 2a: Apply the Application Credentials to your Azure storage account

Skip to 2b if you want to assign Application Credentials to a specific Azure container

1. Go to the Storage accounts page in the Azure UI, which can be done by searching "Storage accounts" in the console.

2. Select the Storage account to which you want to add Application Credentials.

4. Select Access Control (IAM) and click Add, and select Add role assignment.

5. Search and select Storage Blob Data Contributor under the role names and click Next.

6. Click on the Select members link, and in the tab that opens up on the right, search by name and select the application you created in Step 1. Click Select at the bottom of the page.

7. The application should appear in the list of Members, at which point you can click Review + assign.

Step 2b: Apply the Application Credentials to a specific Azure container in your Azure storage account

1. Go to the Storage accounts page in the Azure UI, which can be done by searching "Storage accounts" in the console.

2. Select the Storage account to which you want to add Application Credentials.

  1. Select the Container to which you add the Application Credentials.

4. Select Access Control (IAM) and click Add, and select Add role assignment.

IMPORTANT TO PERFORM STEPS BELOW TO COMPLETE 2b - PLEASE DO NOT SKIP

5. Perform substeps 5-7 from Step 2a above, in order to add the Application Credentials to the Container

6. Execute the steps in Step 2a above on your Storage Account, except set the Storage Account Role Assignment to Storage Blob Delegator in substep 5.

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