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v3.9.16
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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On this page
  • Configure Azure SSO on Activeloop
  • 1. Creating Application
  • 2. Granting Permissions
  • 3. Domain Name Validation in our side

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

Configure Azure SSO on Activeloop

Enabling Azure SSO on Activeloop

PreviousMicrosoft AzureNextProvisioning Federated Credentials

Last updated 6 months ago

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Configure Azure SSO on Activeloop

1. Creating Application

  • Go to App registration page in

  • Click on add New Registration

  1. Put name for the application

  2. For application type, select Default Directory only - Single tenant

  3. For Redirect URI select the type Web

  4. For Callback URL put https://auth.activeloop.ai/login/callback

  5. Click on Register

Once it is created go to Overview page, copy and send us the Application (client) ID and the Directory (tenant) ID

Client secret creation

Go to Certificates & Secrets → Client secrets →New client secret

Name the secret, select preferred expiration and click Add

NOTE: The secret need to be updated before it get expired

Send us the secret value

2. Granting Permissions

  1. Go to API permissions → Microsoft Graph → Delegated Permissions and select following permissions:

    1. email

    2. openid

    3. profile

  1. In the search bar search Directory.Read.All and select the permission as well

Click on Add permissions

3. Domain Name Validation in our side

We also will be needing domain of the azure tenant to authorize the SSO clients

  1. Copy the domain name that will be used for SSO and send us

Go to in Azure portal

🏗️
🌐Domain Names
🌐Azure portal