Cloud Storage

LightlyStudio Enterprise lets admins configure cloud storage credentials centrally. Once set up, every Python client that calls ls.connect() receives the credentials automatically, no per-user setup is needed. Cloud storage is read-only, LightlyStudio will not write any data to your buckets or need write permissions.

Currently supported: AWS S3, Google Cloud Storage (GCS), and Azure Blob Storage.

How It Works

1. Admin creates cloud provider credentials with read access to the storage bucket. See the provider-specific setup guides below for step-by-step instructions.
2. Admin saves the credentials in the LightlyStudio Enterprise GUI.
3. Python clients call ls.connect() and receive the credentials automatically.

Step 1: Get Your Cloud Credentials

Follow the guide for your cloud provider to create credentials with the required permissions:

• AWS S3
• Google Cloud Storage
• Azure Blob Storage

Step 2: Add Credentials in the GUI

1. Open your LightlyStudio Enterprise instance in the browser.
2. Go to the Datasets page and click the Cloud Storage Credentials button. This button is only visible to admins.
3. Select your provider.
4. Enter the credentials requested for the selected provider. For Azure Blob Storage, enter the storage account name and a read-only container SAS token.
5. Click Save Credentials.

The credentials are now stored on the server and shared with all Python client connections. Saving replacement credentials also refreshes the active server configuration. Existing Python clients should call ls.connect() again to receive rotated credentials.

Step 3: Use Cloud Storage from Python

If you have not set up Python access yet, start with Connect from Python. After calling ls.connect(), cloud credentials are injected into your local environment automatically, so you can use remote paths directly without any extra client-side setup.

enterprise_cloud_storage.py

import lightly_studio as ls

ls.connect()

dataset = ls.ImageDataset.load_or_create(name="s3_dataset")
dataset.add_images_from_path(path="s3://my-bucket/images/")

For Google Cloud Storage, use a gcs:// path:

enterprise_gcs_storage.py

import lightly_studio as ls

ls.connect()

dataset = ls.ImageDataset.load_or_create(name="gcs_dataset")
dataset.add_images_from_path(path="gcs://my-bucket/images/")

For Azure Blob Storage, use an abfs:// path:

enterprise_azure_storage.py

import lightly_studio as ls

ls.connect()

dataset = ls.ImageDataset.load_or_create(name="azure_dataset")
dataset.add_images_from_path(path="abfs://my-container/images/")

Note

The Python client must have the cloud storage dependencies installed:

pip install "lightly-studio[cloud-storage]"

See Using Cloud Storage for more details on supported cloud operations.

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