Remote Storage
In Enterprise Edition you can not only store files on a hard drive, but also connect Azure Blob Storage, Google Cloud or any S3 compatible storage (i.e. AWS S3).
You can upload files from your PC to connected cloud storage or use already uploaded files from cloud storage as a source (without duplicating it).

How we store files

Supervisely uses DATA_PATH from .env (defaults to /supervisely/data) to keep caches, database and etc. But we are interested in storage subfolder generated content, like uploaded images or neural networks are stored.
You can find two subfolders here:
  • <something>-public/
  • <something>-private/
That's because we maintain the same structure in local storage as if you would use a remote storage. In that case those two folders are buckets or containers. You may notice that one has "public" in it's name, but it only reflects the kind of data we store in it. Both buckets are private and does not provide anonymous read.

Configure Supervisely to use S3 compatible storage (Amazon S3, Minio)

Edit .env configuration file - you can find it by running supervisely where command.
Change STORAGE_PROVIDER from http (local hard drive) to minio (S3 storage backend).
Also, you need to provide STORAGE_ACCESS_KEY and STORAGE_SECRET_KEY credentials along with endpoint of your S3 storage.
For example, here are settings for Amazon S3:
  • STORAGE_ENDPOINT=s3.amazonaws.com
  • STORAGE_PORT=443
So in the end, here is how your .env settings could look like:
JUPYTER_DOWNLOAD_FILES_BEFORE_START=true
STORAGE_JUPYTER_SYNC=true
STORAGE_PROVIDER=minio
STORAGE_ENDPOINT=s3.amazonaws.com
STORAGE_PORT=443
STORAGE_ACCESS_KEY=<hidden>
STORAGE_SECRET_KEY=<hidden>
Execute sudo supervisely up -d to apply the new settings

Configure Supervisely to use Azure Blob Storage

Edit .env configuration file - you can find it by running supervisely where command.
Change STORAGE_PROVIDER from http (local hard drive) to azure (Azure storage backend).
Also, you need to provide STORAGE_ACCESS_KEY (your storage account name) and STORAGE_SECRET_KEY (secret key) credentials along with endpoint of your blob storage.
Here is how your .env settings could look like:
JUPYTER_DOWNLOAD_FILES_BEFORE_START=true
STORAGE_JUPYTER_SYNC=true
STORAGE_ACCESS_KEY=<account name>
STORAGE_ENDPOINT=https://<account name>.blob.core.windows.net
STORAGE_PROVIDER=azure
STORAGE_SECRET_KEY=<secret key 88 chars long or so: aflmg+wg23fWA+6gAafWmgF4a>
Execute sudo supervisely up -d to apply the new settings

Configure Supervisely to use Google Cloud Storage

Edit .env configuration file - you can find it by running supervisely where command.
Change STORAGE_PROVIDER from http (local hard drive) to google (GCS backend).
Also, you need to provide STORAGE_CREDENTIALS_PATH credentials file generated by Google.
Here is how your .env settings could look like:
JUPYTER_DOWNLOAD_FILES_BEFORE_START=true
STORAGE_JUPYTER_SYNC=true
STORAGE_PROVIDER=google
STORAGE_ENDPOINT=storage.googleapis.com
STORAGE_CREDENTIALS_PATH=/gcs.json
Now create docker-compose.override.yml under cd $(sudo supervisely where):
services:
http-storage:
volumes:
- <path to the secret file>:/gcs.json:ro
Execute sudo supervisely up -d to apply the new settings

Migration from local storage

Now, copy your current storage to an S3. As we mentioned before, because we maintain the same structure in local filesystem, copying will be enough.
We suggest to use minio/mc to copy the files.
Run minio/mc docker image and execute the following commands:
mc config host add s3 https://s3.amazonaws.com <YOUR-ACCESS-KEY> <YOUR-SECRET-KEY>
mc cp <DATA_STORAGE_FROM_HOST>/<your-buckets-prefix>-public s3/<your-buckets-prefix>-public/
mc cp <DATA_STORAGE_FROM_HOST>/<your-buckets-prefix>-private s3/<your-buckets-prefix>-private/
Finally, restart services to apply new configuration: supervisely up -d.

Keys from IAM Role

If you want to use IAM Role you must specify STORAGE_IAM_ROLE=<role_name> in .env file then STORAGE_ACCESS_KEY and STORAGE_SECRET_KEY variables can be ommited.
IAM Roles are only supported for AWS S3.

Frontend caching

Since AWS and Azure can be quite price in case of heavy reads, we enable image caching by default.
If the image is not in the preview cache but in the STORAGE cache it will be generated and put into previews cache, but it will not be fetched from the remote server.
Here are the default values (you can alter them via docker-compose.override.yml file):
services:
proxy:
environment:
CACHE_PREVIEWS_SIZE: 1g
CACHE_PREVIEWS_EXPIRES: 12h
CACHE_STORAGE_SIZE: 10g
CACHE_STORAGE_EXPIRES: 7d
CACHE_IMAGE_CONVERTER_SIZE: 10g
CACHE_IMAGE_CONVERTER_EXPIRES: 7d
If you already have some files on Amazon S3/Google Cloud Storage/Azure Storage and you don't want to upload and store those files in Supervisely, you can use the "Links" plugin to link the files to Supervisely server.
Instead of uploading actual files (i.e. images), you will need to upload .txt file(s) that contains a list of URLs to your files. If your URLs are publicly available (i.e. link looks like https://s3-us-west-2.amazonaws.com/test1/abc and you can open it in your web browser directly), then you can stop reading and start uploading.
If your files are protected, however, you will need to provide credentials in the instance settings or manually create configuration file.

File system provider

If you want to use images from your host where supervisely instance running, you can use "File system" provider
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  • Folder path on the server - path to folder on the host server that will be mounted
  • Storage ID (bucket) - mouted folder identifyer. It will be used in links to mounted folder
For instance, for the example above, when you want to add a new assets (image or video) with local path on your hard drive /data/datasets/persons/image1.jpg, use the following format in API, SDK or corresponding application: fs://local-datasets/persons/image1.jpg

Manual configuration

If you are brave enough, you can create configuration files manually:
Example configuration file:
# amazon s3 example
my-car-datasets:
provider: minio
endpoint: s3.amazonaws.com
access_key: <your access key>
secret_key: <your secret key>
# iam_role: <or just use your iam role>
region: eu-central-1
# array of buckets
buckets:
- cars_2020_20_10
- cars_2020_10_10
โ€‹
# azure storage example
my-boats-datasets:
provider: azure
endpoint: https://<account name>.blob.core.windows.net
access_key: <account name>
secret_key: <secret key 88 chars long or so: aflmg+wg23fWA+6gAafWmgF4a>
# array of buckets
buckets:
- boats_bucket_2020_20_10
- another_boats_bucket_2020_10_10
โ€‹
# google cloud storage example
my-planes-datasets:
provider: google
endpoint: storage.googleapis.com
credentials_path: <path to the secret file inside the container>
# array of buckets
buckets:
- planes_bucket_2020_20_10
- another_planes_bucket_2020_10_10
Links file structure:
<provider name>://<bucket name>/<object name>
Links file example:
s3://cars_2020_20_10/truck.jpg
azure://boats_bucket_2020_20_10/supersonicboat.jpg
google://another_planes_bucket_2020_10_10/boeing.jpg
Create a new file docker-compose.override.yml under cd $(sudo supervisely where):
services:
http-storage:
volumes:
- <path to the configuration file>:/remote_links.yml:ro
Then execute the following to apply the changes:
sudo supervisely up -d http-storage
Google Cloud Storage secret file example, docker-compose.override.yml:
services:
http-storage:
volumes:
- <path to the secret file>:/secret_planes.json:ro