The data hub testbed can be used to evaluate the compliance of an S3-compatible object storage with regard to the requirements for up and downloading files.

It provides key metrics such as elapsed duration and average file part processing time. These metrics are logged and displayed in the terminal. An important note is that the terms "upload" and "download" refer to "Encryption and Upload" and "Download and Decryption", respectively. Additionally, the script does not perform any kind of file cleanup or removal upon completion. Please keep this in mind when running the script consecutively.

Before running this test, your data hub should fulfill the following requirements:

• An S3-compatible Object Storage is running and available via network.
• A DevOps engineer who is familiar with the S3 API and basic unix administration is available to assist with the execution of this test bed.
• An empty bucket has been created that can be used for this test.
• S3 credentials are available to access this bucket with read and write permissions.
• A UNIX machine with access to the Object Storage API is available with Python 3.9 and pip installed.

• Please first make sure that your configuration file is correct.
• Check that your S3 Object Storage is accessible and your credentials are valid for depositing files to the corresponding bucket. To do so, we recommend using a tool such as WinSCP or FileZilla.
• Check that the machine running the script can reach the S3 API by running e.g.: curl <path to the s3 api>
• Consult your local administrator of the S3 API.
• If you have ruled out the possibility that the failure happens due to your local setup, please open an issue in this repository.

1. Git clone this repository and navigate with the terminal into the repository.
2. Create a python virtual environment and activate it (for instruction see here).
3. Install dependencies using pip: pip install -r ./requirements.txt
4. Validate that the script is ready: ./src/s3_upload_test.py

Configuration parameters for this script are provided using a YAML file (e.g., config.yaml). This file should include the following fields:

• s3_endpoint_url: The endpoint to be used for S3 API calls within the script.
• s3_access_key_id: The globally unique IAM user ID for the S3 instance.
• s3_secret_access_key: The secret access key associated with the above access key ID.
• bucket_id: The ID of the S3 bucket. Please note, this ID cannot contain underscores.
• part_size: The default file part size in MiB for multipart file transfer.

Here's a sample configuration that can be adapted for your needs:

s3_endpoint_url: http://localstack:4566
s3_access_key_id: test_access_key
s3_secret_access_key: test_secret_key
bucket_id: test-bucket
part_size: 16

Once you have prepared the configuration file, you can run the script using the following command:

./src/s3_upload_test.py --input-path="path/to/file" --config-path="path/to/config_file" -v

Required:

• --input-path: Specifies the path to the file you want to upload.
• --config-path: Specifies the path to the file containing the required S3 configuration values.

Optional:

• --verbose, -v: Enables verbose mode, which displays logs for individual file parts.
• By default, these logs are hidden.

For example, if the file to be uploaded is located at /home/files/data.txt and the config file is located at /home/files/config.yaml, the command to run the script would be:

The exact command to run the script would be:

./src/s3_upload_test.py --input-path="/home/files/data.txt" --config-path="/home/files/config.yaml"

Add -v or --verbose at the end of the command if you wish to view logs for individual file parts:

./src/s3_upload_test.py --input-path="/home/files/data.txt" --config-path="/home/files/config.yaml" -v