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CHEESE Installation

This part is about creating an AWS instance for running CHEESE.

How to create an EC2 instance for inference?

  1. Go to your AWS account and launch a new instance.
  2. Choose an AWS instance that has a minimum equivalent resources to the following
  3. Amazon Machine Image (AMI) : Select the following deep learning AMI if your account allows it Deep Learning OSS Nvidia Driver AMI GPU PyTorch 2.3 (Ubuntu 20.04).

Please note that the deep learning AMI have pre-installed CUDA drivers. In case the above AMI is not available on your AWS account you can select the following one : Ubuntu Server 22.04 LTS (HVM), SSD Volume Type

  • Instance Type : g4dn.xlarge or similar → 4vCPUs, 16 GB RAM, 1 GPU with 16 GB of GPU RAM

  • Storage : 64 GB minimum, gp2

  • Networking (Optional) : Choose a VPC and a Subnet for a private VPN.

  • Security : Create a key pair for login into the instance or choose a pre-existing one.

  • Download the private key and save it somewhere securely and test the connectivity using SSH using the following steps from AWS :

In case you have problems with SSH, test the connectivity to your instance by choosing the instance in the "Instances" dashboard and clicking connect, choose "connect with EC2 Instance Connect", then you'll have a shell in AWS GUI to test the instance. There you can also reset the ubuntu user password.

For more information please refer to the AWS Documentation.

How to install CHEESE?

  1. Clone the cheese-on-prem-assets repository to your instance.

git clone

  1. Go to the repository folder. cd cheese-on-prem-assets

  2. In case you are working with the following AMI : Ubuntu Server 22.04 LTS (HVM), SSD Volume Type , you need to install Docker and CUDA drivers. You can use the following steps

    • Go to the install folder by running cd install
    • To install Docker run : bash
    • To install CUDA Drivers run : bash
    • Reboot the machine : sudo reboot
  3. Copy the template environment configuration file in config/cheese-env.conf.template which defines global environment variables, and modify it accordingly.

    • CHEESE_CUSTOMER : The customer name
    • CHEESE_PASSWORD : The password used to pull Docker images for running CHEESE
    • LICENSE_FILE : The CHEESE license file
    • CONFIG_FILE : A YAML configuration file for running the CHEESE tool on-premises which contains paths to the data, models… A template can be found in config/cheese_config_file.yaml.template
    • IP : The IP address of the instance (e.g
    • DB_PORT : The port on which to expose the CHEESE database server
    • API_PORT : The port on which to expose the CHEESE API
    • UI_PORT : The port on which to expose the CHEESE UI
  4. Run bash --env_config <env_config_file> inside the install folder. Where <env_config_file> is the path to your environment configuration file.

  5. Check if the installation works by running cheese