Create an AWS EC2 GPU Spot Instance to Run Stable Diffusion WebUI as well as ControlNet and DreamBooth extensions on Ubuntu 22.04 LTS using Terraform

Overview

Install the Stable Diffusion WebUI by AUTOMATIC1111, ControlNet, and Dreambooth extensions on Ubuntu 22.04 LTS Linux using an AWS EC2 GPU spot instance for the fraction of the cost of an on-demand instance.

A Python script is provided to assist you with determining your bid prince for the spot EC2 instance, and Terraform code is provided to assist you with provisioning the EC2 instance in AWS.

It is recommended to use a GPU instance that has at least 16GB of GPU VRAM to run the standard Stable Diffusion Web UI. You will need at least 32GB of system memory and at least 20GB of GPU VRAM if you intend on doing training.

The g4dn instance types with 16G of GPU VRAM are available in many regions, but unfortunately the g5 instance types with 24GB of GPU VRAM and high performant local NVMe SSD storage are only available within the following regions:

Region	Name
us-east-1	North Virginia
us-west-2	Oregon
ca-central-1	Canada
eu-central-1	Frankfurt
eu-west-1	Ireland
eu-west-2	London
eu-north-1	Stockholm

Clone the repo

git clone https://github.com/ashleykleynhans/stable-diffusion-terraform.git
cd  stable-diffusion-terraform

Calculate the spot price for the EC2 GPU instance

Create the Python virtual environment

cd scripts
python3 -m venv venv
source venv/bin/activate
python3 -m pip install --upgrade pip
pip3 install -r requirements.txt

Configure your AWS credentials for the script

Edit the config.yml file and replace YOUR_ACCESS_KEY_ID and YOUR_SECRET_ACCESS_KEY with your actual AWS credentials.

Run the script to calculate the spot price

python3 get_spot_price.py -r eu-west-1 -i g4dn.xlarge

Where eu-west-1 is the region, and g4dn.xlarge is the EC2 instance type.

This will return the spot price, for example 0.24192.

Create your Stable Diffusion EC2 instance

Ensure you are in the Terraform directory

pwd

If you are in the scripts directory:

cd ../terraform

If you are in the root of the project:

cd terraform

Install Terraform

brew install terraform

Initialise Terraform

terraform init

Update the Terraform configuration

Get your IP address:

curl https://icanhazip.com

Then edit terraform/vars.tf, and update the following variables:

• AWS_REGION
• AWS_KEY_PAIR
• EC2_INSTANCE_TYPE
• EC2_INSTANCE_SPOT_PRICE
• EC2_INSTANCE_DISK_SIZE
• VPC_ID
• SUBNET_ID
• MY_IP_ADDRESS

The default disk size is 100GB, but if you plan on experimenting with multiple models and doing training, I recommend increasing it to around 300GB, depending on your requirements.

Create a terraform.tfvars file containing your AWS credentials

Create a terraform.tf file with the following content:

AWS_ACCESS_KEY = "INSERT_YOUR_ACCESS_KEY"
AWS_SECRET_KEY = "INSERT_YOUR_SECRET_KEY"

Check what AWS resources are going to be created

terraform plan

Create the AWS resources

terraform apply

This will create your EC2 instance, and will output the private IP and the public IP.

Take note of the public IP and use it to SSH to the server using the username ubuntu and the private key that you have specified in vars.tf.

NOTE: It takes approximately 20-25 minutes to install all the dependencies, and then the server will be rebooted so that the Nvidia GPU driver can be activated. Once all the dependencies are installed, and the server is rebooted, you can proceed with running Stable Diffusion.

Run Stable Diffusion

Once the AWS resources are created by Terraform, cloud-init will take quite some time to install all the necessary dependencies (scripts/setup.sh), and will reboot the instance in order for the CUDA driver to take effect once its installed.

You can check the progress by establishing an SSH connection to the server and running the following command:

tail -f /var/log/cloud-init-output.log

You should see something like this once everything is installed:

Cloud-init v. 23.1.2-0ubuntu0~22.04.1 finished at Fri, 12 May 2023 14:54:27 +0000. Datasource DataSourceEc2Local.  Up 10.65 seconds

Once the server is ready, you can start Stable Diffusion as follows:

cd /home/ubuntu/stable-diffusion-webui
./webui.sh -f

Access Stable Diffusion WebUI

Once the Stable Diffusion WebUI is running, you can access it in your web browser on your IP (that you provided in vars.tf) on port 7860, for example:

http://127.0.0.1:7860

Obviously replace 127.0.0.1 with the IP that was returned when you ran the curl command to https://icanhazip above.

Destroy the Stable Diffusion AWS resources

Once you are done using Stable Diffusion, training your model, etc, you should destroy the AWS resources so that you are not charged for them.

If you trained any models, be sure to copy them off the server before destroying the resources, otherwise they will be lost forever.

terraform destroy

Troubleshooting

GPU OOM issues

See the the Dreambooth extension wiki.

Community and Contributing

Pull requests and issues on GitHub are welcome. Bug fixes and new features are encouraged.

Appreciate my work?