> ## Documentation Index
> Fetch the complete documentation index at: https://docs.visual-layer.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Self-Hosting System Requirements

> Hardware, software, and GPU requirements for installing Visual Layer on-premises with dependencies and permissions.

### System Configuration

The following hardware specifications are required for Visual Layer on-premises deployment:

| Requirement          | Specification                                                                                  |
| -------------------- | ---------------------------------------------------------------------------------------------- |
| **Operating System** | Ubuntu LTS 20/22/24                                                                            |
| **Architecture**     | X86                                                                                            |
| **RAM**              | 64GB                                                                                           |
| **Disk Space**       | 256GB + 2.5× estimated data size                                                               |
| **CPU**              | 16 cores                                                                                       |
| **GPU** (Optional)   | Common Nvidia GPU types with at least 24GB GPU memory (Nvidia A10, A100, H100, RTX 4090, etc.) |

### Dependencies

Install these software dependencies before setting up Visual Layer:

* Docker v.27 or above - follow [the official instructions](https://docs.docker.com/engine/install/ubuntu/) and [the post-install guide](https://docs.docker.com/engine/install/linux-postinstall/)
* jq - json data parsing library
* psql - postgres command line client
* zip/unzip

### NVIDIA GPU Setup (GPU machines only)

If you are using a GPU machine for acceleration, you need to install the NVIDIA Container Toolkit:

1. Add NVIDIA package repositories:

   ```bash theme={"theme":"monokai"}
   curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
   curl -fsSL https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
     | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#' \
     | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
   ```
2. Download the nvidia-container-toolkit:

   ```bash theme={"theme":"monokai"}
   sudo apt-get update
   sudo apt-get install -y nvidia-container-toolkit
   ```
3. Configure Docker to use the NVIDIA runtime:

   ```bash theme={"theme":"monokai"}
   sudo nvidia-ctk runtime configure --runtime=docker
   sudo systemctl restart docker
   ```
4. Verify the installation:

   ```bash theme={"theme":"monokai"}
   docker run --rm --runtime=nvidia --gpus all nvidia/cuda:11.5-base-ubuntu20.04 nvidia-smi
   ```

   This should display your GPU information if the toolkit is properly installed.

### Advised Tools for Troubleshooting/Maintenance

These tools are recommended for system maintenance and troubleshooting:

* vi - or equivalent required for file editing
* object store CLIs if applicable (aws cli, mc)

### Required Permissions and Access

Ensure proper user permissions for installation:

* Make sure you run the installation as a regular user (not a root user), with sudo privileges