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Self-Hosted ONE AI Worker

Unlock Required

Self-hosted training must be enabled for your account before use. Contact us at support@one-ware.com or book a demo to get access.

self-hosted worker run

What is the Self-Hosted ONE AI Worker?​

Run ONE AI jobs on your own machine or server instead of on ONE WARE Cloud workers.

The self-hosted worker handles training, testing, visualization, and export locally. This way you can train on your own hardware while keeping your dataset private.

What stays local​

  • Datasets
  • Training artifacts
  • Test results
  • Exported models

What is sent to ONE WARE Cloud​

  • Job metadata and status
  • Logs for live monitoring
  • Configuration required to create and track jobs
  • Metadata needed for model architecture prediction
info

The worker must be able to reach https://cloud.one-ware.com while a job is running. If it cannot report status for about 5 minutes, the job is cancelled.

Requirements​

  • Docker or Podman
  • An NVIDIA GPU for the recommended setup
  • NVIDIA Container Toolkit configured for your container runtime
  • Network access to https://cloud.one-ware.com
  • Persistent storage if job data should survive restarts

The container already includes the required CUDA libraries. On the host, you only need a working NVIDIA driver and NVIDIA container runtime support.

Supported NVIDIA GPUs​

CUDA architectures 3.5, 5.0, 6.0, 7.0, 7.5, 8.0, and newer are supported.

In practice, this includes most modern NVIDIA GPUs, for example:

  • GeForce RTX 20, 30, 40, and 50 series
  • NVIDIA T4
  • NVIDIA A2, A10, A30, and A100
  • NVIDIA L4, L40, L40S
  • NVIDIA H100 and H200

If you are unsure, check your GPU's compute capability in NVIDIA's CUDA GPU list.

Setup​

warning

Make sure NVIDIA Container Toolkit is installed and your container runtime is configured to support NVIDIA GPUs.

Podman
Docker

Pull the image:

docker pull registry.one-ware.com/oneware-worker-selfhost:latest

First Start​

Use this when you want to run the worker in the foreground and watch the logs directly:

docker run \
  --name oneware-worker-selfhost \
  --gpus all \
  -p 5000:5000 \
  -v oneware-selfhost-data:/app/selfhost_projects \
  registry.one-ware.com/oneware-worker-selfhost:latest

If everything is working correctly, the worker will detect the GPU and print it in the logs. alt text

Docker Compose​

It is recommended to use Docker Compose to keep the configuration in one place.

services:
  oneware-worker-selfhost:
    image: registry.one-ware.com/oneware-worker-selfhost:latest
    container_name: oneware-worker-selfhost
    restart: unless-stopped
    ports:
      - "5000:5000"
    volumes:
      - oneware-selfhost-data:/app/selfhost_projects
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]

volumes:
  oneware-selfhost-data:

In this configuration, the worker API is exposed on port 5000.

Configuration​

  • Persistent job data: /app/selfhost_projects
  • Temporary workspace: /app/selfhost_workspace

Mount /app/selfhost_projects as a volume if uploads, models, exports, and test results should survive container restarts. The workspace directory is cleaned up automatically after jobs finish.

Runtime behavior​

On startup, the worker checks whether an NVIDIA GPU is available.

If a GPU is found, the default limits are:

  • GPU_DEVICE=0
  • GPU_VRAM_PERCENTAGE=0.9
  • ONEAI_RAM_PERCENTAGE=0.5

If no GPU is available, the worker runs in CPU mode.

The worker processes one job at a time. Additional jobs wait in a queue.

Environment variables​

These variables can be used to control which resources the worker uses. You can also enforce resource limits with Docker itself.

  • GPU_DEVICE: GPU index to use
  • GPU_VRAM_PERCENTAGE: maximum VRAM usage
  • ONEAI_RAM_PERCENTAGE: maximum system RAM usage

Security​

Do not expose the worker directly to the public internet unless you add your own protection. Run it on a trusted network and restrict access to port 5000 with firewall rules or a reverse proxy.

Configure the ONE AI Extension​

Set the self-hosted worker address to:

http://<host>:5000

Replace <host> with the machine name or IP address that the extension can reach.

setting oneai

The cloud page will now show indications that self-hosted mode is active and which jobs are running in that mode.

Self hosted job