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

# Server deployment

> Operational guidance for running the Tandemn server.

The Tandemn server should be treated as shared infrastructure. It receives job requests from users and coordinates execution across accelerated resources.

## Deployment checklist

<Steps>
  <Step title="Choose a server host">
    Pick a machine in your AWS environment that CLI users and EC2 inference replicas can reach.
  </Step>

  <Step title="Prepare AWS access">
    Configure AWS credentials, IAM permissions, S3 bucket access, and quota visibility.
  </Step>

  <Step title="Clone the server repository">
    Fetch the Tandemn server repository and submodules.
  </Step>

  <Step title="Run setup">
    Install dependencies, verify AWS and Redis connectivity, and create `.env`.
  </Step>

  <Step title="Start Redis">
    Run Redis for chunked multi-replica jobs.
  </Step>

  <Step title="Start the control plane">
    Run `python server.py --url <public-or-private-url>`.
  </Step>

  <Step title="Verify from a client">
    Run `tandemn check` from a separate machine using the public server URL.
  </Step>
</Steps>

## Commands

```bash theme={null}
git clone --recurse-submodules https://github.com/Tandemn-Labs/Tandemn-server.git
cd Tandemn-server
bash setup.sh
docker run -d -p 6379:6379 redis
python server.py --url https://your-public-url.example.com
```

## Manual installation

Use this path when you do not want to run `setup.sh`.

```bash theme={null}
uv venv .venv --python 3.12 --seed
source .venv/bin/activate
uv pip install -r requirements.txt
sky check
```

Create a `.env` file in the project root:

```bash theme={null}
S3_UPLOAD_BUCKET=your-s3-bucket
HF_TOKEN=hf_your_token_here
TD_API_KEY=your-secret-key
ANTHROPIC_API_KEY=sk-ant-...
KOI_SERVICE_URL=http://localhost:8090
```

`KOI_SERVICE_URL` is optional. Leave it unset for standalone Orca behavior.

## Operating model

The administrator owns the server deployment, AWS credentials, S3 bucket, Redis, environment configuration, network exposure, and cluster access. Users own their prompt files, model choices, SLOs, and CLI environment.

> Document the server URL, supported models, and expected SLO values for your users before sharing access.

## Network model

For local development, the control plane can be exposed through a tunnel or VPN. For production, deploy the control plane on a small EC2 instance in the same VPC as the inference replicas to avoid public exposure and tunnel latency.

## Updates

When a new Tandemn server version is available, review the release notes, back up deployment-specific configuration, and update in a controlled maintenance window.