# Quickstart

- Canonical URL: https://docs.fairvisor.com/docs/quickstart/
- Section: docs
- Last updated: n/a
> Get Fairvisor Edge running in 5 minutes with Docker.


This guide gets a local Fairvisor Edge instance running in Docker with a simple policy.

## Prerequisites

- Docker 24+ (or Docker Desktop)
- `curl` for testing

## Step 1 - Create policy

```bash
mkdir fairvisor-demo && cd fairvisor-demo
```

Create `policy.json`:

```json
{
  "bundle_version": 1,
  "issued_at": "2026-01-01T00:00:00Z",
  "policies": [
    {
      "id": "demo-rate-limit",
      "spec": {
        "selector": {
          "pathPrefix": "/",
          "methods": ["GET", "POST"]
        },
        "mode": "enforce",
        "rules": [
          {
            "name": "global-rps",
            "limit_keys": ["ip:address"],
            "algorithm": "token_bucket",
            "algorithm_config": {
              "tokens_per_second": 5,
              "burst": 10
            }
          }
        ]
      }
    }
  ],
  "kill_switches": []
}
```

This policy allows every IP address **5 requests per second** with a burst of up to 10. Requests over the limit receive a `429` response. It applies to all paths and both GET and POST methods.

## Step 2 - Run container

```bash
docker run -d \
  --name fairvisor \
  -p 8080:8080 \
  -v "$(pwd)/policy.json:/etc/fairvisor/policy.json:ro" \
  -e FAIRVISOR_CONFIG_FILE=/etc/fairvisor/policy.json \
  -e FAIRVISOR_MODE=decision_service \
  ghcr.io/fairvisor/fairvisor-edge:v0.1.0
```

## Step 3 - Verify

```bash
curl -sf http://localhost:8080/readyz
curl -s -w "\nHTTP %{http_code}\n" \
  -H "X-Original-Method: GET" \
  -H "X-Original-URI: /api/data" \
  -H "X-Forwarded-For: 10.0.0.1" \
  http://localhost:8080/v1/decision
```

Expected output for `/readyz`: `{"status":"ok"}`

A 200 response means the decision service is ready and a policy bundle is loaded.

## Alternative: LLM token budget policy

Replace the `policy.json` content with an LLM-focused policy:

```json
{
  "bundle_version": 1,
  "issued_at": "2026-01-01T00:00:00Z",
  "policies": [
    {
      "id": "llm-budget",
      "spec": {
        "selector": { "pathPrefix": "/v1/chat" },
        "mode": "enforce",
        "rules": [
          {
            "name": "per-org-tpm",
            "limit_keys": ["jwt:org_id"],
            "algorithm": "token_bucket_llm",
            "algorithm_config": {
              "tokens_per_minute": 60000,
              "tokens_per_day": 1200000,
              "default_max_completion": 800
            }
          }
        ]
      }
    }
  ],
  "kill_switches": []
}
```

This policy limits each organization (identified by the `org_id` claim in the JWT) to **60 000 LLM tokens per minute** and **1 200 000 per day**. Individual completions are capped at 800 tokens. Requests that would exceed the budget receive a `429` response with an OpenAI-compatible error body (`error.type: "rate_limit_error"`), so existing clients handle it without any changes.

## Next steps

- [SaaS connection](/docs/deployment/saas/)
- [Helm deployment](/docs/deployment/helm/)
- [CLI usage](/docs/cli/overview/)