TL;DR – Click the button below, add your AI API key (Anthropic, OpenAI, or Google), and your personal Bytebot instance will be live in ~2 minutes.
Why Railway?
Railway provides a zero-ops PaaS experience with private networking and per-service logs that perfectly fits Bytebot’s multi-container architecture. The official template wires every service together using the latest container images pushed to theedge branch.
What Gets Deployed
| Service | Container Image (edge) | Port | Exposed? | Purpose |
|---|---|---|---|---|
| bytebot-ui | ghcr.io/bytebot-ai/bytebot-ui:edge | 9992 | Yes | Next.js web UI rendered to the world |
| bytebot-agent | ghcr.io/bytebot-ai/bytebot-agent:edge | 9991 | No | Task orchestration & LLM calls |
| bytebot-desktop | ghcr.io/bytebot-ai/bytebot-desktop:edge | 9990 | No | Containerised Ubuntu + XFCE desktop |
| postgres | postgres:14-alpine | 5432 | No | Persistence layer |
bytebot-ui is assigned a public domain.
Step-by-Step Walk-through
1
1. Open the Template
Click the Deploy on Railway button above or visit https://railway.com/deploy/bytebot?referralCode=L9lKXQ.
2
2. Configure Environment
For the bytebot-agent resource, add your AI API key (choose at least one):
- Anthropic: Paste into
ANTHROPIC_API_KEYfor Claude models - OpenAI: Paste into
OPENAI_API_KEYfor GPT models - Google: Paste into
GEMINI_API_KEYfor Gemini models
3
3. Kick off the Deployment
Press Deploy. Railway will pull the pre-built images, create the Postgres database and link all services on a private network.
4
4. Launch Bytebot
When the build logs show “bytebot-ui: ready”, click the generated URL (e.g.
Tip: You can tail logs for each service from the Railway dashboard.
https://bytebot-ui-prod.up.railway.app). You should see the task interface. Create a task and watch the desktop stream!Tip: You can tail logs for each service from the Railway dashboard.
The first deploy downloads several container layers – expect ~2 minutes. Subsequent redeploys are much faster.
Private Networking & Security
• Private networking ensures that the agent, desktop and database can communicate securely without exposing their ports to the internet.• Public exposure is limited to the UI which serves static assets and proxies WebSocket traffic.
• Add authentication by placing the UI behind Railway’s built-in password protection or an external provider (e.g. Cloudflare Access, Auth0, OAuth proxy).
• You can also point a custom domain to the UI from the Railway dashboard and enable Cloudflare for WAF/CDN protection.
Customisation & Scaling
- Change images – Fork the repo, push your own images and edit the template’s
Dockerfilereferences. - Increase resources – Each service has an independent CPU/RAM slider in Railway. Bump up the desktop or agent if you plan heavy automations.
Troubleshooting
| Symptom | Likely Cause | Fix |
|---|---|---|
| Web UI shows “connecting…” | Desktop not ready or private networking mis-config | Wait for bytebot-desktop container to finish starting, or restart service |
Agent errors 401 or 403 | Missing/invalid API key | Re-enter your AI provider’s API key in Railway variables |
| Slow desktop video | Free Railway plan throttling | Upgrade plan or reduce screen resolution in desktop settings |
Next Steps
• Explore the REST APIs to script tasks programmatically.• Join our Discord community for support and showcase your automations!