How to install Clawdbot on a dedicated server

This guide is written for teams deploying Clawdbot-like AI agent workloads on dedicated infrastructure. It focuses on stable operations, repeatable deployment, and secure defaults.

One-click installer script

For customers who want a faster setup, use the one-click installer below (Ubuntu/Debian dedicated servers): 

curl -fsSL https://offshorehost.info/scripts/clawdbot-oneclick-install.sh | sudo bash

With automatic domain + TLS setup:

curl -fsSL https://offshorehost.info/scripts/clawdbot-oneclick-install.sh | sudo bash -s -- --domain bot.example.com --email [email protected]

Script path: /scripts/clawdbot-oneclick-install.sh. It installs Docker, creates /opt/clawdbot, writes .env and docker-compose.yml, and configures systemd autostart. When --domain and --email are set, it also configures Nginx reverse proxy and Let's Encrypt TLS.

Quick security hardening checklist (copy/paste)

Use this as a pre-production signoff list for Clawdbot dedicated deployments: 

[ ] SSH password auth disabled; key-only access enabled
[ ] Root login disabled for remote SSH
[ ] Firewall allowlist applied (SSH, app edge, monitoring only)
[ ] OS security updates enabled and verified
[ ] Docker/containers run with least privilege
[ ] Secrets stored outside codebase (.env/secret manager)
[ ] Separate API keys for prod/stage/dev
[ ] API key rotation policy documented
[ ] Webhook signatures verified on all inbound endpoints
[ ] Queue concurrency limits set per worker class
[ ] Tool/action allowlists configured for agent runtime
[ ] Output redaction enabled for tokens and credentials
[ ] Access logs + audit logs retained with retention policy
[ ] Daily encrypted backups configured
[ ] Restore test completed in staging
[ ] Incident runbook tested (simulate provider/API outage)
[ ] Token/cost anomaly alerts configured
[ ] Failover/rollback steps documented and assigned

1) Choose your base architecture

For production, avoid single-process setups. Use at least:

  • Application service (API/web)
  • Queue broker (Redis)
  • Worker pool for agent jobs
  • PostgreSQL for state and audit trails
  • Optional vector store for embedding retrieval

2) Harden the dedicated server first

  • Update packages and enable unattended security upgrades.
  • Disable password SSH, enforce key-based login.
  • Enable firewall allowlist for SSH, app ports, and monitoring.
  • Create non-root deploy user and limit sudo scope.

If running Proxmox, isolate management and app traffic on separate VLANs.

3) Install runtime and deploy stack

Use Docker + Compose unless your team already uses Kubernetes.

  1. Install Docker Engine and Compose plugin.
  2. Create `/opt/clawdbot` and store compose files there.
  3. Add `.env` with API keys, DB URL, queue URL, and feature flags.
  4. Bring up services with health checks and restart policies.

4) Configure workers and queues

Agent systems fail most often due to unbounded concurrency.

  • Set max worker count per queue.
  • Separate heavy jobs from low-latency jobs.
  • Add retry limits and dead-letter queue handling.
  • Track queue depth, job age, and fail rates.

5) Add monitoring, logs, and alerts

Minimum dashboard for Clawdbot-like workloads:

  • API response time (p95/p99)
  • Queue latency and pending job count
  • Worker failure percentage
  • Token/API cost anomalies
  • DB connection and storage growth

6) Backup and recovery plan

Backups are not complete without restore tests.

  • Daily database backup + encrypted off-node copy
  • Weekly restore test into staging
  • Snapshot retention policy for quick rollback
  • Documented incident runbook for operator handoff

7) Production checklist before launch

  • Secrets rotation policy enabled
  • Rate limits configured on public endpoints
  • Webhooks signed and verified
  • Resource quotas set for workers
  • Rollback and maintenance windows documented

8) Security tips for deploying Clawdbot

Secrets and credential hygiene

  • Store API keys in environment variables or a secrets manager, never in code or images.
  • Use separate keys for production, staging, and local testing.
  • Rotate provider keys periodically and immediately after suspected exposure.
  • Restrict key scopes where possible (read-only vs write permissions).

Network and runtime isolation

  • Keep worker nodes on private subnets; expose only reverse proxy/API edge nodes publicly.
  • Separate queues by risk level so untrusted jobs cannot starve critical tasks.
  • Run containers with least privilege (drop capabilities, read-only FS where feasible).
  • Use egress rules to allow only required AI/provider endpoints.

Prompt and tool safety controls

  • Treat external content as untrusted input and sanitize before tool execution.
  • Add allowlists for tool actions (filesystem paths, domains, command classes).
  • Enforce output filters/redaction for credentials, tokens, and internal endpoints.
  • Log tool invocations with user/job context for auditability.

Incident readiness

Prepare a one-page incident runbook: isolate worker pool, disable risky tools, rotate secrets, and replay failed jobs after remediation. Test this process quarterly under simulated load.

Security for AI agents is an operational process, not a one-time setup. Review logs, update policies, and rerun hardening checks after every major feature release.

Need help choosing hardware for Clawdbot + Proxmox? See dedicated plans or continue with the HA + scaling cluster guide or contact us via encrypted channels.