✨ From vibe coding to vibe deployment. UBOS MCP turns ideas into infra with one message.

Learn more
Andrii Bidochko
  • Updated: March 23, 2026
  • 7 min read

Using the Extended OpenClaw DevOps Agent on UBOS: A Full‑Stack Deployment Guide

The extended OpenClaw DevOps Agent lets you provision infrastructure as code and deploy a full‑stack application on UBOS in just a few commands.

Introduction

AI‑agents are dominating headlines, and the Moltbook social network has become the newest playground for developers experimenting with autonomous workflows. While the hype is real, turning that excitement into a production‑ready stack still requires solid DevOps foundations.

Enter the extended OpenClaw DevOps Agent—a lightweight, open‑source automation layer that integrates natively with the UBOS platform overview. In this guide you’ll learn how to install the agent, define your infrastructure as code (IaC), and launch a complete backend‑frontend application with a managed database, all within the UBOS ecosystem.

Prerequisites

Before you start, make sure you have the following ready:

  • A registered UBOS for startups account (free tier works for testing).
  • UBOS CLI installed (npm i -g @ubos/cli).
  • Git ≥ 2.30, Docker ≥ 20.10, and a local code editor.
  • Basic knowledge of YAML/JSON for IaC definitions.

Having these tools in place ensures a smooth, repeatable deployment pipeline.

Installing the OpenClaw DevOps Agent

The agent is distributed as a Docker image and a small CLI wrapper. Follow the steps below:

# Pull the latest OpenClaw image
docker pull ubos/openclaw-agent:latest

# Verify the image
docker run --rm ubos/openclaw-agent:latest --version

# Install the CLI helper
npm i -g @ubos/openclaw-cli

Once installed, authenticate the CLI with your UBOS token:

ubos login --token YOUR_UBOS_API_TOKEN

Now the agent can communicate securely with your UBOS workspace.

Defining Infrastructure as Code

OpenClaw uses a declarative YAML schema that mirrors UBOS resource types. Below is a minimal infrastructure.yaml that provisions a container runtime, a PostgreSQL database, and a static file bucket.

resources:
  - name: app-runtime
    type: container
    image: node:18-alpine
    ports:
      - 8080:8080
    env:
      - NODE_ENV=production

  - name: pg-db
    type: postgres
    version: "13"
    storage: 10Gi
    credentials:
      username: ubos_user
      password: ${DB_PASSWORD}

  - name: static-bucket
    type: bucket
    public: true

Each block is self‑contained, making the file MECE (Mutually Exclusive, Collectively Exhaustive). The UBOS templates for quick start library offers ready‑made snippets for common services, so you can copy‑paste and adjust values.

Save the file and run the provisioning command:

openclaw apply -f infrastructure.yaml

The agent will spin up the resources, outputting a JSON manifest with endpoint URLs and secret references.

Deploying a Full‑Stack Application

Backend Service (Node.js/Express)

Create a simple API that connects to the PostgreSQL instance. The following snippet lives in src/server.js:

const express = require('express');
const { Pool } = require('pg');
require('dotenv').config();

const app = express();
app.use(express.json());

const pool = new Pool({
  host: process.env.PG_HOST,
  user: process.env.PG_USER,
  password: process.env.PG_PASSWORD,
  database: process.env.PG_DB,
  port: 5432,
});

app.get('/api/health', (req, res) => res.json({status: 'ok'}));

app.get('/api/items', async (req, res) => {
  const { rows } = await pool.query('SELECT * FROM items');
  res.json(rows);
});

const PORT = process.env.PORT || 8080;
app.listen(PORT, () => console.log(`API listening on ${PORT}`));

Commit the code to a Git repo and reference it in the IaC file using the source attribute (shown later). The Web app editor on UBOS can also import this repo directly for rapid iteration.

Frontend UI (React)

For the UI we’ll use a minimal React app that calls the backend API. Save the following as src/App.jsx:

import React, { useEffect, useState } from 'react';
import axios from 'axios';

function App() {
  const [items, setItems] = useState([]);

  useEffect(() => {
    axios.get('/api/items')
      .then(res => setItems(res.data))
      .catch(err => console.error(err));
  }, []);

  return (
    <div className="p-4">
      <h1 className="text-2xl font-bold mb-4">Item List</h1>
      <ul>
        {items.map(item => (
          <li key={item.id}>{item.name}</li>
        ))}
      </ul>
    </div>
  );
}

export default App;

Bundle the UI with vite or create-react-app, then push the build folder to the static-bucket defined earlier. The AI SEO Analyzer can be run on the generated HTML to ensure the page is search‑friendly before publishing.

Database Setup

Initialize the PostgreSQL schema using a migration script. Store the script in migrations/01_init.sql:

CREATE TABLE items (
  id SERIAL PRIMARY KEY,
  name VARCHAR(255) NOT NULL,
  created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

INSERT INTO items (name) VALUES ('UBOS Starter Kit'), ('OpenClaw Agent'), ('Moltbook Integration');

Run the migration via the OpenClaw CLI:

openclaw exec -r pg-db -- psql -f migrations/01_init.sql

Notice the use of the Chroma DB integration for vector‑search capabilities—if you later need semantic lookup, you can attach a Chroma instance with a single line in the IaC file.

Deployment Commands

With the backend, frontend, and database ready, update the IaC file to include the source repository and build steps:

resources:
  - name: app-runtime
    type: container
    image: node:18-alpine
    ports:
      - 8080:8080
    env:
      - NODE_ENV=production
      - PG_HOST=${pg-db.host}
      - PG_USER=${pg-db.username}
      - PG_PASSWORD=${pg-db.password}
      - PG_DB=${pg-db.database}
    source:
      repo: https://github.com/your-org/fullstack-demo
      path: src
    build:
      command: npm install && npm run build

  - name: static-bucket
    type: bucket
    public: true
    source:
      repo: https://github.com/your-org/fullstack-demo
      path: build

Apply the updated configuration:

openclaw apply -f infrastructure.yaml

OpenClaw will pull the code, build the Docker image, push the static assets, and wire the services together. Visit the generated URL (shown in the CLI output) to see your live full‑stack app.

Best‑Practice Tips

Security Hardening

  • Store secrets in UBOS vault and reference them via ${SECRET_NAME} placeholders.
  • Enable TLS on the container runtime by adding tls: true in the resource definition.
  • Restrict bucket access with signed URLs for private assets.

CI/CD Integration

Hook the OpenClaw CLI into your GitHub Actions or GitLab pipelines. A minimal GitHub workflow looks like this:

name: Deploy to UBOS
on:
  push:
    branches: [ main ]
jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up UBOS CLI
        run: npm i -g @ubos/openclaw-cli
      - name: Authenticate
        env:
          UBOS_TOKEN: ${{ secrets.UBOS_TOKEN }}
        run: ubos login --token $UBOS_TOKEN
      - name: Apply IaC
        run: openclaw apply -f infrastructure.yaml

Joining the UBOS partner program gives you access to pre‑approved CI templates and priority support.

Monitoring & Logging

UBOS automatically streams container logs to its built‑in observability stack. For advanced metrics, enable the Enterprise AI platform by UBOS and attach a Prometheus exporter to the app-runtime resource.

AI‑Enhanced Development

Leverage UBOS’s AI marketing agents to auto‑generate release notes, or use the AI Article Copywriter to draft documentation directly from your code comments.

Conclusion & Next Steps

By following this tutorial you have:

  1. Installed the extended OpenClaw DevOps Agent.
  2. Defined a complete IaC blueprint using UBOS resources.
  3. Deployed a production‑grade full‑stack application with a database and static assets.
  4. Integrated security, CI/CD, and monitoring best practices.

Ready to scale? Explore the UBOS pricing plans for larger workloads, or browse the UBOS portfolio examples for inspiration.

For a deeper dive into each resource type, check out our detailed guide on UBOS portfolio examples, which includes advanced patterns like multi‑region failover and AI‑driven autoscaling.

Happy building, and may your OpenClaw agents be ever‑efficient!


Andrii Bidochko

CTO UBOS

Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.

Sign up for our newsletter

Stay up to date with the roadmap progress, announcements and exclusive discounts feel free to sign up with your email.

Sign In

Register

Reset Password

Please enter your username or email address, you will receive a link to create a new password via email.