deploy-everywhere

name

deploy-everywhere

description

Deploy a Python AI agent or app to multiple platforms in one command: Railway, Fly.io, Docker Hub, AWS Lambda, and GitHub Actions CI. Generates Dockerfile, platform-specific configs, environment variable templates, and a deployment checklist. Adapted from OpenClaw's multi-platform deployment pipeline. Use when you want to ship Nanobot-powered tools to production without manual config per platform.

deploy-everywhere

Ship your Nanobot app to 10 platforms from one command.

Usage

@Nanobot deploy-everywhere --platforms railway,fly,lambda
@Nanobot deploy-everywhere --platforms docker --push ghcr.io/mk-knight23/nanobot
@Nanobot deploy-everywhere --dry-run      # Preview all configs, don't deploy
@Nanobot deploy-everywhere --platform github-actions --trigger push:main

Supported Platforms

Platform	Config Generated	Deploy Method
Railway	railway.toml	railway up
Fly.io	fly.toml	fly deploy
AWS Lambda	serverless.yml	sls deploy
Docker Hub	Dockerfile	docker push
GitHub Actions	.github/workflows/deploy.yml	git push
Render	render.yaml	git push
Heroku	Procfile	git push heroku

Files Created

Dockerfile                          # Multi-stage Python build, <150MB image
.dockerignore                       # Excludes .env, __pycache__, tests
railway.toml                        # Railway service + env config
fly.toml                            # Fly.io app config
.github/workflows/deploy.yml        # CI/CD pipeline
.env.template                       # All required env vars (no secrets)
DEPLOY_CHECKLIST.md                 # Pre-flight checklist before going live

What It Handles

1. Dependency Optimization

• Uses uv for fast Docker layer caching
• Separates production from dev deps
• Pins exact versions in requirements.lock

2. Environment Variable Management

• Scans code for os.environ and os.getenv calls
• Generates .env.template with all required vars
• Adds startup validation: fails fast if required vars are missing

3. Health Check Endpoint

• Injects /health endpoint into your agent gateway
• Returns: uptime, version, active provider, memory usage

4. Secrets Detection

• Blocks deploy if .env file is in git staging
• Warns on hardcoded strings matching secret patterns
• Integrates with git-secrets if installed

Multi-Platform CI/CD

# Generated .github/workflows/deploy.yml
on:
  push:
    branches: [main]
jobs:
  deploy:
    steps:
      - uses: actions/checkout@v4
      - run: pip install uv && uv sync
      - run: python -m pytest --tb=short
      - run: railway up          # or fly deploy, etc.

Philosophy

Nanobot should ship everywhere. One Docker image, multiple runtimes. The skill handles the plumbing so you focus on the agent logic.