# Production deployment notes

## Gitea Actions
This repo includes `.gitea/workflows/ci-deploy.yml` for:
- backend build
- backend tests
- frontend tests
- frontend production build
- deployment to Ubuntu after successful tests on `main`

### Required secrets in Gitea
- `PROD_HOST`
- `PROD_USER`
- `PROD_SSH_KEY`

## Ubuntu server setup
Recommended app path:
- `/opt/job-tracker/app`

Persistent runtime secrets path:
- `/opt/job-tracker/shared/.env`

Requirements:
- Docker Engine
- Docker Compose plugin
- reverse proxy in front (Nginx, Caddy, or Traefik)
- shared env file present on server in `/opt/job-tracker/shared/.env`
- network connectivity from the backend container to your `mariadb` container/service

The deploy script will automatically create a symlink from:
- `/opt/job-tracker/shared/.env`

to:
- `/opt/job-tracker/app/.env`

This keeps secrets outside the uploaded repo checkout so they are not wiped by CI deploys.

### Frontend API base URL
The production frontend already proxies `/api` to the backend container via Nginx.

Recommended default:
- leave `REACT_APP_API_BASE_URL` unset/empty in production

Only set `REACT_APP_API_BASE_URL` if the UI must call a different external API origin on purpose.

## Example production `.env`
```env
DATABASE_PROVIDER=mariadb
JOBTRACKER_CONNECTION_STRING=server=mariadb;port=3306;database=jobtracker;user=jobtracker;password=REPLACE_ME
AUTH_JWT_KEY=replace_with_long_random_secret
AUTH_ADMIN_EMAIL=you@example.com
AUTH_ADMIN_PASSWORD=replace_with_strong_password
APP_PUBLIC_BASE_URL=https://your-domain.example
AI_SERVICE_BASE_URL=http://ai-service:8001
EMAIL_FOLLOWUPREMINDERS_ENABLED=true
EMAIL_FOLLOWUPREMINDERS_UPCOMINGDAYS=2
# Optional backward-compatible alias if older config still references the previous name:
SUMMARIZER_BASE_URL=http://ai-service:8001
```

## Database recommendation
For production, yes — use a real database.

### Recommended direction
Short term:
- SQLite is acceptable for a single-user or very small deployment
- keep backups and volume persistence

Better production choice:
- MariaDB or PostgreSQL

### My recommendation
- **PostgreSQL** if you want the best long-term maintainability and fewer edge cases
- **MariaDB** is also fine if that is what you already know or host elsewhere

If you stay on SQLite:
- okay for small personal use
- not ideal for concurrent writes, larger scale, or operational robustness

## Practical recommendation for this project
If this app is going to be a real production service on Ubuntu:
- move to PostgreSQL first if possible
- MariaDB is still a reasonable option if preferred

## Deployment flow
1. push to `main`
2. Gitea Actions runs tests
3. if green, workflow uploads repo to server
4. `deploy/deploy.sh` links `/opt/job-tracker/shared/.env` into the repo checkout, then runs `docker compose build && docker compose up -d`
5. workflow checks service status after deployment

## Post-deploy verification you should also do manually the first time
- confirm reverse proxy routes to the frontend correctly
- confirm API auth/login works with production config
- confirm backend can connect to MariaDB
- confirm AI service container is reachable from backend
- confirm reminder and admin/system pages load
- verify follow-up reminder emails are enabled only when intended and that links open the correct job/tab