dockerized läuft
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# Deployment & CI/CD Guide
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## 1. Gitea Actions Workflow
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## 1. Docker Development Cycle
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Der empfohlene Entwicklungs-Workflow nutzt Docker Compose für eine isolierte Umgebung mit Hot-Reload.
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### Voraussetzungen
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- Docker (v20.10+)
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- Docker Compose (v2.0+)
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### Ersts Start (Build & Initialize)
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```bash
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# Navigiere zum Projektverzeichnis
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cd formeleon
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# Build Images und Start Container
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docker-compose up --build
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```
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Das Entrypoint-Script führt automatisch folgende Schritte aus:
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1. Prüft Python-Abhängigkeiten
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2. Führt Datenbank-Migrationen aus (`flask db upgrade`)
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3. Seeded die Datenbank mit Testdaten (`flask seed-db`) - nur bei leerer DB
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4. Startet den Flask-Entwicklungsserver mit Hot-Reload
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### Täglicher Entwicklungs-Workflow
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#### Container starten/stoppen
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```bash
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# Starten (im Hintergrund)
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docker-compose up -d
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# Stoppen
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docker-compose down
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# Neu starten (nach Code-Änderungen)
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docker-compose restart app
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# Logs anzeigen
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docker-compose logs -f app
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```
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#### Code-Änderungen testen
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Dank der Volume-Mounts in `docker-compose.yml` werden Änderungen an folgenden Verzeichnissen sofort im Container sichtbar:
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- `app.py`, `config.py`, `models.py`
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- `routes/`
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- `services/`
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- `utils/`
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- `templates/`
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- `static/`
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- `migrations/`
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**Kein Container-Rebuild nötig!** Der Flask-Dev-Server erkennt Änderungen und lädt neu.
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### Flask CLI-Kommandos in Docker
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Führe Flask-Kommandos im laufenden Container aus:
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```bash
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# Allgemeine Syntax
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docker-compose run --rm app flask <kommando>
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# Beispiele:
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# Migration erstellen
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docker-compose run --rm app flask db migrate -m "add user table"
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# Migration anwenden
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docker-compose run --rm app flask db upgrade
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# Migration zurücksetzen
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docker-compose run --rm app flask db downgrade
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# Datenbank mit Testdaten füllen
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docker-compose run --rm app flask seed-db
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# Mandanten verwalten
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docker-compose run --rm app flask create-tenant "Test" "public-key-123"
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# Benutzer verwalten
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docker-compose run --rm app flask create-user "test@example.com" "Test User" --role=admin
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```
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### Shell im Container
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```bash
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# Interaktive Shell
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docker-compose exec app bash
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# Python Shell
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docker-compose exec app python
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# Flask Shell (mit App-Kontext)
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docker-compose exec app flask shell
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```
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### Datenbank zurücksetzen
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```bash
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# Container stoppen und Volumes löschen (ACHTUNG: Alle Daten gehen verloren!)
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docker-compose down -v
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# Neu starten mit frischer Datenbank
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docker-compose up --build
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```
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---
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## 2. Docker Setup für Produktion
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Für die Produktion sollte ein separates `docker-compose.prod.yml` erstellt werden.
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### `docker-compose.prod.yml` (Beispiel)
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```yaml
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version: '3.8'
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services:
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web:
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build: .
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container_name: formeleon-web
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ports:
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- "8000:5000"
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environment:
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- FLASK_ENV=production
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- FLASK_DEBUG=0
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- DEV_MODE=false
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- SECRET_KEY=${SECRET_KEY}
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- SQLALCHEMY_DATABASE_URI=${DATABASE_URL}
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- ZITADEL_ISSUER=${ZITADEL_ISSUER}
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- ZITADEL_CLIENT_ID=${ZITADEL_CLIENT_ID}
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- ZITADEL_CLIENT_SECRET=${ZITADEL_CLIENT_SECRET}
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- RECAPTCHA_SITE_KEY=${RECAPTCHA_SITE_KEY}
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- RECAPTCHA_SECRET_KEY=${RECAPTCHA_SECRET_KEY}
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volumes:
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- ./data:/app/data
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restart: always
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:5000/"]
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interval: 30s
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timeout: 10s
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retries: 3
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postgres:
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image: postgres:15-alpine
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container_name: formeleon-postgres
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environment:
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- POSTGRES_DB=formeleon
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- POSTGRES_USER=formeleon
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- POSTGRES_PASSWORD=${POSTGRES_PASSWORD}
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volumes:
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- postgres_data:/var/lib/postgresql/data
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ports:
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- "5432:5432"
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restart: always
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U formeleon"]
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interval: 5s
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timeout: 5s
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retries: 5
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volumes:
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postgres_data:
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```
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### Produktion starten
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```bash
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# Mit kombinierter Konfiguration
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docker-compose -f docker-compose.yml -f docker-compose.prod.yml up -d --build
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# Logs anzeigen
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docker-compose logs -f
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# Status prüfen
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docker-compose ps
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```
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---
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## 3. Gitea Actions Workflow
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Bei einem Push auf den `main`-Branch oder einem Release-Tag führt der Gitea-Runner automatisiert folgende Schritte auf dem Zielserver aus:
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@@ -8,27 +183,70 @@ Bei einem Push auf den `main`-Branch oder einem Release-Tag führt der Gitea-Run
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2. Erstellen/Aktualisieren der Docker-Images.
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3. Zero-Downtime Restart der Container via Docker Compose.
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### Beispiel `.gitea/workflows/deploy.yml`
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```yaml
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name: Deploy to Production
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on:
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push:
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branches: [main]
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tags: ['v*']
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jobs:
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deploy:
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runs-on: self-hosted
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Stop services
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run: docker-compose -f docker-compose.yml -f docker-compose.prod.yml down
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- name: Pull latest images
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run: docker-compose -f docker-compose.yml -f docker-compose.prod.yml pull
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- name: Build and start
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run: docker-compose -f docker-compose.yml -f docker-compose.prod.yml up -d --build
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- name: Run migrations
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run: docker-compose -f docker-compose.yml -f docker-compose.prod.yml run --rm web flask db upgrade
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- name: Cleanup
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run: docker system prune -f
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```
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---
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## 2. Docker Setup
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## 4. Docker Troubleshooting
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Das System läuft in einem schlanken Gunicorn-Container hinter einem Reverse Proxy.
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### Häufige Probleme & Lösungen
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### `docker-compose.yml` (Auszug)
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```yaml
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version: '3.8'
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| Problem | Lösung |
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|---------|--------|
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| Port 5000 bereits belegt | `docker-compose down` und neu starten |
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| Datenbank-Fehler | `docker-compose down -v && docker-compose up --build` |
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| Python-Module nicht gefunden | `docker-compose build --no-cache && docker-compose up` |
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| Container startet nicht | `docker-compose logs app` prüfen |
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| Hot-Reload funktioniert nicht | Volume-Mounts in docker-compose.yml prüfen |
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services:
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web:
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build: .
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restart: always
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env_file:
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- .env
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ports:
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- "8000:8000"
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volumes:
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- sqlite_data:/app/data
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### Debug-Modus
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volumes:
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sqlite_data:
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```bash
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# Container im Debug-Modus starten
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docker-compose up --build --abort-on-container-exit
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# Oder mit Shell
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ENTERPOINT_OVERRIDE=bash docker-compose run --rm --service-ports app
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```
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### Cache leeren
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```bash
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# Docker Cache leeren
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docker builder prune
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# Unused Images entfernen
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docker image prune -a
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# System cleanup
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docker system prune -a --volumes
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```
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