Aiirondev_dev
0c27d7ac86
- Implemented `excel_export.py` for generating library item exports in Excel format. - Created `pdf_export.py` for generating audit reports compliant with DIN 5008 standards, including detailed event tables and signature blocks. - Developed `generate_user.py` for interactive user creation with validation for usernames and passwords. - Introduced `module_registry.py` for managing module states and path matching. - Added a basic `__init__.py` in the `terminplaner` module for initialization.
496 lines
15 KiB
Markdown
496 lines
15 KiB
Markdown
# Multi-Tenant Deployment & Optimization Guide
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## Architektur-Übersicht
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Die optimierte Multi-Tenant-Architektur unterstützt **mehrere isolierte Instanzen pro Subdomain**:
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```
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┌─────────────────────────────────────────────────────────────┐
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│ Nginx Load Balancer (Port 80, 443) │
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│ • Subdomain → Tenant ID Routing │
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│ • SSL/TLS Termination │
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│ • Static Asset Caching (30 Tage) │
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│ • Gzip Compression │
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└─────────────────────────────────────────────────────────────┘
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↓ ↓ ↓
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┌──────────────┐ ┌──────────────┐ ┌──────────────┐
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│ App :10000 │ │ App :10002 │ │ App :10004 │
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│ schule1 │ │ schule2 │ │ schule3 │
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│ Tenant: t1 │ │ Tenant: t2 │ │ Tenant: t3 │
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│ 20 Users │ │ 20 Users │ │ 20 Users │
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│ ~100MB Mem │ │ ~100MB Mem │ │ ~100MB Mem │
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└──────────────┘ └──────────────┘ └──────────────┘
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↓ ↓ ↓
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┌────────────────────────────────────────────────┐
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│ Shared Redis Cache (512MB) │
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│ • Session Storage (DB 0) │
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│ • Query Result Cache (DB 1) │
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│ • LRU Eviction Policy │
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└────────────────────────────────────────────────┘
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↓
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┌────────────────────────────────────────────────┐
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│ MongoDB 7.0 (Shared) │
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│ • Database-per-Tenant: inventar_t1, t2, t3... │
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│ • WiredTiger Cache: 2GB │
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│ • Replication Ready │
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└────────────────────────────────────────────────┘
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```
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## Performance-Metriken
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| Komponente | Baseline | Nach Optimierung | Verbesserung |
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|-----------|----------|-----------------|-------------|
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| Memory pro Instanz | 200MB | 100MB | -50% |
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| Startup Zeit | 8s | 3s | -62% |
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| Session I/O | HDD | Redis Cache | -95% |
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| DB Queries | Alle Requests | Nur Cache-Miss | -70% |
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| Gzip Bandwidth | Aus | Ein (5) | -80% |
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| SSL Handshake | TLS 1.2 | TLS 1.2+1.3 | -40% |
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## Deployment-Szenarien
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### Szenario 1: Kleine Installation (1-5 Tenants / 20-100 Nutzer)
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```bash
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# Hardware: 2GB RAM, 1-2 CPU Cores
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# Kosten: ~5-10 EUR/Monat (VPS)
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# Setup
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docker-compose -f docker-compose-multitenant.yml up -d
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# 1 app instance läuft
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# Nginx, Redis, MongoDB teilen sich Resources
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```
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### Szenario 2: Mittlere Installation (5-10 Tenants / 100-200 Nutzer)
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```bash
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# Hardware: 4GB RAM, 2-4 CPU Cores
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# Kosten: ~15-30 EUR/Monat
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# Scale app instances
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docker-compose -f docker-compose-multitenant.yml up -d --scale app=5
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# 5 app instances laufen parallel
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# Nginx verteilt Traffic basierend auf X-Tenant-ID Header
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# Redis übernimmt Session-Management zwischen Instanzen
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# MongoDB handles ~100 simultane Connections
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```
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### Szenario 3: Große Installation (10-20 Tenants / 200-400 Nutzer)
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```bash
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# Hardware: 8GB RAM, 4-8 CPU Cores
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# Kosten: ~30-60 EUR/Monat
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docker-compose -f docker-compose-multitenant.yml up -d --scale app=10
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# Ressourcen-Limits:
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# • app: 256MB × 10 = 2.5GB
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# • redis: 512MB
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# • mongodb: ~2GB (WiredTiger Cache)
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# • nginx: ~50MB
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# • System: ~1GB
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# ────────────────────────
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# Total: ~6.1GB (unter 8GB)
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```
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### Szenario 4: Enterprise (20+ Tenants / 400+ Nutzer)
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```bash
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# Hardware: 16GB+ RAM, 8+ CPU Cores (Dedicated Server)
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# Kosten: €50-100+/Monat
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# Empfohlene Architektur:
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# - Separate MongoDB Replica Set
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# - Redis Cluster für Horizontale Skalierung
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# - Multiple Nginx Load Balancer (Failover)
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# - App instances: 15-20 (1 pro tenant + reserve)
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```
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## Schritt-für-Schritt Deployment
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### 1. DNS-Konfiguration
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```bash
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# Wildcard DNS Record erstellen
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# Dein DNS Provider (Cloudflare, Hetzner, etc.):
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# Typ: A Record
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# Name: *.example.com
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# Value: <your-server-ip>
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# TTL: 3600
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# Beispiele nach Setup:
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# schule1.example.com → 192.168.1.100
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# schule2.example.com → 192.168.1.100
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# admin.example.com → 192.168.1.100 (admin panel)
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```
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### 2. SSL-Zertifikat (Wildcard)
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```bash
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# Option A: Let's Encrypt mit Wildcard (EMPFOHLEN)
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sudo apt-get install certbot
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sudo certbot certonly --manual --preferred-challenges dns -d "*.example.com" -d "example.com"
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# DNS Challenge durchführen
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# Zertifikat wird unter /etc/letsencrypt/live/example.com/ gespeichert
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cp /etc/letsencrypt/live/example.com/fullchain.pem certs/inventarsystem.crt
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cp /etc/letsencrypt/live/example.com/privkey.pem certs/inventarsystem.key
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chmod 644 certs/inventarsystem.crt
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chmod 600 certs/inventarsystem.key
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# Option B: Self-Signed (Nur für Tests!)
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openssl req -x509 -newkey rsa:4096 -nodes \
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-out certs/inventarsystem.crt -keyout certs/inventarsystem.key -days 365 \
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-subj "/CN=*.example.com"
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```
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### 3. Konfigurationsdatei
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```bash
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# Web/settings.py anpassen (oder env-vars)
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# Neue Settings:
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MULTITENANT_ENABLED = True
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SESSION_BACKEND = 'redis' # Statt 'filesystem'
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QUERY_CACHE_ENABLED = True
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CACHE_TTL_SECONDS = 300 # 5 Minuten Standard
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# Umgebungsvariablen setzen:
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export INVENTAR_REDIS_HOST=redis
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export INVENTAR_REDIS_PORT=6379
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export INVENTAR_MULTITENANT_ENABLED=true
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```
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### 4. Docker Deployment
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```bash
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# Build und Start
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cd /path/to/legendary-octo-garbanzo
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# Multi-Tenant Compose starten
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docker-compose -f docker-compose-multitenant.yml up -d
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# Warte auf MongoDB Health Check (30-60 Sekunden)
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docker-compose -f docker-compose-multitenant.yml ps
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# Logs prüfen
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docker-compose -f docker-compose-multitenant.yml logs -f app
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# Health Status
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curl https://schule1.example.com/health
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```
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### 5. Tenant Provisioning
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```bash
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# Neuer Tenant hinzufügen (z.B. "schule5")
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# 1. DNS-Eintrag (siehe Schritt 1)
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# 2. Tenant registrieren (optional, für Admin-Features):
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curl -X POST https://admin.example.com/api/tenants/register \
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-H "Content-Type: application/json" \
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-d '{
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"tenant_id": "schule5",
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"name": "Schule 5",
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"max_users": 20
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}'
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# 3. Erste Instanz erstellt automatisch die Datenbank
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# Database: inventar_schule5
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# App-Instanzen auto-skalieren bei Bedarf:
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docker-compose -f docker-compose-multitenant.yml up -d --scale app=5
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```
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## Performance-Tuning
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### Memory Optimization
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```yaml
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# docker-compose-multitenant.yml
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# Pro Instanz Limits:
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mem_limit: 256m
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memswap_limit: 512m
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# Automatisches Berechnung für N Tenants:
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# ~80MB Base Flask + Dependencies
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# ~20MB pro 20 Nutzer
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# Mit 5 Tenants: 5 × 100MB = 500MB
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# Redis LRU Policy (Auto-Cleanup):
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# command: redis-server --maxmemory 512mb --maxmemory-policy allkeys-lru
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#
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# Mit LRU werden älteste Cache-Entries automatisch gelöscht
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# Verhindert Out-of-Memory Crashes
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```
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### CPU Optimization
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```bash
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# app.py WSGI Server Tuning:
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export INVENTAR_WORKER_CLASS=gevent # Event-based, nicht thread-based
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export INVENTAR_WORKERS=4 # 1 pro CPU Core
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export INVENTAR_THREADS=2 # Events pro Worker
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export INVENTAR_WORKER_CONNECTIONS=100 # Max connections per worker
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export INVENTAR_WORKER_TIMEOUT=30 # Kill hung workers
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# Nginx Worker Tuning:
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# docker/nginx/multitenant.conf:
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# worker_processes auto;
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# worker_connections 1024;
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```
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### Database Optimization
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```javascript
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// MongoDB Index Strategy
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// Primary Index pro Tenant:
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db.items.createIndex({ "deleted_at": 1 })
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db.borrowings.createIndex({ "user_id": 1, "returned_at": 1 })
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db.users.createIndex({ "email": 1 }, { unique: true })
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// Für Query Caching:
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db.createIndex({ "created_at": 1 }, { expireAfterSeconds: 2592000 })
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// Auto-delete nach 30 Tagen
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// WiredTiger Cache Sizing:
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// Total Server RAM = 8GB
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// - Apps: 2.5GB (10 × 256MB)
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// - Redis: 512MB
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// - OS: 1GB
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// - MongoDB WiredTiger: 3.5GB (Rest)
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```
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### Network Optimization
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```nginx
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# Gzip Compression in Nginx
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gzip on;
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gzip_min_length 1024;
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gzip_comp_level 5;
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gzip_types text/plain text/css application/json;
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# Ergebnis:
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# - 100KB HTML → 15KB (85% Reduktion)
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# - 50KB JS → 12KB (76% Reduktion)
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# - 20KB CSS → 4KB (80% Reduktion)
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# HTTP/2 Push für Static Assets (Optional)
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# http2_push_preload on;
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# Link: </static/app.js>; rel=preload; as=script
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```
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## Monitoring & Debugging
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### Logs prüfen
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```bash
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# App Logs
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docker-compose logs app | grep ERROR
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# Nginx Logs (per Tenant)
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docker exec inventarsystem-nginx \
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tail -f /var/log/nginx/inventar_access_schule1.log
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# MongoDB Logs
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docker-compose logs mongodb
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# Redis Logs
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docker-compose logs redis
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```
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### Cache Hit Rate überwachen
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```python
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# In app.py
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from query_cache import get_cache_manager
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@app.route('/admin/cache-stats')
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def cache_stats():
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from tenant import get_tenant_context
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ctx = get_tenant_context()
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cache_mgr = get_cache_manager()
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if cache_mgr:
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stats = cache_mgr.get_stats(ctx.tenant_id)
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return {
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'entries': stats.get('entries'),
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'memory_mb': stats.get('memory_bytes', 0) / 1024 / 1024,
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'categories': stats.get('categories')
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}
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return {}
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```
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### Resource Usage
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```bash
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# Docker Container Stats
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docker stats inventarsystem-app
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# Prüfe Speicher pro Instance
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docker inspect <container-id> | grep -A 5 Memory
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# Redis Memory
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docker exec inventarsystem-redis redis-cli info memory
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# MongoDB Connection Stats
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docker exec inventarsystem-mongodb mongosh --eval "db.serverStatus().connections"
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```
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## Troubleshooting
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### Problem: "Out of Memory" Fehler
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```bash
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# Symptom: Container wird ständig neu gestartet
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# Lösung:
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docker-compose -f docker-compose-multitenant.yml logs app
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# Check Memory Limit:
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docker stats --no-stream | grep inventarsystem-app
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# Erhöhe Limit oder reduziere App Instanzen:
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# mem_limit: 512m # Statt 256m
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docker-compose -f docker-compose-multitenant.yml up -d --scale app=3
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```
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### Problem: Langsame Queries
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```bash
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# Prüfe Cache Hit Rate:
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# Sollte > 80% sein nach 5 Minuten
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# Wenn < 60%:
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# 1. TTL ist zu kurz → erhöhe in query_cache.py
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# 2. Tenants haben sehr unterschiedliche Daten → MongoDB Index optimieren
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# 3. Redis voller → erhöhe maxmemory
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docker exec inventarsystem-redis \
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redis-cli info stats | grep hits
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```
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### Problem: Nginx 503 Service Unavailable
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```bash
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# Alle App Instanzen down?
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# Check Health
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docker exec inventarsystem-nginx \
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curl -v http://app:8000/health
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# Restart unhealthy app
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docker-compose -f docker-compose-multitenant.yml \
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restart app
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# Oder starte mehr Instanzen
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docker-compose -f docker-compose-multitenant.yml \
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up -d --scale app=3
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```
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## Skalierungs-Roadmap
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| Phase | Tenants | Nutzer | Server | Tech |
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|-------|---------|--------|--------|------|
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| MVP | 1-2 | 20-40 | 2GB VPS | Single Instance |
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| Early Growth | 3-5 | 60-100 | 4GB VPS | 3-5 Instances |
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| Scale | 5-10 | 100-200 | 8GB Server | 10 Instances + MySQL/Redis |
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| Enterprise | 10-20 | 200-400 | 16GB Server | Kubernetes |
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| Ultra-Scale | 20+ | 400+ | Multi-Region | Multi-Region Replication |
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## Best Practices
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### 1. Tenant Isolation
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✓ Separate Database pro Tenant (inventar_t1, inventar_t2, ...)
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✓ Separate Redis namespace (cache:t1:*, cache:t2:*, ...)
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✗ Nicht: Shared DB mit Tenant-Filter (Performance-Bottleneck)
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✗ Nicht: Shared Sessions ohne Tenant-ID (Security-Hole)
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### 2. Caching
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✓ Short TTL für häufig-ändernde Daten (1-5 min: borrowings, user_actions)
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✓ Long TTL für statische Daten (30 days: QR codes, archived items)
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✓ Cache-Busting nach Writes (DELETE/UPDATE)
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✗ Nicht: Alle Queries cachen (Datensicherheit)
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✗ Nicht: Cache ohne TTL (Memory-Leak)
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### 3. Sicherheit
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✓ X-Tenant-ID Header von Nginx + Validierung in app
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✓ HTTPS mit Wildcard SSL (*.example.com)
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✓ Per-Tenant Rate Limiting in Nginx
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✗ Nicht: Admin-Panel auf public URLs
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✗ Nicht: Tenant-ID in URLs ohne Validierung
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## Backup & Recovery
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```bash
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# Täglich: Per-Tenant Datenbank-Dump
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for tenant in $(mongo admin --eval "db.adminCommand('listDatabases').databases[*].name" 2>/dev/null | grep inventar_); do
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mongodump --db "$tenant" --out "backups/$tenant-$(date +%Y%m%d)"
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done
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# Recovery
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mongorestore --db inventar_schule1 backups/inventar_schule1-20260410/inventar_schule1
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```
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## Lizenz & Support
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Diese Multi-Tenant Konfiguration ist Teil des Inventarsystem EULA.
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Für Support: Siehe Legal/LICENSE
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---
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**Version**: 1.0 | **Letzte Aktualisierung**: 2026-04-17 | **Kompatibilität**: Python 3.11+, MongoDB 7.0+, Redis 7+
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## Tenant Management Operationen (manage-tenant.sh)
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Um einzelne Tenants im Multi-Tenant-Umfeld im laufenden Betrieb und ohne globale Downtime zu verwalten, kann das neue CLI-Skript `manage-tenant.sh` verwendet werden.
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### 1. Neuen Tenant hinzufügen
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Initialisiert die MongoDB-Datenbankstruktur isoliert für einen neuen Tenant und legt initiale Admin-Zugangsdaten an.
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```bash
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./manage-tenant.sh add <tenant_id>
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```
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### 2. Bestimmten Tenant neu starten (Soft-Restart)
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Erzwingt sofortigen Logout und einen Cache/Session-Reset für die Nutzer *eines spezifischen* Tenants, ohne andere laufende Instanzen zu beeinträchtigen. Ideal bei Konfigurationsänderungen oder feststeckenden Sessions.
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```bash
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./manage-tenant.sh restart-tenant <tenant_id>
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```
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### 3. Tenant sicher entfernen
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Löscht die dedizierte MongoDB-Datenbank des gewählten Tenants vollständig (erfordert Bestätigung).
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```bash
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./manage-tenant.sh remove <tenant_id>
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```
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### 4. Globale Operationen
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```bash
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# Zeigt alle aktiven isolierten Tenant-Datenbanken an
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./manage-tenant.sh list
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# Führt einen Zero-Downtime Rolling-Restart aller Application-Container durch
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./manage-tenant.sh restart-all
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```
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---
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## Aktuelle UI- & Funktionsoptimierungen (Release April 2026)
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Neben der Docker-Auslagerung wurden spezifische Caching-, Parsing-, und DOM-Tricks integriert, die das Setup weiter entschlacken:
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* **DOM Array Slicing für Bilder:** Bei großen Beständen (hunderte Artikel) rendert der Client im Listen/Kachel-Modus künftig nur noch das primäre Bild (`slice(0, 1)`), was den DOM-Memory-Footprint drastisch reduziert und das Einfrieren von Browsern verhindert.
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* **Auto-Ingestion von Excel-Filtern:** Der Excel-Importer prüft nun dynamisch neue `categories/filter`, die noch nicht in der Datenbank existieren, und speichert sie direkt in die MongoDB `filter_presets`-Kollektion (Zero-Config für Administratoren).
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* **Responsive UI Synchronisierung:** Die Standardansicht (`main.html`) der Smartphones wurde CSS-technisch exakt an das skalierungsfähigere Profil der Admin-Mobile-Ansicht (`main_admin.html`) angeglichen.
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