Initial commit: LLM Automation Docs & Remediation Engine v2.0
Features: - Automated datacenter documentation generation - MCP integration for device connectivity - Auto-remediation engine with safety checks - Multi-factor reliability scoring (0-100%) - Human feedback learning loop - Pattern recognition and continuous improvement - Agentic chat support with AI - API for ticket resolution - Frontend React with Material-UI - CI/CD pipelines (GitLab + Gitea) - Docker & Kubernetes deployment - Complete documentation and guides v2.0 Highlights: - Auto-remediation with write operations (disabled by default) - Reliability calculator with 4-factor scoring - Human feedback system for continuous learning - Pattern-based progressive automation - Approval workflow for critical actions - Full audit trail and rollback capability
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LLM Automation System
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README_MONGODB.md
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README_MONGODB.md
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# 🍃 Sistema Documentazione con MongoDB
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## Novità Versione 2.0
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Il sistema è stato **completamente migrato a MongoDB 7.0** per migliorare:
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- ✅ Flessibilità schema
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- ✅ Performance
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- ✅ Scalabilità
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- ✅ Developer experience
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## 🚀 Quick Start MongoDB
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### 1. Local Development
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```bash
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# Clone repository
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git clone https://git.company.local/infrastructure/datacenter-docs.git
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cd datacenter-docs
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# Setup environment
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cp .env.example .env
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nano .env # Edit MongoDB credentials
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# Start MongoDB + Redis
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docker-compose up -d mongodb redis
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# Install dependencies
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poetry install
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# Start API
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poetry run uvicorn datacenter_docs.api.main:app --reload
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```
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### 2. Docker Compose (All-in-One)
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```bash
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# Edit .env
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cp .env.example .env
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# MongoDB credentials
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MONGO_ROOT_USER=admin
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MONGO_ROOT_PASSWORD=your_secure_password
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MONGODB_URL=mongodb://admin:your_secure_password@mongodb:27017
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MONGODB_DATABASE=datacenter_docs
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# Start everything
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docker-compose up -d
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# Check health
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curl http://localhost:8000/health
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# Response: {"status":"healthy","database":"mongodb",...}
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# Access services
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# API: http://localhost:8000/api/docs
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# Chat: http://localhost:8001
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# Frontend: http://localhost
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# Flower: http://localhost:5555
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```
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### 3. Kubernetes
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```bash
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# Apply manifests
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kubectl apply -f deploy/kubernetes/namespace.yaml
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# Create secrets
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kubectl create secret generic datacenter-secrets \
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--from-literal=mongodb-url='mongodb://admin:password@mongodb:27017' \
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--from-literal=mongodb-root-user='admin' \
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--from-literal=mongodb-root-password='password' \
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--from-literal=redis-url='redis://:password@redis:6379/0' \
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--from-literal=mcp-api-key='your-key' \
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--from-literal=anthropic-api-key='sk-ant-xxx' \
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-n datacenter-docs
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# Deploy MongoDB (StatefulSet with replica set)
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kubectl apply -f deploy/kubernetes/mongodb.yaml
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# Deploy application
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kubectl apply -f deploy/kubernetes/deployment.yaml
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kubectl apply -f deploy/kubernetes/service.yaml
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kubectl apply -f deploy/kubernetes/ingress.yaml
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# Check status
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kubectl get pods -n datacenter-docs
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```
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## 📊 MongoDB Features
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### Document Structure
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Tutti i dati sono memorizzati come documenti JSON nativi:
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```json
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{
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"ticket_id": "INC-12345",
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"title": "Network issue",
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"description": "Cannot reach VLAN 100",
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"status": "resolved",
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"resolution": "Check switch configuration...",
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"suggested_actions": ["action1", "action2"],
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"confidence_score": 0.92,
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"metadata": {
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"source": "ServiceNow",
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"custom_field": "any value"
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},
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"created_at": ISODate("2025-01-15T10:30:00Z")
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}
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```
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### Collections
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- `tickets` - Ticket e risoluzioni
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- `documentation_sections` - Metadata sezioni doc
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- `chat_sessions` - Conversazioni chat
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- `system_metrics` - Metriche sistema
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- `audit_logs` - Audit trail
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### Beanie ODM
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Utilizziamo **Beanie** (ODM moderno) per type-safe document operations:
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```python
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from datacenter_docs.api.models import Ticket
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# Create
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ticket = Ticket(
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ticket_id="INC-001",
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title="Test",
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description="Testing MongoDB"
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)
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await ticket.insert()
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# Find
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tickets = await Ticket.find(Ticket.status == "resolved").to_list()
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# Update
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ticket.status = "closed"
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await ticket.save()
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# Delete
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await ticket.delete()
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# Aggregation
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pipeline = [
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{"$group": {
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"_id": "$category",
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"count": {"$sum": 1}
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}}
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]
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result = await Ticket.aggregate(pipeline).to_list()
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```
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## 🔧 Configurazione MongoDB
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### Environment Variables
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```bash
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# Required
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MONGODB_URL=mongodb://admin:password@mongodb:27017
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MONGODB_DATABASE=datacenter_docs
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# Optional (for admin operations)
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MONGO_ROOT_USER=admin
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MONGO_ROOT_PASSWORD=secure_password
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```
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### Connection String Examples
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```bash
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# Local
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MONGODB_URL=mongodb://admin:password@localhost:27017
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# Docker Compose
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MONGODB_URL=mongodb://admin:password@mongodb:27017
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# Kubernetes (single)
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MONGODB_URL=mongodb://admin:password@mongodb.datacenter-docs.svc.cluster.local:27017
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# Kubernetes (replica set)
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MONGODB_URL=mongodb://admin:password@mongodb-0.mongodb:27017,mongodb-1.mongodb:27017,mongodb-2.mongodb:27017/?replicaSet=rs0
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# MongoDB Atlas (cloud)
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MONGODB_URL=mongodb+srv://user:password@cluster.mongodb.net/datacenter_docs?retryWrites=true&w=majority
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```
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## 🔍 Query Examples
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### Python API
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```python
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# Simple queries
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resolved = await Ticket.find(Ticket.status == "resolved").to_list()
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high_priority = await Ticket.find(
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Ticket.priority == "high",
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Ticket.status == "processing"
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).to_list()
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# Complex queries
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from datetime import datetime, timedelta
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recent = datetime.now() - timedelta(days=7)
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high_confidence = await Ticket.find(
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Ticket.created_at > recent,
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Ticket.confidence_score > 0.9
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).sort(-Ticket.created_at).to_list()
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# Text search
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search_results = await Ticket.find({
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"$text": {"$search": "network connectivity"}
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}).to_list()
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# Aggregation
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stats = await Ticket.aggregate([
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{"$group": {
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"_id": "$category",
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"total": {"$sum": 1},
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"avg_confidence": {"$avg": "$confidence_score"}
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}},
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{"$sort": {"total": -1}}
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]).to_list()
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```
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### MongoDB Shell
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```javascript
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// Connect
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mongosh mongodb://admin:password@localhost:27017
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use datacenter_docs
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// Basic queries
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db.tickets.find({ status: "resolved" })
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db.tickets.countDocuments({ category: "network" })
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// Complex queries
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db.tickets.find({
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status: "resolved",
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confidence_score: { $gt: 0.8 },
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created_at: { $gte: new Date("2025-01-01") }
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})
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// Text search
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db.tickets.find({
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$text: { $search: "network connectivity" }
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})
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// Aggregation
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db.tickets.aggregate([
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{ $match: { status: "resolved" } },
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{ $group: {
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_id: "$category",
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count: { $sum: 1 },
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avg_time: { $avg: "$processing_time" }
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}},
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{ $sort: { count: -1 } }
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])
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```
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## 🛠️ Maintenance
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### Backup
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```bash
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# Full backup
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docker-compose exec mongodb mongodump \
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--username admin \
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--password password \
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--authenticationDatabase admin \
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--out /data/backup
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# Restore
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docker-compose exec mongodb mongorestore \
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--username admin \
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--password password \
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--authenticationDatabase admin \
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/data/backup
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```
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### Monitoring
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```bash
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# Database stats
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docker-compose exec mongodb mongosh \
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-u admin -p password --authenticationDatabase admin \
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--eval "db.stats()"
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# Collection stats
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docker-compose exec mongodb mongosh \
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-u admin -p password --authenticationDatabase admin \
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datacenter_docs --eval "db.tickets.stats()"
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```
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### Indexes
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```javascript
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// Check indexes
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db.tickets.getIndexes()
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// Create custom index
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db.tickets.createIndex({ category: 1, status: 1 })
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// Text search index
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db.tickets.createIndex({
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title: "text",
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description: "text",
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resolution: "text"
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})
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```
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## 🔐 Security
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### Authentication
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MongoDB usa autenticazione SCRAM-SHA-256:
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```javascript
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// Create app user
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db.createUser({
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user: "docs_app",
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pwd: "secure_password",
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roles: [
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{ role: "readWrite", db: "datacenter_docs" }
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]
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})
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```
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### Authorization
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Roles disponibili:
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- `read` - Solo lettura
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- `readWrite` - Lettura + scrittura
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- `dbAdmin` - Amministrazione DB
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- `userAdmin` - Gestione utenti
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### TLS/SSL
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```bash
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# Generate certificates
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openssl req -x509 -nodes -days 365 -newkey rsa:2048 \
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-keyout mongodb.key -out mongodb.crt
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# Docker Compose con TLS
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mongodb:
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command: ["--tlsMode=requireTLS", "--tlsCertificateKeyFile=/cert/mongodb.pem"]
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volumes:
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- ./certs/mongodb.pem:/cert/mongodb.pem:ro
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```
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## 📈 Performance
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### Connection Pooling
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```python
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# Default: maxPoolSize=100
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MONGODB_URL=mongodb://user:pass@host:27017/?maxPoolSize=200
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```
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### Read Preference
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```python
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# Replica set - preferisci secondary per letture
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MONGODB_URL=mongodb://user:pass@host:27017/?readPreference=secondaryPreferred
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```
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### Write Concern
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```python
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# Majority (safe, slower)
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MONGODB_URL=mongodb://user:pass@host:27017/?w=majority
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# Faster (less safe)
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MONGODB_URL=mongodb://user:pass@host:27017/?w=1
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```
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## 🚀 Scalability
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### Replica Set (High Availability)
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```yaml
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# docker-compose.yml
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services:
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mongodb-0:
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image: mongo:7.0
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command: ["--replSet", "rs0"]
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mongodb-1:
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image: mongo:7.0
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command: ["--replSet", "rs0"]
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mongodb-2:
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image: mongo:7.0
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command: ["--replSet", "rs0"]
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```
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### Sharding (Horizontal Scaling)
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Per dataset molto grandi (>1TB):
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```javascript
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// Enable sharding
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sh.enableSharding("datacenter_docs")
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// Shard collection
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sh.shardCollection("datacenter_docs.tickets", { category: 1 })
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```
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## 🆚 MongoDB vs PostgreSQL
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| Feature | MongoDB | PostgreSQL |
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|---------|---------|------------|
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| Schema | Flexible | Fixed |
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| Scaling | Horizontal (native) | Vertical (easier) |
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| Queries | JSON-like | SQL |
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| Transactions | Yes (4.0+) | Yes |
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| Performance (reads) | Excellent | Very good |
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| Performance (writes) | Excellent | Good |
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| JSON support | Native | JSONB |
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| Aggregation | Pipeline | SQL + CTEs |
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| Learning curve | Easy | Moderate |
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## 📚 Documentation
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- 📖 [MONGODB_GUIDE.md](./MONGODB_GUIDE.md) - Guida completa MongoDB
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- 📖 [README_COMPLETE_SYSTEM.md](./README_COMPLETE_SYSTEM.md) - Sistema completo
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- 📖 [DEPLOYMENT_GUIDE.md](./DEPLOYMENT_GUIDE.md) - Deploy guide
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## 🆘 Troubleshooting
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### Connection issues
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```bash
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# Test MongoDB connection
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docker-compose exec api python -c "
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from motor.motor_asyncio import AsyncIOMotorClient
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import asyncio
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async def test():
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client = AsyncIOMotorClient('mongodb://admin:password@mongodb:27017')
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await client.admin.command('ping')
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print('MongoDB OK')
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asyncio.run(test())
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"
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```
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### Authentication errors
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```bash
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# Verify credentials
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docker-compose exec mongodb mongosh \
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-u admin -p password --authenticationDatabase admin \
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--eval "db.runCommand({connectionStatus: 1})"
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```
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### Performance issues
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```javascript
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// Check slow queries
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db.setProfilingLevel(2) // Log all queries
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db.system.profile.find().sort({ts:-1}).limit(5)
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// Analyze query
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db.tickets.find({status: "resolved"}).explain("executionStats")
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```
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---
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**MongoDB Version**: 7.0
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**Driver**: Motor 3.3+ (Async)
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**ODM**: Beanie 1.24+
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**Minimum Python**: 3.10
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Reference in New Issue
Block a user