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 # 📚 Automated Infrastructure Documentation System
 Sistema automatizzato per la generazione e mantenimento della documentazione tecnica dell'infrastruttura aziendale tramite LLM locale con validazione umana e pubblicazione GitOps.
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 [![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/)
 [![Kafka](https://img.shields.io/badge/Kafka-3.6+-red.svg)](https://kafka.apache.org/)
 ## 📋 Indice
 - [Overview](#overview)
 - [Architettura](#architettura)
 - [Schema Architetturale](#schema-architetturale)
 - [Schema Tecnico](#schema-tecnico)
 - [Contatti](#contatti)
 ## 🎯 Overview
 Sistema progettato per **automatizzare la creazione e l'aggiornamento della documentazione tecnica** di sistemi infrastrutturali complessi (VMware, Kubernetes, Linux, Cisco, ecc.) utilizzando un Large Language Model locale (Qwen).
 ### Caratteristiche Principali
 - ✅ **Raccolta dati asincrona** da molteplici sistemi infrastrutturali
 - ✅ **Isolamento di sicurezza**: LLM non accede mai ai sistemi live
 - ✅ **Event-driven architecture** con Apache Kafka
 - ✅ **LLM locale on-premise** (Qwen) tramite MCP Server
 - ✅ **Human-in-the-loop validation** con workflow GitOps
 - ✅ **CI/CD automatizzato** per pubblicazione
 ## 🏗️ Architettura
 Il sistema è suddiviso in **3 flussi principali**:
 1. **Raccolta Dati (Background)**: Connettori interrogano periodicamente i sistemi infrastrutturali tramite API e pubblicano i dati su Kafka
 2. **Generazione Documentazione (On-Demand)**: LLM locale (Qwen) genera markdown interrogando Kafka/Redis tramite MCP Server
 3. **Validazione e Pubblicazione (GitOps)**: Review umana su Pull Request e deploy automatico via CI/CD
 > **Principio di Sicurezza**: L'LLM non ha mai accesso diretto ai sistemi infrastrutturali. Tutti i dati passano attraverso Kafka/Redis.
 ---
 ## 📊 Schema Architetturale
 ### Management View
 Schema semplificato per presentazioni executive e management.
 <!-- 
 ===========================================
 INCOLLA QUI LO SCHEMA ARCHITETTURALE 
 (quello per il management, più semplice)
 ===========================================
 -->
 ```mermaid
 graph TB
    %% Styling
    classDef infrastructure fill:#e1f5ff,stroke:#01579b,stroke-width:3px,color:#333
    classDef kafka fill:#fff3e0,stroke:#e65100,stroke-width:3px,color:#333
    classDef cache fill:#f3e5f5,stroke:#4a148c,stroke-width:3px,color:#333
    classDef llm fill:#e8f5e9,stroke:#1b5e20,stroke-width:3px,color:#333
    classDef git fill:#fce4ec,stroke:#880e4f,stroke-width:3px,color:#333
    classDef human fill:#fff9c4,stroke:#f57f17,stroke-width:3px,color:#333
    %% ========================================
    %% FLUSSO 1: RACCOLTA DATI (Background)
    %% ========================================
    INFRA[("🏢 SISTEMI<br/>INFRASTRUTTURALI<br/><br/>VMware | K8s | Linux | Cisco")]:::infrastructure
    CONN["🔌 CONNETTORI<br/>Polling Automatico"]:::infrastructure
    KAFKA[("📨 APACHE KAFKA<br/>Message Broker<br/>+ Persistenza")]:::kafka
    CONSUMER["⚙️ KAFKA CONSUMER<br/>Processor Service"]:::kafka
    REDIS[("💾 REDIS CACHE<br/>(Opzionale)<br/>Performance Layer")]:::cache
    INFRA -->|"API Polling<br/>Continuo"| CONN
    CONN -->|"Publish<br/>Eventi"| KAFKA
    KAFKA -->|"Consume<br/>Stream"| CONSUMER
    CONSUMER -.->|"Update<br/>Opzionale"| REDIS
    %% ========================================
    %% FLUSSO 2: GENERAZIONE DOCUMENTAZIONE
    %% ========================================
    USER["👤 UTENTE<br/>Richiesta Doc"]:::human
    LLM["🤖 LLM ENGINE<br/>Claude / GPT"]:::llm
    MCP["🔧 MCP SERVER<br/>API Control Platform"]:::llm
    DOC["📄 DOCUMENTO<br/>Markdown Generato"]:::llm
    USER -->|"1. Prompt"| LLM
    LLM -->|"2. Tool Call"| MCP
    MCP -->|"3a. Query"| KAFKA
    MCP -.->|"3b. Query<br/>Fast"| REDIS
    KAFKA -->|"4a. Dati"| MCP
    REDIS -.->|"4b. Dati"| MCP
    MCP -->|"5. Context"| LLM
    LLM -->|"6. Genera"| DOC
    %% ========================================
    %% FLUSSO 3: VALIDAZIONE E PUBBLICAZIONE
    %% ========================================
    GIT["📦 GITLAB<br/>Repository"]:::git
    PR["🔀 PULL REQUEST<br/>Review Automatica"]:::git
    TECH["👨‍💼 TEAM TECNICO<br/>Validazione Umana"]:::human
    PIPELINE["⚡ CI/CD PIPELINE<br/>GitLab Runner"]:::git
    MKDOCS["📚 MKDOCS<br/>Static Site Generator"]:::git
    WEB["🌐 DOCUMENTAZIONE<br/>GitLab Pages<br/>(Pubblicata)"]:::git
    DOC -->|"Push +<br/>Branch"| GIT
    GIT -->|"Crea"| PR
    PR -->|"Notifica"| TECH
    TECH -->|"Approva +<br/>Merge"| GIT
    GIT -->|"Trigger"| PIPELINE
    PIPELINE -->|"Build"| MKDOCS
    MKDOCS -->|"Deploy"| WEB
    %% ========================================
    %% ANNOTAZIONI SICUREZZA
    %% ========================================
    SECURITY["🔒 SICUREZZA<br/>LLM isolato dai sistemi live"]:::human
    PERF["⚡ PERFORMANCE<br/>Cache Redis opzionale"]:::cache
    LLM -.->|"NESSUN<br/>ACCESSO"| INFRA
    SECURITY -.-> LLM
    PERF -.-> REDIS
 ```
 ---
 ## 🔧 Schema Tecnico
 ### Implementation View
 Schema dettagliato per il team tecnico con specifiche implementative.
 <!-- 
 ===========================================
 INCOLLA QUI LO SCHEMA TECNICO DETTAGLIATO
 (quello con tutti i dettagli per gli sviluppatori)
 ===========================================
 -->
 ```mermaid
 graph TB
    %% Styling tecnico
    classDef infra fill:#e1f5ff,stroke:#01579b,stroke-width:2px,color:#333,font-size:11px
    classDef connector fill:#e3f2fd,stroke:#1565c0,stroke-width:2px,color:#333,font-size:11px
    classDef kafka fill:#fff3e0,stroke:#e65100,stroke-width:2px,color:#333,font-size:11px
    classDef cache fill:#f3e5f5,stroke:#4a148c,stroke-width:2px,color:#333,font-size:11px
    classDef llm fill:#e8f5e9,stroke:#1b5e20,stroke-width:2px,color:#333,font-size:11px
    classDef git fill:#fce4ec,stroke:#880e4f,stroke-width:2px,color:#333,font-size:11px
    classDef monitor fill:#fff8e1,stroke:#f57f17,stroke-width:2px,color:#333,font-size:11px
    %% =====================================
    %% LAYER 1: SISTEMI SORGENTE
    %% =====================================
    subgraph SOURCES["🏢 INFRASTRUCTURE SOURCES"]
        VCENTER["VMware vCenter<br/>API: vSphere REST 7.0+<br/>Port: 443/HTTPS<br/>Auth: API Token"]:::infra
        K8S_API["Kubernetes API<br/>API: v1.28+<br/>Port: 6443/HTTPS<br/>Auth: ServiceAccount + RBAC"]:::infra
        LINUX["Linux Servers<br/>Protocol: SSH/Ansible<br/>Port: 22<br/>Auth: SSH Keys"]:::infra
        CISCO["Cisco Devices<br/>Protocol: NETCONF/RESTCONF<br/>Port: 830/443<br/>Auth: AAA"]:::infra
    end
    %% =====================================
    %% LAYER 2: CONNETTORI
    %% =====================================
    subgraph CONNECTORS["🔌 DATA COLLECTORS (Python/Go)"]
        CONN_VM["VMware Collector<br/>Lang: Python 3.11<br/>Lib: pyvmomi<br/>Schedule: */15 * * * *<br/>Output: JSON"]:::connector
        CONN_K8S["K8s Collector<br/>Lang: Python 3.11<br/>Lib: kubernetes-client<br/>Schedule: */5 * * * *<br/>Resources: pods,svc,ing,deploy"]:::connector
        CONN_LNX["Linux Collector<br/>Lang: Python 3.11<br/>Lib: paramiko/ansible<br/>Schedule: */30 * * * *<br/>Data: sysinfo,packages,services"]:::connector
        CONN_CSC["Cisco Collector<br/>Lang: Python 3.11<br/>Lib: ncclient<br/>Schedule: */30 * * * *<br/>Data: interfaces,routing,vlans"]:::connector
    end
    VCENTER -->|"GET /api/vcenter/vm"| CONN_VM
    K8S_API -->|"kubectl proxy<br/>API calls"| CONN_K8S
    LINUX -->|"SSH batch<br/>commands"| CONN_LNX
    CISCO -->|"NETCONF<br/>get-config"| CONN_CSC
    %% =====================================
    %% LAYER 3: MESSAGE BROKER
    %% =====================================
    subgraph MESSAGING["📨 KAFKA CLUSTER (3 brokers)"]
        KAFKA_TOPICS["Kafka Topics:<br/>• vmware.inventory (P:6, R:3)<br/>• k8s.resources (P:12, R:3)<br/>• linux.systems (P:3, R:3)<br/>• cisco.network (P:3, R:3)<br/>Retention: 7 days<br/>Format: JSON + Schema Registry"]:::kafka
        SCHEMA["Schema Registry<br/>Avro Schemas<br/>Versioning enabled<br/>Port: 8081"]:::kafka
    end
    CONN_VM -->|"Producer<br/>Batch 100 msg"| KAFKA_TOPICS
    CONN_K8S -->|"Producer<br/>Batch 100 msg"| KAFKA_TOPICS
    CONN_LNX -->|"Producer<br/>Batch 50 msg"| KAFKA_TOPICS
    CONN_CSC -->|"Producer<br/>Batch 50 msg"| KAFKA_TOPICS
    KAFKA_TOPICS <--> SCHEMA
    %% =====================================
    %% LAYER 4: PROCESSING & CACHE
    %% =====================================
    subgraph PROCESSING["⚙️ STREAM PROCESSING"]
        CONSUMER_GRP["Kafka Consumer Group<br/>Group ID: doc-consumers<br/>Lang: Python 3.11<br/>Lib: kafka-python<br/>Workers: 6<br/>Commit: auto (5s)"]:::kafka
        PROCESSOR["Data Processor<br/>• Validation<br/>• Transformation<br/>• Enrichment<br/>• Deduplication"]:::kafka
    end
    KAFKA_TOPICS -->|"Subscribe<br/>offset management"| CONSUMER_GRP
    CONSUMER_GRP --> PROCESSOR
    subgraph STORAGE["💾 CACHE LAYER (Optional)"]
        REDIS_CLUSTER["Redis Cluster<br/>Mode: Cluster (6 nodes)<br/>Port: 6379<br/>Persistence: RDB + AOF<br/>Memory: 64GB<br/>Eviction: allkeys-lru"]:::cache
        REDIS_KEYS["Key Structure:<br/>• vmware:vcenter-id:vms<br/>• k8s:cluster:namespace:resource<br/>• linux:hostname:info<br/>• cisco:device-id:config<br/>TTL: 1-24h based on type"]:::cache
    end
    PROCESSOR -.->|"SET/HSET<br/>Pipeline batch"| REDIS_CLUSTER
    REDIS_CLUSTER --> REDIS_KEYS
    %% =====================================
    %% LAYER 5: LLM & MCP
    %% =====================================
    subgraph LLM_LAYER["🤖 AI GENERATION LAYER"]
        LLM_ENGINE["LLM Engine<br/>Model: Claude Sonnet 4 / GPT-4<br/>API: Anthropic/OpenAI<br/>Temp: 0.3<br/>Max Tokens: 4096<br/>Timeout: 120s"]:::llm
        MCP_SERVER["MCP Server<br/>Lang: TypeScript/Node.js<br/>Port: 3000<br/>Protocol: JSON-RPC 2.0<br/>Auth: JWT tokens"]:::llm
        MCP_TOOLS["MCP Tools:<br/>• getVMwareInventory(vcenter)<br/>• getK8sResources(cluster,ns,type)<br/>• getLinuxSystemInfo(hostname)<br/>• getCiscoConfig(device,section)<br/>• queryTimeRange(start,end)<br/>Return: JSON + Metadata"]:::llm
    end
    LLM_ENGINE <-->|"Tool calls<br/>JSON-RPC"| MCP_SERVER
    MCP_SERVER --> MCP_TOOLS
    MCP_TOOLS -->|"1. Query Kafka Consumer API<br/>GET /api/v1/data"| CONSUMER_GRP
    MCP_TOOLS -.->|"2. Fallback Redis<br/>MGET/HGETALL"| REDIS_CLUSTER
    CONSUMER_GRP -->|"JSON Response<br/>+ Timestamps"| MCP_TOOLS
    REDIS_CLUSTER -.->|"Cached JSON<br/>Fast response"| MCP_TOOLS
    MCP_TOOLS -->|"Structured Data<br/>+ Context"| LLM_ENGINE
    subgraph OUTPUT["📝 DOCUMENT GENERATION"]
        TEMPLATE["Template Engine<br/>Format: Jinja2<br/>Templates: markdown/*.j2<br/>Variables: from LLM"]:::llm
        MARKDOWN["Markdown Output<br/>Format: CommonMark<br/>Metadata: YAML frontmatter<br/>Assets: diagrams in mermaid"]:::llm
        VALIDATOR["Doc Validator<br/>• Markdown linting<br/>• Link checking<br/>• Schema validation"]:::llm
    end
    LLM_ENGINE --> TEMPLATE
    TEMPLATE --> MARKDOWN
    MARKDOWN --> VALIDATOR
    %% =====================================
    %% LAYER 6: GITOPS
    %% =====================================
    subgraph GITOPS["🔄 GITOPS WORKFLOW"]
        GIT_REPO["GitLab Repository<br/>URL: gitlab.com/docs/infra<br/>Branch strategy: main + feature/*<br/>Protected: main (require approval)"]:::git
        GIT_API["GitLab API<br/>API: v4<br/>Auth: Project Access Token<br/>Permissions: api, write_repo"]:::git
        PR_AUTO["Automated PR Creator<br/>Lang: Python 3.11<br/>Lib: python-gitlab<br/>Template: .gitlab/merge_request.md"]:::git
    end
    VALIDATOR -->|"git add/commit/push"| GIT_REPO
    GIT_REPO <--> GIT_API
    GIT_API --> PR_AUTO
    REVIEWER["👨‍💼 Technical Reviewer<br/>Role: Maintainer/Owner<br/>Review: diff + validation<br/>Approve: required (min 1)"]:::monitor
    PR_AUTO -->|"Notification<br/>Email + Slack"| REVIEWER
    REVIEWER -->|"Merge to main"| GIT_REPO
    %% =====================================
    %% LAYER 7: CI/CD & PUBLISH
    %% =====================================
    subgraph CICD["⚡ CI/CD PIPELINE"]
        GITLAB_CI["GitLab CI/CD<br/>Runner: docker<br/>Image: python:3.11-alpine<br/>Stages: build, test, deploy"]:::git
        PIPELINE_JOBS["Pipeline Jobs:<br/>1. lint (markdownlint-cli)<br/>2. build (mkdocs build)<br/>3. test (link-checker)<br/>4. deploy (rsync/s3)"]:::git
        MKDOCS_CFG["MkDocs Config<br/>Theme: material<br/>Plugins: search, tags, mermaid<br/>Extensions: admonition, codehilite"]:::git
    end
    GIT_REPO -->|"on: push to main<br/>Webhook trigger"| GITLAB_CI
    GITLAB_CI --> PIPELINE_JOBS
    PIPELINE_JOBS --> MKDOCS_CFG
    subgraph PUBLISH["🌐 PUBLICATION"]
        STATIC_SITE["Static Site<br/>Generator: MkDocs<br/>Output: HTML/CSS/JS<br/>Assets: optimized images"]:::git
        CDN["GitLab Pages / S3 + CloudFront<br/>URL: docs.company.com<br/>SSL: Let's Encrypt<br/>Cache: 1h"]:::git
        SEARCH["Search Index<br/>Engine: Algolia/Meilisearch<br/>Update: on publish<br/>API: REST"]:::git
    end
    MKDOCS_CFG -->|"mkdocs build<br/>--strict"| STATIC_SITE
    STATIC_SITE --> CDN
    STATIC_SITE --> SEARCH
    %% =====================================
    %% LAYER 8: MONITORING & OBSERVABILITY
    %% =====================================
    subgraph OBSERVABILITY["📊 MONITORING & LOGGING"]
        PROMETHEUS["Prometheus<br/>Metrics: collector lag, cache hit/miss<br/>Scrape: 30s<br/>Retention: 15d"]:::monitor
        GRAFANA["Grafana Dashboards<br/>• Kafka metrics<br/>• Redis performance<br/>• LLM response times<br/>• Pipeline success rate"]:::monitor
        ELK["ELK Stack<br/>Logs: all components<br/>Index: daily rotation<br/>Retention: 30d"]:::monitor
        ALERTS["Alerting<br/>• Connector failures<br/>• Kafka lag > 10k<br/>• Redis OOM<br/>• Pipeline failures<br/>Channel: Slack + PagerDuty"]:::monitor
    end
    CONN_VM -.->|"metrics"| PROMETHEUS
    CONN_K8S -.->|"metrics"| PROMETHEUS
    KAFKA_TOPICS -.->|"metrics"| PROMETHEUS
    REDIS_CLUSTER -.->|"metrics"| PROMETHEUS
    MCP_SERVER -.->|"metrics"| PROMETHEUS
    GITLAB_CI -.->|"metrics"| PROMETHEUS
    PROMETHEUS --> GRAFANA
    CONN_VM -.->|"logs"| ELK
    CONSUMER_GRP -.->|"logs"| ELK
    MCP_SERVER -.->|"logs"| ELK
    GITLAB_CI -.->|"logs"| ELK
    GRAFANA --> ALERTS
    %% =====================================
    %% SECURITY ANNOTATIONS
    %% =====================================
    SEC1["🔒 SECURITY:<br/>• All APIs use TLS 1.3<br/>• Secrets in Vault/K8s Secrets<br/>• Network: private VPC<br/>• LLM has NO direct access"]:::monitor
    SEC2["🔐 AUTHENTICATION:<br/>• API Tokens rotated 90d<br/>• RBAC enforced<br/>• Audit logs enabled<br/>• MFA required for Git"]:::monitor
    SEC1 -.-> MCP_SERVER
    SEC2 -.-> GIT_REPO
 ```
 ---
 ## 📧 Contatti
 - **Team**: Infrastructure Documentation Team
 - **Email**: infra-docs@company.com
 - **GitLab**: https://gitlab.com/company/infra-docs-automation
 ---
 **Versione**: 1.0.0  
 **Ultimo aggiornamento**: 2025-10-28