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Architecture Overview

Juro v2.0.0 is built on a modern, enterprise-grade architecture designed for scalability, performance, and comprehensive compliance scanning across multiple regulations and standards.

🏗️ System Architecture​

High-Level Architecture​

┌─────────────────────────────────────────────────────────────────┐
│                        Juro v2.0.0 Platform                    │
├─────────────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────┐ │
│  │   VS Code   │  │  GitHub     │  │    CLI      │  │   AI    │ │
│  │ Extension   │  │  Actions    │  │   Tools     │  │ Agents  │ │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────┘ │
├─────────────────────────────────────────────────────────────────┤
│                    Integration Layer (MCP)                      │
├─────────────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────┐ │
│  │   GitHub    │  │ Compliance  │  │ Performance │  │   Auto  │ │
│  │  Actions    │  │   Engine    │  │ Optimization│  │Detection│ │
│  │  Service    │  │             │  │             │  │ Engine  │ │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────┘ │
├─────────────────────────────────────────────────────────────────┤
│                    Core Services Layer                          │
├─────────────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────┐ │
│  │   MCP       │  │   Service   │  │   Cache     │  │  Rule   │ │
│  │  Server     │  │  Container  │  │  Manager    │  │ Manager │ │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────┘ │
├─────────────────────────────────────────────────────────────────┤
│                    Data & Storage Layer                         │
├─────────────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────┐ │
│  │   Rule      │  │   Cache     │  │   Logs      │  │  Config │ │
│  │   Packs     │  │  Storage    │  │  Storage    │  │ Storage │ │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────┘ │
└─────────────────────────────────────────────────────────────────┘

🔧 Core Components​

MCP Server​

  • Protocol: Model Context Protocol (MCP) implementation
  • Ports: HTTP API (8080), MCP TCP (3000)
  • Features: Tool registration, request handling, response formatting
  • Scalability: Horizontal scaling with load balancing

Service Container​

  • Dependency Injection: IoC container for service management
  • Service Registration: Automatic service discovery and registration
  • Lifecycle Management: Service initialization, startup, and shutdown
  • Configuration: Centralized configuration management

Compliance Engine​

  • Rule Processing: Multi-regulation rule processing
  • Pattern Matching: Advanced regex and context-aware matching
  • Violation Detection: Real-time violation identification
  • Scoring System: Algorithm-based compliance scoring

🚀 Performance Architecture​

CacheManager​

class CacheManager {
  // Intelligent caching system
  async cacheRulePack(regulation: string, rules: Rule[]): Promise<void>
  async cacheScanResult(filePath: string, result: ScanResult): Promise<void>
  async getCachedResult(filePath: string): Promise<ScanResult | null>
  async invalidateCache(pattern: string): Promise<void>
}

WorkerPool​

class WorkerPool {
  // Parallel processing architecture
  async createWorkers(count: number): Promise<void>
  async distributeTask(task: ScanTask): Promise<ScanResult>
  async scaleWorkers(targetCount: number): Promise<void>
  async getWorkerStats(): Promise<WorkerStats[]>
}

MemoryManager​

class MemoryManager {
  // Advanced memory management
  async processLargeFile(filePath: string, chunkSize: number): Promise<ScanResult>
  async cleanupMemory(): Promise<void>
  async monitorMemoryUsage(): Promise<MemoryStats>
  async allocateMemory(size: number): Promise<Buffer>
}

🔌 Integration Services​

GitHub Actions Service​

class GitHubActionsService {
  // Complete GitHub Actions integration
  async addWorkflow(repoPath: string, config: WorkflowConfig): Promise<WorkflowResult>
  async createPRWorkflow(repoPath: string, config: PRConfig): Promise<WorkflowResult>
  async runPRComplianceCheck(prData: PRData): Promise<ComplianceResult>
  async generateComplianceReport(results: ScanResult[]): Promise<Report>
  async sendComplianceNotifications(data: ComplianceData): Promise<NotificationResult>
}

VS Code Extension Service​

class VSCodeExtensionService {
  // Real-time IDE integration
  async scanFile(filePath: string): Promise<ScanResult>
  async scanWorkspace(workspacePath: string): Promise<ScanResult[]>
  async getComplianceScore(filePath: string): Promise<ComplianceScore>
  async getViolations(filePath: string): Promise<Violation[]>
}

Auto-Detection Engine​

class AutoDetectionEngine {
  // Intelligent project detection
  async detectProjectType(projectPath: string): Promise<ProjectType>
  async mapRegulations(projectType: ProjectType): Promise<Regulation[]>
  async generateConfiguration(projectType: ProjectType): Promise<Configuration>
  async downloadRulePacks(regulations: Regulation[]): Promise<RulePack[]>
}

📊 Data Flow Architecture​

Scanning Workflow​

1. Request Received (MCP/HTTP)
   ↓
2. Service Container Resolution
   ↓
3. Auto-Detection Engine (Project Type + Regulations)
   ↓
4. Rule Pack Loading (Cache Check)
   ↓
5. Worker Pool Task Distribution
   ↓
6. Parallel File Processing
   ↓
7. Compliance Engine Analysis
   ↓
8. Result Aggregation
   ↓
9. Cache Storage
   ↓
10. Response Formatting
    ↓
11. Client Response

Performance Optimization Flow​

1. File Change Detection
   ↓
2. Cache Lookup
   ↓
3. Incremental Processing (if cached)
   ↓
4. Worker Pool Distribution
   ↓
5. Chunked File Processing
   ↓
6. Memory Management
   ↓
7. Result Caching
   ↓
8. Performance Metrics Collection

🔒 Security Architecture​

Authentication & Authorization​

  • API Key Management: Secure API key validation
  • Token-Based Auth: JWT tokens for service communication
  • Role-Based Access: Granular permission system
  • Audit Logging: Comprehensive security event logging

Data Protection​

  • Encryption at Rest: All cached data encrypted
  • Encryption in Transit: TLS 1.3 for all communications
  • Secure Storage: Encrypted rule packs and configurations
  • Data Anonymization: PII protection in logs and metrics

📈 Scalability Architecture​

Horizontal Scaling​

  • Load Balancing: Multiple MCP server instances
  • Service Discovery: Automatic service registration
  • Health Checks: Continuous service monitoring
  • Auto-Scaling: Dynamic resource allocation

Vertical Scaling​

  • Worker Pool Scaling: 1-8 workers based on load
  • Memory Optimization: Dynamic memory allocation
  • CPU Optimization: Multi-core processing
  • I/O Optimization: Async file operations

🔄 Deployment Architecture​

Container Deployment​

# Docker Compose Example
version: '3.8'
services:
  juro-mcp-server:
    image: juro/mcp-server:v2.0.0
    ports:
      - "3000:3000"
      - "8080:8080"
    environment:
      - NODE_ENV=production
      - WORKER_COUNT=4
      - CACHE_ENABLED=true
    volumes:
      - ./config:/app/config
      - ./cache:/app/cache

Kubernetes Deployment​

# Kubernetes Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: juro-mcp-server
spec:
  replicas: 3
  selector:
    matchLabels:
      app: juro-mcp-server
  template:
    metadata:
      labels:
        app: juro-mcp-server
    spec:
      containers:
      - name: juro-mcp-server
        image: juro/mcp-server:v2.0.0
        ports:
        - containerPort: 3000
        - containerPort: 8080
        resources:
          requests:
            memory: "512Mi"
            cpu: "500m"
          limits:
            memory: "2Gi"
            cpu: "2000m"

📊 Monitoring & Observability​

Metrics Collection​

  • Performance Metrics: Scan duration, throughput, resource usage
  • Business Metrics: Compliance scores, violation trends
  • System Metrics: CPU, memory, disk, network usage
  • Custom Metrics: User-defined performance indicators

Logging Architecture​

  • Structured Logging: JSON-formatted logs with context
  • Log Levels: DEBUG, INFO, WARN, ERROR, FATAL
  • Log Aggregation: Centralized log collection and analysis
  • Log Retention: Configurable log retention policies

Health Checks​

  • Liveness Probes: Service availability checks
  • Readiness Probes: Service readiness for traffic
  • Dependency Checks: External service availability
  • Performance Checks: Response time and throughput validation

🔧 Configuration Management​

Environment Configuration​

{
  "mcp": {
    "port": 3000,
    "host": "0.0.0.0",
    "protocol": "tcp"
  },
  "performance": {
    "workerPool": {
      "minWorkers": 1,
      "maxWorkers": 8,
      "defaultWorkers": 4
    },
    "caching": {
      "enabled": true,
      "ttl": 3600,
      "maxSize": "1GB"
    }
  },
  "compliance": {
    "regulations": ["GDPR", "DORA"],
    "severityThreshold": "MEDIUM",
    "maxFileSize": "50MB"
  }
}

Dynamic Configuration​

  • Hot Reloading: Configuration changes without restart
  • Environment-Specific: Different configs for dev/staging/prod
  • Secret Management: Secure handling of sensitive configuration
  • Validation: Configuration schema validation

🚀 Future Architecture Plans​

Phase 3: Advanced Integrations​

  • Multi-Cloud Support: AWS, Azure, GCP integrations
  • Enterprise SSO: SAML, OIDC integration
  • Advanced Analytics: ML-powered compliance insights
  • Custom Rule Engine: User-defined rule creation

Phase 4: AI Enhancement​

  • Natural Language Processing: Advanced AI queries
  • Predictive Compliance: ML-based violation prediction
  • Automated Fixes: AI-generated code fixes
  • Intelligent Recommendations: Context-aware suggestions

Ready to understand Juro's architecture? Explore the technical details or get started with implementation!