Architecture¶

Welcome to the Studio Platform Architecture documentation! This comprehensive guide covers the technical architecture, system design, and infrastructure patterns that power the Studio Platform.

🏗️ Architecture Overview¶

Platform Architecture¶

Studio Platform is built on a modern microservices architecture designed for scalability, resilience, and maintainability. The system leverages cloud-native technologies and follows industry best practices for enterprise applications.

graph TD
    A[Client Layer] --> B[API Gateway]
    B --> C[Frontend Service]
    B --> D[Backend Service]
    B --> E[AI Service]
    B --> F[Document Service]

    D --> G[PostgreSQL]
    D --> H[Neo4j]
    D --> I[Redis]

    E --> J[Vector Store]
    E --> K[AI Models]

    F --> L[MinIO Storage]
    F --> M[Processing Queue]

    N[Identity Service] --> B
    O[Policy Service] --> B
    P[Monitoring Service] --> Q[Prometheus]
    P --> R[Grafana]

    S[External Services] --> B
    T[FleetDM] --> G
    U[Prowler] --> G
    V[n8n] --> M

Architecture Principles¶

Core Principles:

• Microservices - Service-oriented architecture
• Cloud-Native - Designed for cloud deployment
• API-First - API-driven design
• Event-Driven - Event-based communication
• Security-First - Security by design
• Scalability - Horizontal scalability
• Resilience - Fault tolerance and recovery

Design Patterns:

• CQRS - Command Query Responsibility Segregation
• Event Sourcing - Event-driven state management
• Saga Pattern - Distributed transaction management
• Circuit Breaker - Fault tolerance pattern
• API Gateway - Single entry point
• Service Mesh - Service communication

Technology Stack¶

Frontend:

• Framework - Next.js 13+ with App Router
• Language - TypeScript
• Styling - Tailwind CSS
• UI Components - Radix UI
• State Management - React Query, Zustand
• Forms - React Hook Form
• Charts - Recharts, D3.js

Backend:

• Runtime - Node.js 18+
• Framework - Express.js
• Language - TypeScript
• Database - PostgreSQL, Neo4j, Redis
• ORM - Prisma
• Authentication - Ory Kratos
• Authorization - Open Policy Agent

Infrastructure:

• Containerization - Docker
• Orchestration - Docker Compose, Kubernetes
• API Gateway - Kong
• Monitoring - Prometheus, Grafana
• Logging - Loki, Fluent Bit
• CI/CD - GitHub Actions

📚 Architecture Documentation Structure¶

System Architecture¶

• System Overview - High-level system architecture
• Microservices - Microservices design and patterns
• Data Flow - Data flow and processing patterns
• Security Model - Security architecture and controls
• Deployment - Deployment strategies and patterns

Component Architecture¶

• Frontend Architecture - Frontend application architecture
• Backend Architecture - Backend service architecture
• Database Architecture - Database design and relationships
• Integration Architecture - Third-party integration patterns
• Monitoring Architecture - Monitoring and observability

Infrastructure Architecture¶

• Container Architecture - Docker and Kubernetes architecture
• Network Architecture - Network design and security
• Storage Architecture - Storage systems and data management
• Security Architecture - Security infrastructure and controls
• Scalability Architecture - Scaling patterns and strategies

🎯 Architecture Goals¶

Functional Requirements¶

Core Functionality:

• Compliance Management - Comprehensive compliance tracking
• Evidence Management - Document and evidence handling
• Risk Assessment - Risk analysis and management
• AI Assistant - Intelligent compliance assistance
• Reporting - Comprehensive reporting and analytics

User Experience:

• Intuitive Interface - User-friendly design
• Responsive Design - Mobile-friendly interface
• Performance - Fast and responsive application
• Accessibility - WCAG compliant interface
• Internationalization - Multi-language support

Non-Functional Requirements¶

Performance:

• Response Time - <2 seconds for most operations
• Throughput - 1000+ concurrent users
• Availability - 99.9% uptime
• Scalability - Horizontal scaling support
• Latency - <100ms for API calls

Security:

• Authentication - Multi-factor authentication
• Authorization - Role-based access control
• Data Protection - Encryption at rest and in transit
• Audit Trail - Comprehensive audit logging
• Compliance - SOC 2, ISO 27001, GDPR compliance

Reliability:

• Fault Tolerance - Graceful degradation
• Recovery - Fast recovery from failures
• Backup - Regular backup and recovery
• Disaster Recovery - Comprehensive disaster recovery
• Monitoring - Real-time monitoring and alerting

🔧 Technical Architecture¶

Service Architecture¶

Frontend Service¶

Frontend Architecture:

graph TD
    A[User Browser] --> B[Next.js App]
    B --> C[API Gateway]
    C --> D[Backend Services]

    B --> E[Client State Management]
    B --> F[UI Components]
    B --> G[Routing]
    B --> H[Authentication]

    E --> I[React Query]
    E --> J[Zustand]

    F --> K[Radix UI]
    F --> L[Tailwind CSS]

    G --> M[App Router]
    G --> N[Middleware]

    H --> O[OAuth 2.0]
    H --> P[JWT Tokens]

Frontend Components: - Pages - Route-based page components - Components - Reusable UI components - Hooks - Custom React hooks - Services - API integration services - Utils - Utility functions and helpers - Types - TypeScript type definitions

Backend Service¶

Backend Architecture:

graph TD
    A[API Gateway] --> B[Backend Service]
    B --> C[Controllers]
    B --> D[Services]
    B --> E[Repositories]
    B --> F[Models]

    C --> G[User Controller]
    C --> H[Project Controller]
    C --> I[Evidence Controller]
    C --> J[Compliance Controller]

    D --> K[User Service]
    D --> L[Project Service]
    D --> M[Evidence Service]
    D --> N[Compliance Service]

    E --> O[User Repository]
    E --> P[Project Repository]
    E --> Q[Evidence Repository]
    E --> R[Compliance Repository]

    F --> S[User Model]
    F --> T[Project Model]
    F --> U[Evidence Model]
    F --> V[Compliance Model]

Backend Components: - Controllers - HTTP request handlers - Services - Business logic implementation - Repositories - Data access layer - Models - Data models and schemas - Middleware - Request/response processing - Utils - Utility functions and helpers

AI Service¶

AI Architecture:

graph TD
    A[API Gateway] --> B[AI Service]
    B --> C[AI Controller]
    B --> D[AI Services]
    B --> E[AI Models]
    B --> F[Vector Store]

    C --> G[Chat Controller]
    C --> H[Analysis Controller]
    C --> I[Generation Controller]

    D --> J[Chat Service]
    D --> K[Analysis Service]
    D --> L[Generation Service]

    E --> M[Google Gemini]
    E --> N[OpenAI]
    E --> O[Custom Models]

    F --> P[ChromaDB]
    F --> Q[Pinecone]
    F --> R[Weaviate]

AI Components: - Controllers - AI request handlers - Services - AI logic implementation - Models - AI model interfaces - Vector Store - Vector database integration - Embeddings - Text embedding generation - Prompts - Prompt management

Data Architecture¶

Database Architecture¶

Database Design:

graph TD
    A[Application Layer] --> B[Data Access Layer]
    B --> C[PostgreSQL]
    B --> D[Neo4j]
    B --> E[Redis]
    B --> F[MinIO]
    B --> G[ChromaDB]

    C --> H[Relational Data]
    C --> I[Users]
    C --> J[Projects]
    C --> K[Evidence]

    D --> L[Graph Data]
    D --> M[Relationships]
    D --> N[Networks]

    E --> O[Cache]
    E --> P[Queue]
    E --> Q[Session]

    F --> R[Files]
    F --> S[Documents]
    F --> T[Media]

    G --> U[Embeddings]
    G --> V[Vectors]
    G --> W[Similarity Search]

Database Responsibilities: - PostgreSQL - Primary relational database - Neo4j - Graph database for relationships - Redis - Cache and message queue - MinIO - Object storage for files - ChromaDB - Vector database for AI

Data Flow Architecture¶

Data Flow Patterns:

graph TD
    A[Client Request] --> B[API Gateway]
    B --> C[Backend Service]
    C --> D[Cache Layer]
    D --> E[Database Layer]

    D --> F[PostgreSQL]
    D --> G[Neo4j]
    D --> H[Redis]

    E --> I[Response Processing]
    I --> J[Response Cache]
    J --> K[Client Response]

    L[Background Jobs] --> M[Queue]
    M --> N[Worker Services]
    N --> O[Database Updates]

    P[Events] --> Q[Event Bus]
    Q --> R[Event Handlers]
    R --> S[Data Updates]

🔒 Security Architecture¶

Security Model¶

Security Layers¶

Security Architecture:

graph TD
    A[Network Security] --> B[Application Security]
    B --> C[Data Security]
    C --> D[Identity Security]

    A --> E[Firewall]
    A --> F[Load Balancer]
    A --> G[WAF]

    B --> H[API Gateway]
    B --> I[Rate Limiting]
    B --> J[Input Validation]

    C --> K[Encryption]
    C --> L[Access Control]
    C --> M[Audit Logging]

    D --> N[Authentication]
    D --> O[Authorization]
    D --> P[Session Management]

Security Components: - Network Security - Firewall, WAF, DDoS protection - Application Security - API gateway, rate limiting, input validation - Data Security - Encryption, access control, audit logging - Identity Security - Authentication, authorization, session management

Authentication & Authorization¶

Authentication Flow¶

OAuth 2.0 Flow:

sequenceDiagram
    participant U as User
    participant C as Client
    participant A as Auth Server
    participant R as Resource Server

    U->>C: Request Resource
    C->>A: Authorization Request
    A->>U: Redirect to Login
    U->>A: Login with Credentials
    A->>U: Authorization Code
    U->>C: Authorization Code
    C->>A: Token Request
    A->>C: Access Token
    C->>R: API Request with Token
    R->>C: Resource Data
    C->>U: Resource Data

Authorization Model: - RBAC - Role-based access control - ABAC - Attribute-based access control - Policy Engine - Open Policy Agent - Fine-grained Permissions - Resource-level permissions - Dynamic Authorization - Context-aware authorization

🚀 Deployment Architecture¶

Deployment Patterns¶

Container Architecture¶

Docker Architecture:

graph TD
    A[Development] --> B[Docker Compose]
    A --> C[Local Services]

    D[Staging] --> E[Docker Swarm]
    D --> F[Staging Services]

    G[Production] --> H[Kubernetes]
    G --> I[Production Services]

    J[Monitoring] --> K[Prometheus]
    J --> L[Grafana]
    J --> M[AlertManager]

    N[Logging] --> O[Loki]
    N --> P[Fluent Bit]
    N --> Q[Log Aggregation]

Deployment Environments: - Development - Local development with Docker Compose - Staging - Pre-production with Docker Swarm - Production - Production with Kubernetes - Monitoring - Centralized monitoring and logging

Infrastructure Architecture¶

Cloud Infrastructure:

graph TD
    A[Load Balancer] --> B[API Gateway]
    B --> C[Frontend Services]
    B --> D[Backend Services]
    B --> E[AI Services]

    C --> F[CDN]
    D --> G[Database Cluster]
    E --> H[AI Model Services]

    I[Security] --> J[Firewall]
    I --> K[WAF]
    I --> L[DDoS Protection]

    M[Monitoring] --> N[Prometheus]
    M --> O[Grafana]
    M --> P[AlertManager]

    Q[Backup] --> R[Backup Storage]
    Q --> S[Disaster Recovery]

📊 Monitoring Architecture¶

Observability Stack¶

Monitoring Components¶

Monitoring Architecture:

graph TD
    A[Applications] --> B[Metrics Collection]
    A --> C[Log Collection]
    A --> D[Trace Collection]

    B --> E[Prometheus]
    C --> F[Loki]
    D --> G[Jaeger]

    E --> H[Grafana]
    F --> H
    G --> H

    I[Alerting] --> J[AlertManager]
    J --> K[Notification Channels]

    L[Storage] --> M[Prometheus Storage]
    L --> N[Loki Storage]
    L --> O[Jaeger Storage]

Monitoring Components: - Metrics - Prometheus, Grafana - Logging - Loki, Fluent Bit - Tracing - Jaeger, OpenTelemetry - Alerting - AlertManager, notification channels - Storage - Long-term metrics and logs storage

Performance Monitoring¶

Performance Metrics¶

Key Metrics: - Response Time - API response time monitoring - Throughput - Requests per second - Error Rate - Error percentage and types - Resource Usage - CPU, memory, disk, network - User Experience - Page load time, user satisfaction

Performance Dashboards: - System Overview - Overall system health - Service Metrics - Individual service performance - Database Performance - Database query performance - User Metrics - User experience metrics - Business Metrics - Business-relevant metrics

✅ Architecture Best Practices¶

Design Principles¶

Microservices Best Practices¶

• Single Responsibility - Each service has a single responsibility
• Loose Coupling - Services are loosely coupled
• High Cohesion - Services are highly cohesive
• API-First - Design APIs first
• Fault Tolerance - Design for failure
• Observability - Make services observable

Data Architecture Best Practices¶

• Data Consistency - Ensure data consistency
• Data Security - Protect data at rest and in transit
• Data Privacy - Respect data privacy
• Data Governance - Implement data governance
• Data Quality - Ensure data quality
• Data Retention - Implement data retention policies

Common Architecture Mistakes¶

❌ Avoid These Mistakes: - Not designing for scalability - Not implementing proper security - Not considering fault tolerance - Not implementing proper monitoring - Not designing for maintainability

✅ Follow These Best Practices: - Design for scalability and performance - Implement security by design - Design for fault tolerance and resilience - Implement comprehensive monitoring - Design for maintainability and extensibility

!!! tip Start Small Begin with a simple architecture and evolve it as your needs grow. Don't over-engineer from the start.

!!! note Security First Always prioritize security in architecture decisions. Implement security controls at every layer.

!!! question Need Help? Check our Architecture Support for architecture assistance, or join our developer community.