Runtime Architecture

This page describes architecture patterns, scaling strategies, and best practices for large HypnoScript projects in enterprises.

Architecture Patterns

Layered Architecture

• Presentation Layer: CLI, Web-UI, API Gateways
• Application Layer: Business logic, orchestration
• Domain Layer: Core logic, validation, rules
• Infrastructure Layer: Database, messaging, external services

graph TD
  A[Presentation] --> B[Application]
  B --> C[Domain]
  C --> D[Infrastructure]

Microservices Architecture

• Services are independent, communicate via APIs/Events
• Each service can use its own HypnoScript modules
• Service Discovery, Load Balancing, API Gateways

graph LR
  S1[User Service] -- API --> GW[API Gateway]
  S2[Order Service] -- API --> GW
  S3[Inventory Service] -- API --> GW
  GW -- REST/gRPC --> Client

Event-Driven Architecture

• Loose coupling through events and message queues
• Scalable, asynchronous processing

graph LR
  Producer -- Event --> Queue
  Queue -- Event --> Consumer1
  Queue -- Event --> Consumer2

Modularization

• Separation into standalone modules (e.g., auth, billing, reporting)
• Shared utility and core modules
• Clear interfaces (APIs, Contracts)

project/
├── modules/
│   ├── auth/
│   ├── billing/
│   ├── reporting/
│   └── core/
├── shared/
│   └── utils.hyp
├── config/
│   └── hypnoscript.config.json
└── scripts/
    └── deploy.sh

Scaling and Deployment

Scaling Strategies

• Horizontal Scaling: Multiple instances, load balancer
• Vertical Scaling: More resources per instance
• Auto-Scaling: Dynamic adjustment based on load

Deployment Patterns

• Blue-Green Deployment: Two environments, switch without downtime
• Canary Releases: New version for subset of users
• Rolling Updates: Gradual update

Containerization

• Using Docker for reproducible deployments
• Orchestration with Kubernetes, Docker Swarm

# Example: Kubernetes Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: hypnoscript-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: hypnoscript
  template:
    metadata:
      labels:
        app: hypnoscript
    spec:
      containers:
        - name: hypnoscript
          image: myregistry/hypnoscript:latest
          ports:
            - containerPort: 8080

Observability & Monitoring

• Centralized logging (ELK, Grafana, Prometheus)
• Distributed tracing (OpenTelemetry, Jaeger)
• Health checks, alerting

Security & Compliance

• Centralized authentication (SSO, OAuth, LDAP)
• Encryption (TLS, at-rest, in-transit)
• Audit logging, GDPR compliance

Best Practices

• Configuration Management: Separation of code and configuration
• Automated Testing & CI/CD: Quality and security
• Infrastructure as Code: Terraform, Ansible, Helm
• Documentation & Knowledge Management: Centrally maintained documentation

Example Architecture Diagram

graph TD
  subgraph Frontend
    UI[Web-UI]
    CLI[CLI]
  end
  subgraph Backend
    API[API Gateway]
    Auth[Auth Service]
    Billing[Billing Service]
    Reporting[Reporting Service]
    Core[Core Module]
  end
  subgraph Infrastructure
    DB[(Database)]
    MQ[(Message Queue)]
    Cache[(Redis Cache)]
    LB[Load Balancer]
  end
  UI --> API
  CLI --> API
  API --> Auth
  API --> Billing
  API --> Reporting
  Auth --> DB
  Billing --> DB
  Reporting --> DB
  API --> MQ
  API --> Cache
  LB --> API

Next Steps

• Runtime Security – Security architecture
• Runtime Monitoring – Monitoring & Alerting
• Runtime Integration – Interfaces & Integration

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