# TECHNICAL ARCHITECTURE & INFRASTRUCTURE PLAN
## RAG Heat & SWARMCARE - System Design & Technology Stack

**Document Version:** 2.1 Ultimate
**Date:** October 31, 2025
**Architecture Style:** Microservices with Event-Driven Components

---

## EXECUTIVE TECHNICAL SUMMARY

Both RAG Heat and SWARMCARE are built as cloud-native, microservices-based applications with shared infrastructure components. The architecture prioritizes:

- **Scalability:** Horizontal scaling for all services
- **Security:** HIPAA-compliant encryption and access control
- **Performance:** Sub-2-second API response times
- **Reliability:** 99.5%+ uptime with automated failover
- **Observability:** Comprehensive monitoring and logging

---

## SYSTEM ARCHITECTURE OVERVIEW

### High-Level Architecture Diagram:

```
┌─────────────────────────────────────────────────────────────────┐
│                        Load Balancer / CDN                      │
│                     (CloudFlare / Cloud Load Balancer)          │
└─────────────────────────────────────────────────────────────────┘
                                │
                ┌───────────────┴───────────────┐
                │                               │
    ┌───────────▼──────────┐       ┌───────────▼──────────┐
    │   RAG Heat Frontend  │       │ SWARMCARE Frontend   │
    │    (React/Next.js)   │       │   (React/Next.js)    │
    └───────────┬──────────┘       └───────────┬──────────┘
                │                               │
    ┌───────────▼──────────┐       ┌───────────▼──────────┐
    │  RAG Heat API        │       │  SWARMCARE API       │
    │  Gateway (FastAPI)   │       │  Gateway (FastAPI)   │
    └───────────┬──────────┘       └───────────┬──────────┘
                │                               │
    ┌───────────┴───────────────────────────────┴──────────┐
    │                                                        │
    │              Shared Services Layer                    │
    │  ┌─────────┐  ┌─────────┐  ┌──────────┐             │
    │  │ Auth    │  │ Logging │  │ Metrics  │             │
    │  │ Service │  │ Service │  │ Service  │             │
    │  └─────────┘  └─────────┘  └──────────┘             │
    └────────────────────────────────────────────────────────┘
                                │
    ┌───────────────────────────┴───────────────────────────┐
    │                                                         │
┌───▼────────┐  ┌────────────┐  ┌──────────┐  ┌───────────┐
│ Neo4j      │  │ Vector DB  │  │ Document │  │PostgreSQL │
│ (Knowledge │  │(Weaviate/  │  │Store     │  │(Metadata) │
│  Graph)    │  │ Pinecone)  │  │(MarkLogic│  │           │
│            │  │            │  │/MongoDB) │  │           │
└────────────┘  └────────────┘  └──────────┘  └───────────┘
```

---

## RAG HEAT ARCHITECTURE

### Component Diagram:

```
┌──────────────────────────────────────────────────────────────┐
│                    RAG Heat System                           │
│                                                               │
│  ┌─────────────────────────────────────────────────────┐   │
│  │              Frontend Layer (React)                  │   │
│  │  - Document Upload UI                                │   │
│  │  - Query Interface                                   │   │
│  │  - Results Visualization                             │   │
│  │  - Knowledge Graph Explorer                          │   │
│  └──────────────────┬──────────────────────────────────┘   │
│                     │                                        │
│  ┌──────────────────▼──────────────────────────────────┐   │
│  │           API Gateway (FastAPI)                      │   │
│  │  /api/v1/documents  - Document management           │   │
│  │  /api/v1/query      - RAG queries                    │   │
│  │  /api/v1/graph      - Knowledge graph queries        │   │
│  │  /api/v1/embeddings - Embedding generation           │   │
│  └──────────────────┬──────────────────────────────────┘   │
│                     │                                        │
│  ┌──────────────────▼──────────────────────────────────┐   │
│  │              Core Services                           │   │
│  │                                                       │   │
│  │  ┌─────────────────────────────────────────────┐   │   │
│  │  │  Document Processing Service                 │   │   │
│  │  │  - PDF/Text extraction                       │   │   │
│  │  │  - Chunking strategies                       │   │   │
│  │  │  - Metadata extraction                       │   │   │
│  │  └─────────────────┬───────────────────────────┘   │   │
│  │                    │                                 │   │
│  │  ┌─────────────────▼───────────────────────────┐   │   │
│  │  │  Embedding Service                           │   │   │
│  │  │  - OpenAI/Cohere embeddings                  │   │   │
│  │  │  - Batch processing                          │   │   │
│  │  │  - Caching layer                             │   │   │
│  │  └─────────────────┬───────────────────────────┘   │   │
│  │                    │                                 │   │
│  │  ┌─────────────────▼───────────────────────────┐   │   │
│  │  │  RAG Pipeline Service (LangChain)            │   │   │
│  │  │  - Query understanding                       │   │   │
│  │  │  - Retrieval (hybrid: vector + graph)        │   │   │
│  │  │  - Context ranking                           │   │   │
│  │  │  - Generation (OpenAI/Claude)                │   │   │
│  │  └─────────────────┬───────────────────────────┘   │   │
│  │                    │                                 │   │
│  │  ┌─────────────────▼───────────────────────────┐   │   │
│  │  │  Medical NLP Service                         │   │   │
│  │  │  - NER (Named Entity Recognition)            │   │   │
│  │  │  - Ontology linking                          │   │   │
│  │  │  - Concept extraction                        │   │   │
│  │  └─────────────────┬───────────────────────────┘   │   │
│  │                    │                                 │   │
│  │  ┌─────────────────▼───────────────────────────┐   │   │
│  │  │  Knowledge Graph Service                     │   │   │
│  │  │  - Graph queries (Cypher)                    │   │   │
│  │  │  - Ontology reasoning                        │   │   │
│  │  │  - Graph algorithms                          │   │   │
│  │  └─────────────────────────────────────────────┘   │   │
│  └───────────────────────────────────────────────────┘   │
│                                                            │
│  ┌──────────────────────────────────────────────────┐    │
│  │              Data Layer                           │    │
│  │  - Neo4j (Knowledge Graph)                        │    │
│  │  - Weaviate/Pinecone (Vector Store)               │    │
│  │  - MarkLogic/MongoDB (Document Store)             │    │
│  │  - PostgreSQL (Metadata, Users, Logs)             │    │
│  │  - Redis (Caching, Sessions)                      │    │
│  └──────────────────────────────────────────────────┘    │
└────────────────────────────────────────────────────────────┘
```

---

## SWARMCARE ARCHITECTURE

### Component Diagram:

```
┌──────────────────────────────────────────────────────────────┐
│                  SWARMCARE System                            │
│                                                               │
│  ┌─────────────────────────────────────────────────────┐   │
│  │              Frontend Layer (React)                  │   │
│  │  - Healthcare Dashboard                              │   │
│  │  - Workflow Management                               │   │
│  │  - Real-time Collaboration                           │   │
│  │  - Agent Monitoring                                  │   │
│  └──────────────────┬──────────────────────────────────┘   │
│                     │                                        │
│  ┌──────────────────▼──────────────────────────────────┐   │
│  │           API Gateway (FastAPI)                      │   │
│  │  /api/v1/workflows   - Workflow management           │   │
│  │  /api/v1/agents      - Agent operations              │   │
│  │  /api/v1/tasks       - Task management               │   │
│  │  /api/v1/realtime    - WebSocket connections         │   │
│  └──────────────────┬──────────────────────────────────┘   │
│                     │                                        │
│  ┌──────────────────▼──────────────────────────────────┐   │
│  │              Core Services                           │   │
│  │                                                       │   │
│  │  ┌─────────────────────────────────────────────┐   │   │
│  │  │  Multi-Agent Orchestration Service           │   │   │
│  │  │  - Agent lifecycle management                │   │   │
│  │  │  - Task delegation                           │   │   │
│  │  │  - Inter-agent communication                 │   │   │
│  │  │  - Agent coordination                        │   │   │
│  │  └─────────────────┬───────────────────────────┘   │   │
│  │                    │                                 │   │
│  │  ┌─────────────────▼───────────────────────────┐   │   │
│  │  │  Agent Intelligence Service                  │   │   │
│  │  │  - LLM-powered decision making               │   │   │
│  │  │  - Healthcare domain logic                   │   │   │
│  │  │  - Adaptive behavior                         │   │   │
│  │  └─────────────────┬───────────────────────────┘   │   │
│  │                    │                                 │   │
│  │  ┌─────────────────▼───────────────────────────┐   │   │
│  │  │  Workflow Engine Service                     │   │   │
│  │  │  - Workflow definition (BPMN-like)           │   │   │
│  │  │  - State management                          │   │   │
│  │  │  - Task routing                              │   │   │
│  │  │  - Workflow monitoring                       │   │   │
│  │  └─────────────────┬───────────────────────────┘   │   │
│  │                    │                                 │   │
│  │  ┌─────────────────▼───────────────────────────┐   │   │
│  │  │  Real-time Communication Service             │   │   │
│  │  │  - WebSocket/SignalR management              │   │   │
│  │  │  - Event broadcasting                        │   │   │
│  │  │  - Live notifications                        │   │   │
│  │  └─────────────────┬───────────────────────────┘   │   │
│  │                    │                                 │   │
│  │  ┌─────────────────▼───────────────────────────┐   │   │
│  │  │  Healthcare Integration Service              │   │   │
│  │  │  - FHIR API support                          │   │   │
│  │  │  - EHR integration layer                     │   │   │
│  │  │  - HL7 message handling                      │   │   │
│  │  └─────────────────┬───────────────────────────┘   │   │
│  │                    │                                 │   │
│  │  ┌─────────────────▼───────────────────────────┐   │   │
│  │  │  Clinical Decision Support Service           │   │   │
│  │  │  - Risk prediction models                    │   │   │
│  │  │  - Patient triage                            │   │   │
│  │  │  - Treatment recommendations                 │   │   │
│  │  └─────────────────────────────────────────────┘   │   │
│  └───────────────────────────────────────────────────┘   │
│                                                            │
│  ┌──────────────────────────────────────────────────┐    │
│  │              Data Layer                           │    │
│  │  - Neo4j (Care relationships, workflows)          │    │
│  │  - PostgreSQL (Tasks, agents, state)              │    │
│  │  - MongoDB (Healthcare documents)                 │    │
│  │  - Redis (Real-time state, queues)                │    │
│  │  - Message Queue (RabbitMQ/Kafka)                 │    │
│  └──────────────────────────────────────────────────┘    │
└────────────────────────────────────────────────────────────┘
```

---

## SHARED INFRASTRUCTURE

### Shared Services:

```
┌──────────────────────────────────────────────────────────┐
│                 Shared Services Platform                  │
│                                                            │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐   │
│  │ Auth Service │  │ API Gateway  │  │ Rate Limiter │   │
│  │ (OAuth2/JWT) │  │ (Kong/Tyk)   │  │ (Redis)      │   │
│  └──────────────┘  └──────────────┘  └──────────────┘   │
│                                                            │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐   │
│  │ Logging      │  │ Monitoring   │  │ Alerting     │   │
│  │ (ELK Stack)  │  │ (Prometheus/ │  │ (PagerDuty/  │   │
│  │              │  │  Grafana)    │  │  Slack)      │   │
│  └──────────────┘  └──────────────┘  └──────────────┘   │
│                                                            │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐   │
│  │ Secret Mgmt  │  │ Config Mgmt  │  │ Service Mesh │   │
│  │ (Vault)      │  │ (Consul)     │  │ (Istio)      │   │
│  └──────────────┘  └──────────────┘  └──────────────┘   │
└──────────────────────────────────────────────────────────┘
```

---

## TECHNOLOGY STACK DETAILS

### Frontend Stack:

**Framework:**
- React 18.2+ with TypeScript
- Next.js 14+ for SSR and routing
- Vite for build tooling (alternative)

**UI Libraries:**
- Material-UI (MUI) v5 or Tailwind CSS v3
- Shadcn/ui components (modern, accessible)
- React Hook Form for forms
- Zod for validation

**State Management:**
- Redux Toolkit (global state)
- React Query (TanStack Query) for server state
- Zustand (lightweight state) for simple cases

**Real-time:**
- Socket.io-client or SignalR client
- SWR for real-time data fetching

**Visualization:**
- D3.js for custom visualizations
- Recharts or Chart.js for standard charts
- React Flow for workflow diagrams
- vis.js for graph visualization

**Testing:**
- Jest for unit tests
- React Testing Library for component tests
- Playwright or Cypress for E2E tests

---

### Backend Stack (Python):

**Framework:**
- FastAPI 0.104+ (primary)
- Pydantic v2 for validation
- SQLAlchemy 2.0+ for ORM
- Alembic for migrations

**RAG & LLM:**
- LangChain 0.1.0+ (RAG orchestration)
- LlamaIndex 0.9+ (alternative/complementary)
- OpenAI Python SDK
- Anthropic Python SDK
- Hugging Face Transformers

**Multi-Agent:**
- AutoGen (Microsoft)
- CrewAI
- Custom agent framework on top of LangChain

**Medical NLP:**
- spaCy 3.7+ with medical models
- scispaCy (scientific/medical NLP)
- Transformers (BioBERT, ClinicalBERT)
- MedCAT for medical NER

**Background Jobs:**
- Celery 5.3+ with Redis broker
- APScheduler for cron-like tasks
- Dramatiq (alternative)

**API Documentation:**
- FastAPI auto-generated Swagger/OpenAPI
- Redoc for enhanced documentation

**Testing:**
- Pytest 7.4+
- Pytest-asyncio for async tests
- Pytest-cov for coverage
- Locust for load testing

---

### Databases:

**Neo4j (Knowledge Graph):**
- Version: 5.x Enterprise or Community
- Purpose: Ontology storage, relationship queries
- Access: py2neo or neo4j-driver
- Deployment: Managed cloud or self-hosted
- Backup: Automated daily backups

**Vector Database (Choose One):**

**Option A: Weaviate**
- Open-source, self-hosted
- Built-in vectorization
- Hybrid search (vector + keyword)
- GraphQL API
- Docker deployment

**Option B: Pinecone**
- Managed service
- Fastest time to production
- Auto-scaling
- Higher cost
- Better for MVP

**Recommendation:** Start with Pinecone for speed, migrate to Weaviate if cost becomes issue.

**Document Store (Choose One):**

**Option A: MarkLogic**
- Enterprise-grade
- HIPAA-compliant out of box
- Expensive licensing
- Excellent for healthcare

**Option B: MongoDB**
- Open-source, flexible
- Good healthcare document support
- Cheaper alternative
- HIPAA-compliant with configuration

**Recommendation:** MongoDB for cost-effectiveness, MarkLogic if budget allows.

**PostgreSQL:**
- Version: 15+ with pgvector extension
- Purpose: Metadata, users, logs, structured data
- Extensions: pgvector, pg_trgm, uuid-ossp
- Managed: AWS RDS or Google Cloud SQL

**Redis:**
- Version: 7.0+
- Purpose: Caching, sessions, real-time state, message broker
- Deployment: Redis Cloud or self-hosted
- Persistence: AOF + RDB for durability

---

### Message Queue:

**RabbitMQ:**
- Purpose: Task queues, event bus for SWARMCARE agents
- Deployment: CloudAMQP or self-hosted
- Alternative: Apache Kafka for higher scale

---

### Cloud Infrastructure:

**Primary Cloud: Google Cloud Platform (GCP)**

**Compute:**
- Google Kubernetes Engine (GKE) for container orchestration
- Cloud Run for serverless APIs (optional for low-traffic services)
- Compute Engine for VMs (Neo4j, databases if not managed)

**Storage:**
- Cloud Storage for document/file storage
- Persistent Disks for database volumes

**Networking:**
- Cloud Load Balancing
- Cloud CDN for static assets
- VPC for private networking
- Cloud Armor for DDoS protection

**Security:**
- Cloud IAM for access control
- Cloud KMS for encryption keys
- Secret Manager for secrets
- Security Command Center

**Monitoring:**
- Cloud Monitoring (Stackdriver)
- Cloud Logging
- Cloud Trace for distributed tracing

**Alternative: AWS**
If GCP data not available:
- EKS instead of GKE
- S3 instead of Cloud Storage
- RDS instead of Cloud SQL
- ELB instead of Cloud Load Balancing

---

### DevOps & CI/CD:

**Version Control:**
- GitHub (private organization)
- Branch protection rules
- Required code reviews

**CI/CD:**
- GitHub Actions (primary)
- Docker Hub or Google Container Registry
- Automated testing on PR
- Automated deployment to staging on merge
- Manual approval for production

**Infrastructure as Code:**
- Terraform for cloud infrastructure
- Helm charts for Kubernetes deployments
- Docker Compose for local development

**Containerization:**
- Docker for all services
- Multi-stage builds for smaller images
- Docker Compose for local orchestration
- Kubernetes for production orchestration

**Monitoring & Observability:**
- Prometheus for metrics collection
- Grafana for visualization
- ELK Stack (Elasticsearch, Logstash, Kibana) for logs
- Jaeger or OpenTelemetry for distributed tracing
- Sentry for error tracking

**Secrets Management:**
- HashiCorp Vault (self-hosted)
- Google Secret Manager (GCP)
- AWS Secrets Manager (AWS)

---

## DATA ARCHITECTURE

### Ontology Integration (13-14 Ontologies):

**Ontologies to Integrate:**

1. **SNOMED-CT** (Systematized Nomenclature of Medicine - Clinical Terms)
   - 350,000+ clinical concepts
   - Primary clinical terminology

2. **ICD-10** (International Classification of Diseases, 10th Revision)
   - Disease classification
   - Billing and epidemiology

3. **ICD-11** (Latest version)
   - Updated disease classification
   - Better digital integration

4. **RxNorm** (Medications)
   - Normalized names for drugs
   - Drug interaction data

5. **LOINC** (Logical Observation Identifiers Names and Codes)
   - Laboratory and clinical observations
   - Test results standardization

6. **CPT** (Current Procedural Terminology)
   - Medical procedures and services
   - Billing codes

7. **HL7 FHIR** (Fast Healthcare Interoperability Resources)
   - Healthcare data exchange standard
   - RESTful API standard

8. **UMLS** (Unified Medical Language System)
   - Meta-ontology linking other ontologies
   - Concept mapping

9. **HPO** (Human Phenotype Ontology)
   - Phenotypic abnormalities
   - Genetic diseases

10. **Gene Ontology**
    - Gene functions and relationships
    - Bioinformatics integration

11. **Disease Ontology (DO)**
    - Disease classification and relationships
    - Research integration

12. **Drug Ontology (DrON)**
    - Drug classification
    - Chemical structures

13. **Clinical Quality Language (CQL)**
    - Quality measures
    - Clinical decision support

14. **OMOP CDM** (Observational Medical Outcomes Partnership Common Data Model)
    - Standardized data schema
    - Multi-institution studies

---

### Ontology Loading Pipeline:

```
┌─────────────────────────────────────────────────────────┐
│              Ontology Loading Pipeline                  │
│                                                          │
│  1. Download     →  2. Parse        →  3. Transform     │
│     (Automated)      (Python scripts)   (Graph format)  │
│                                                          │
│  4. Load to Neo4j → 5. Create Index → 6. Validate       │
│     (Batch import)   (Performance)      (Completeness)  │
│                                                          │
│  7. Link Ontologies → 8. Cache Common Queries           │
│     (Cross-reference)  (Performance optimization)       │
└─────────────────────────────────────────────────────────┘
```

**Implementation:**
- Automated weekly updates
- Differential loading (only changes)
- Version tracking for reproducibility

---

### Data Flow: RAG Heat

```
User Query
    │
    ▼
Query Understanding (LLM)
    │
    ▼
Medical NER (Extract entities)
    │
    ├──► Vector Search (Weaviate/Pinecone)
    │    - Find similar documents
    │    - Semantic search
    │
    └──► Graph Query (Neo4j)
         - Ontology reasoning
         - Relationship traversal
    │
    ▼
Context Fusion
    │
    ▼
Re-ranking (Relevance scoring)
    │
    ▼
Generation (LLM with context)
    │
    ▼
Response to User
```

---

### Data Flow: SWARMCARE

```
Healthcare Event (e.g., new patient)
    │
    ▼
Workflow Engine (Determines workflow)
    │
    ▼
Task Delegation (Assign to agents)
    │
    ├──► Agent 1: Patient Intake
    │    (LLM-powered data collection)
    │
    ├──► Agent 2: Risk Assessment
    │    (ML model prediction)
    │
    ├──► Agent 3: Care Coordination
    │    (Schedule appointments, notify staff)
    │
    └──► Agent 4: Documentation
         (Generate reports, update EHR)
    │
    ▼
Agent Collaboration (Inter-agent messaging)
    │
    ▼
Workflow Completion
    │
    ▼
Real-time Updates (WebSocket to frontend)
```

---

## API DESIGN

### RAG Heat API Endpoints:

**Document Management:**
```
POST   /api/v1/documents                 - Upload document
GET    /api/v1/documents                 - List documents
GET    /api/v1/documents/{id}            - Get document details
DELETE /api/v1/documents/{id}            - Delete document
PUT    /api/v1/documents/{id}/process    - Reprocess document
```

**Query & Retrieval:**
```
POST   /api/v1/query                     - RAG query
POST   /api/v1/query/batch               - Batch queries
GET    /api/v1/query/{id}                - Get query results
POST   /api/v1/query/{id}/feedback       - Provide feedback
```

**Knowledge Graph:**
```
GET    /api/v1/graph/ontologies          - List ontologies
POST   /api/v1/graph/query               - Cypher query
GET    /api/v1/graph/entity/{id}         - Get entity details
GET    /api/v1/graph/relationships/{id}  - Get relationships
POST   /api/v1/graph/search              - Search entities
```

**Embeddings:**
```
POST   /api/v1/embeddings/generate       - Generate embeddings
POST   /api/v1/embeddings/batch          - Batch embedding generation
```

---

### SWARMCARE API Endpoints:

**Workflows:**
```
GET    /api/v1/workflows                 - List workflows
POST   /api/v1/workflows                 - Create workflow
GET    /api/v1/workflows/{id}            - Get workflow
PUT    /api/v1/workflows/{id}            - Update workflow
DELETE /api/v1/workflows/{id}            - Delete workflow
POST   /api/v1/workflows/{id}/start      - Start workflow instance
GET    /api/v1/workflows/{id}/status     - Get workflow status
```

**Agents:**
```
GET    /api/v1/agents                    - List agents
POST   /api/v1/agents                    - Create agent
GET    /api/v1/agents/{id}               - Get agent details
PUT    /api/v1/agents/{id}               - Update agent
DELETE /api/v1/agents/{id}               - Delete agent
POST   /api/v1/agents/{id}/activate      - Activate agent
POST   /api/v1/agents/{id}/deactivate    - Deactivate agent
```

**Tasks:**
```
GET    /api/v1/tasks                     - List tasks
POST   /api/v1/tasks                     - Create task
GET    /api/v1/tasks/{id}                - Get task details
PUT    /api/v1/tasks/{id}                - Update task
POST   /api/v1/tasks/{id}/assign         - Assign task to agent
POST   /api/v1/tasks/{id}/complete       - Mark task complete
```

**Real-time:**
```
WS     /api/v1/realtime                  - WebSocket connection
POST   /api/v1/realtime/broadcast        - Broadcast message
```

---

## SECURITY ARCHITECTURE

### Authentication & Authorization:

**Authentication:**
- OAuth 2.0 / OpenID Connect
- JWT tokens (15-min access, 7-day refresh)
- Multi-factor authentication (MFA) for admins
- API keys for service-to-service

**Authorization:**
- Role-Based Access Control (RBAC)
- Resource-level permissions
- Attribute-Based Access Control (ABAC) for complex rules

**Roles:**
- Super Admin (full access)
- Admin (project management)
- Developer (code and data access)
- Researcher (data read, research features)
- API Consumer (external integrations)

---

### HIPAA Compliance:

**Encryption:**
- **At Rest:** AES-256 encryption for all data
- **In Transit:** TLS 1.3 for all connections
- **Keys:** Managed by Cloud KMS or Vault

**Access Control:**
- Minimum necessary access principle
- Role-based permissions
- Audit logs for all data access
- Session timeouts (15 minutes idle)

**Audit Logging:**
- All API calls logged
- All data access logged
- Logs retained for 7 years
- Tamper-proof logging (write-once storage)

**Data Retention:**
- Patient data: 7 years minimum
- System logs: 7 years
- Backups: 90 days rolling, 7 years annual

**Business Associate Agreements (BAA):**
- Required with all cloud providers
- Required with LLM providers (OpenAI, Anthropic)
- Templates prepared by legal advisor

**Breach Notification:**
- Automated breach detection
- Incident response plan
- Legal notification process (60 days)

---

### Network Security:

**Firewall:**
- Web Application Firewall (WAF) - Cloud Armor or AWS WAF
- DDoS protection
- IP whitelisting for admin access

**VPN:**
- VPN required for production database access
- VPN for internal services

**Network Segmentation:**
- Public subnet: Load balancers
- Private subnet: Application servers
- Data subnet: Databases (no internet access)

---

## SCALABILITY & PERFORMANCE

### Horizontal Scaling:

**Application Layer:**
- Stateless services (12-factor app)
- Auto-scaling based on CPU/memory (HPA in Kubernetes)
- Scale from 2 to 50 pods per service

**Database Layer:**
- Neo4j clustering (3+ nodes for HA)
- PostgreSQL read replicas (3+ replicas)
- Vector DB sharding (if needed)

**Caching:**
- Redis cluster for distributed caching
- CDN for static assets
- API response caching (5-60 mins depending on endpoint)

---

### Performance Targets:

| Metric | Target | Measurement |
|--------|--------|-------------|
| API Response Time (p95) | <2s | All API endpoints |
| API Response Time (p99) | <5s | All API endpoints |
| RAG Query Time | <3s | Document retrieval + generation |
| Graph Query Time | <100ms | Simple Cypher queries |
| Concurrent Users | 1,000+ | Simultaneous active users |
| Throughput | 1,000 req/s | Per service |
| Database Write TPS | 10,000+ | Transactions per second |
| System Uptime | 99.5% | Monthly uptime |

---

### Performance Optimization Strategies:

**Caching:**
- Redis for hot data (embeddings, common queries)
- Browser caching for static assets
- API Gateway caching for idempotent GETs

**Database Optimization:**
- Index optimization (Neo4j and PostgreSQL)
- Query optimization (EXPLAIN ANALYZE)
- Connection pooling (pgBouncer)
- Read replicas for read-heavy operations

**Code Optimization:**
- Async/await for I/O operations
- Batch processing for embeddings
- Lazy loading for large datasets
- Pagination for list endpoints

**Load Balancing:**
- Round-robin for stateless services
- Least connections for stateful services
- Health checks (every 10 seconds)

---

## DISASTER RECOVERY & BACKUP

### Backup Strategy:

**Database Backups:**
- **PostgreSQL:** Automated daily backups, retain 30 days
- **Neo4j:** Automated daily backups, retain 30 days
- **MongoDB:** Automated daily backups, retain 30 days
- **Redis:** RDB snapshots every 6 hours

**Application Data:**
- **Documents:** Replicated to 3 regions
- **Code:** Git (no backup needed)
- **Config:** Stored in IaC (Git)

**Backup Testing:**
- Monthly restore test
- Quarterly full disaster recovery drill

---

### Disaster Recovery Plan:

**RTO (Recovery Time Objective):** 4 hours
**RPO (Recovery Point Objective):** 1 hour

**Failover Procedure:**
1. Detect failure (automated monitoring)
2. Alert on-call engineer (5 minutes)
3. Assess impact (15 minutes)
4. Initiate failover (30 minutes)
5. Restore from backup if needed (2-3 hours)
6. Verify functionality (1 hour)

**Multi-Region Deployment:**
- Active-passive setup (primary + backup region)
- Automated failover for critical services
- Data replication between regions

---

## MCP (MODEL CONTEXT PROTOCOL) SERVERS

### MCP Architecture:

**Purpose:**
- Extend LLM capabilities with custom tools
- Healthcare-specific integrations
- Real-time data access for agents

**MCP Servers to Build:**

1. **Medical Knowledge MCP Server**
   - Tools: Search ontologies, query Neo4j, get drug interactions
   - Use Case: Agents query medical knowledge

2. **EHR Integration MCP Server**
   - Tools: Read patient data, write notes, schedule appointments
   - Use Case: SWARMCARE agents interact with EHR

3. **Document Processing MCP Server**
   - Tools: Extract text, OCR, parse medical documents
   - Use Case: Process uploaded healthcare documents

4. **Real-time Notification MCP Server**
   - Tools: Send notifications, create alerts, broadcast updates
   - Use Case: Real-time updates to users and agents

**MCP Implementation:**
- Python SDK: `mcp` package
- Hosted as separate services
- Authentication via API keys
- Rate limiting per tool

---

## DEVELOPMENT ENVIRONMENT

### Local Development Setup:

**Prerequisites:**
- Python 3.11+
- Node.js 20+
- Docker Desktop
- Git
- IDE: VS Code with Claude Code extension

**Setup Script:**
```bash
# Clone repositories
git clone [repo-url] raghe-at && cd raghe-at
git clone [repo-url] swarmcare && cd swarmcare

# Install dependencies
cd raghe-at/backend && pip install -r requirements.txt
cd raghe-at/frontend && npm install

# Start services with Docker Compose
docker-compose up -d

# Run migrations
cd raghe-at/backend && alembic upgrade head

# Start development servers
cd raghe-at/backend && uvicorn main:app --reload
cd raghe-at/frontend && npm run dev
```

**Docker Compose for Local Dev:**
```yaml
version: '3.8'
services:
  postgres:
    image: postgres:15
    environment:
      POSTGRES_DB: raghe-at
      POSTGRES_USER: dev
      POSTGRES_PASSWORD: devpass
    ports:
      - "5432:5432"

  neo4j:
    image: neo4j:5.12
    environment:
      NEO4J_AUTH: neo4j/devpass
    ports:
      - "7474:7474"
      - "7687:7687"

  redis:
    image: redis:7
    ports:
      - "6379:6379"

  weaviate:
    image: semitechnologies/weaviate:latest
    environment:
      QUERY_DEFAULTS_LIMIT: 25
      AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED: 'true'
    ports:
      - "8080:8080"
```

---

## DEPLOYMENT ARCHITECTURE

### Kubernetes Deployment:

**Namespaces:**
- `raghe-at-prod`
- `swarmcare-prod`
- `shared-services`
- `monitoring`

**Deployment Strategy:**
- Blue-green deployments for zero downtime
- Canary releases for risky changes
- Rollback capability (previous 5 versions)

**Resource Allocation (per service):**
```yaml
resources:
  requests:
    memory: "512Mi"
    cpu: "500m"
  limits:
    memory: "2Gi"
    cpu: "2000m"
```

**Autoscaling:**
```yaml
autoscaling:
  minReplicas: 2
  maxReplicas: 10
  targetCPUUtilizationPercentage: 70
  targetMemoryUtilizationPercentage: 80
```

---

## DOCUMENT REFERENCES

This document is part of the comprehensive project plan:

1. Master Project Plan
2. Resource Allocation & Organizational Chart
3. Sprint Planning & Execution Framework
4. **Technical Architecture & Infrastructure Plan** ← YOU ARE HERE
5. Advisory Board & Stakeholder Engagement Plan
6. Compensation & Performance Metrics Framework
7. Research & Documentation Strategy
8. Risk Management & Compliance Plan
9. Communication & Collaboration Framework
10. Timeline & Milestone Tracker

---

**END OF TECHNICAL ARCHITECTURE & INFRASTRUCTURE PLAN**
