Infrastructure Documentation¶

Overview¶

The EEMT infrastructure documentation provides comprehensive technical details about the system architecture, deployment configurations, and operational considerations for running EEMT at scale.

Documentation Sections¶

Container Architecture¶

Detailed documentation of the Docker container ecosystem including: - Multi-layered container design - Image composition and dependencies - Volume management strategies - Network configuration - Security considerations - Performance optimization

Docker Deployment Guide¶

Step-by-step instructions for deploying EEMT using Docker: - Prerequisites and installation - Quick start procedures - Deployment modes (local, distributed, documentation) - Configuration options - Monitoring and maintenance

Web Interface Architecture¶

Technical architecture of the FastAPI web application: - System design and components - Request handling flow - Database architecture - Frontend implementation - Container orchestration - Performance considerations

Distributed Deployment¶

Guide for scaling EEMT across multiple nodes: - Master-worker architecture - HPC integration examples - Container orchestration platforms - Network and storage configuration

Infrastructure Components¶

Container Stack¶

graph TD
    subgraph "EEMT Container Ecosystem"
        A[Ubuntu 24.04 Base]
        B[Scientific Stack Layer]
        C[EEMT Core Layer]
        D1[Web Interface Container]
        D2[Worker Container]
        D3[Documentation Container]

        A --> B
        B --> C
        C --> D1
        C --> D2
        A --> D3
    end

Key Technologies¶

Deployment Architecture¶

graph LR
    subgraph "User Access"
        U1[Web Browser]
        U2[REST API Client]
        U3[CLI Tools]
    end

    subgraph "Application Layer"
        W[Web Interface]
        A[API Gateway]
    end

    subgraph "Processing Layer"
        M[Master Node]
        W1[Worker 1]
        W2[Worker 2]
        WN[Worker N]
    end

    subgraph "Storage Layer"
        V1[Data Volumes]
        V2[Results Storage]
        DB[Database]
    end

    U1 --> W
    U2 --> A
    U3 --> A
    W --> M
    A --> M
    M --> W1
    M --> W2
    M --> WN
    W1 --> V1
    W2 --> V1
    WN --> V2
    M --> DB

Resource Requirements¶

Minimum Infrastructure¶

Scaling Considerations¶

Vertical Scaling (Single Node)¶

• Increase CPU cores for more parallel workers
• Add RAM for larger datasets
• Use SSD storage for improved I/O
• GPU acceleration (future enhancement)

Horizontal Scaling (Multi-Node)¶

• Deploy master node for coordination
• Add worker nodes for processing
• Use shared storage (NFS, S3)
• Implement load balancing

Network Architecture¶

Port Allocations¶

Security Zones¶

graph TB
    subgraph "Public Zone"
        I[Internet]
        LB[Load Balancer]
    end

    subgraph "DMZ"
        WEB[Web Interface]
        API[API Gateway]
    end

    subgraph "Private Zone"
        MASTER[Master Node]
        WORKERS[Worker Pool]
        STORAGE[Storage]
        DB[Database]
    end

    I --> LB
    LB --> WEB
    LB --> API
    WEB --> MASTER
    API --> MASTER
    MASTER --> WORKERS
    WORKERS --> STORAGE
    MASTER --> DB

Storage Architecture¶

Volume Types¶

Data Flow¶

1. Input Stage: DEM files uploaded to uploads/ volume
2. Processing Stage: Temporary data in temp/ volume
3. Output Stage: Results written to results/ volume
4. Archive Stage: Results compressed and stored

Monitoring and Observability¶

Health Checks¶

# Docker health check configuration
healthcheck:
  test: ["CMD", "curl", "-f", "http://localhost:5000/health"]
  interval: 30s
  timeout: 10s
  retries: 3
  start_period: 40s

Metrics Collection¶

• System Metrics: CPU, memory, disk, network
• Application Metrics: Job count, processing time, success rate
• Container Metrics: Resource usage, restart count
• Custom Metrics: EEMT-specific calculations

Logging Strategy¶

Disaster Recovery¶

Backup Strategy¶

1. Database Backups: Daily SQLite dumps
2. Volume Snapshots: Weekly filesystem snapshots
3. Configuration Backup: Version controlled in Git
4. Container Images: Registry backups

Recovery Procedures¶

1. Service Failure: Auto-restart via Docker
2. Node Failure: Failover to standby node
3. Data Loss: Restore from backups
4. Complete Disaster: Rebuild from infrastructure-as-code

Performance Tuning¶

Container Optimization¶

# Resource limits and reservations
deploy:
  resources:
    limits:
      cpus: '4.0'
      memory: 8G
    reservations:
      cpus: '2.0'
      memory: 4G

Network Optimization¶

• Use bridge networks for local communication
• Enable host networking for performance-critical workers
• Implement connection pooling
• Configure DNS caching

Storage Optimization¶

• Use SSD for temporary processing
• Enable compression for results
• Implement data deduplication
• Regular cleanup of temporary files

Best Practices¶

Deployment¶

1. Use infrastructure-as-code (Docker Compose, Kubernetes manifests)
2. Implement blue-green deployments
3. Maintain staging environments
4. Automate deployment pipelines

Security¶

1. Run containers as non-root users
2. Implement network segmentation
3. Enable TLS for all communications
4. Regular security updates

Operations¶

1. Monitor all critical metrics
2. Implement automated alerts
3. Maintain runbooks for common issues
4. Regular disaster recovery testing

Troubleshooting Guide¶

Common Issues¶

Diagnostic Commands¶

# Check container status
docker ps -a

# View container logs
docker logs <container_name>

# Inspect container
docker inspect <container_name>

# Monitor resources
docker stats

# Network diagnostics
docker network ls
docker network inspect <network_name>

# Volume inspection
docker volume ls
docker volume inspect <volume_name>

Future Enhancements¶

Planned Infrastructure Improvements¶

1. Kubernetes Migration: Helm charts and operators
2. Service Mesh: Istio/Linkerd integration
3. Observability Stack: Prometheus + Grafana + Loki
4. CI/CD Pipeline: GitHub Actions + ArgoCD
5. Multi-Cloud Support: AWS, GCP, Azure deployments

Roadmap¶

• Q1 2025: Kubernetes deployment support
• Q2 2025: Enhanced monitoring and alerting
• Q3 2025: Multi-region deployment
• Q4 2025: Serverless execution options

Support Resources¶

• GitHub Issues
• Discussion Forum
• Container Registry
• Documentation