Maxim Lanies, 2GC CloudBridge • • Updated: 10/15/2025

2GC CloudBridge: Architecture of Smart Network Layer for Real-Time and Secure Connectivity

Architecture and principles of the distributed 2GC CloudBridge platform for building secure, latency-optimized networks over existing internet infrastructure using QUIC/MASQUE, BBRv2, FEC, and AI-routing mechanisms.

2GC CloudBridge: Architecture of Smart Network Layer for Real-Time and Secure Connectivity
CloudBridge QUIC MASQUE BBRv2 FEC AI-routing Zero Trust Network Architecture Real-time

2GC CloudBridge: Architecture of Smart Network Layer for Real-Time and Secure Connectivity

Abstract: This article examines the architecture and principles of the distributed 2GC CloudBridge platform, designed for building secure, latency-optimized networks over existing internet infrastructure. The solution leverages modern transport technologies - QUIC/MASQUE, BBRv2, and Forward Error Correction (FEC), as well as AI-routing mechanisms and Zero-Trust security. Special attention is given to the combination of network and management layers that provide autonomous route optimization and resilience to failures and attacks.

Architectural Approach

CloudBridge is built as a multi-layered mesh network of regional nodes (Points of Presence) connected through MASQUE tunnels over QUIC. Each node performs relay, routing, and local telemetry analysis functions. Management is handled by a central Control Plane, including identity services (OIDC/Zitadel), orchestration (Cadence), monitoring (Prometheus, Grafana), and routing (GoBGP).

Core System Layers:

Transport Layer. QUIC and MASQUE implementation with connection migration, ACK-Frequency, FEC, and BBRv2 congestion control provides low latency and loss resilience.

AI-Routing Layer. Collection and analysis of telemetry (RTT, losses, load) enables prediction of channel degradation and real-time route restructuring.

Security Layer. Zero-Trust principles are applied: OIDC authentication, OPA policy control, inter-service mTLS encryption, and kernel-level Falco monitoring.

Observability Layer. Over 300 metrics and SLO contours enable assessment of data transmission quality and timely response to deviations.

Protocols and Research Results

In 2025, the CloudBridge team conducted a series of laboratory experiments on QUIC protocol integration and optimization (over 1200 tests). The following improvements were implemented:

  • BBRv2 showed throughput increase of 40–98% compared to Cubic
  • ACK-Frequency Optimization reduced overhead by 20–40%
  • FEC achieved recovery of up to 95% of lost packets with 10% redundancy
  • Critical Zone Avoidance (26–35 pps) eliminated the unstable protocol operation zone - throughput increased by 73%, latency decreased by 30%
  • Automatic TLS certificate rotation eliminated downtime associated with key expiration

These features are implemented in production and monitored through Prometheus metrics relay_quic_*.

Security and Fault Tolerance

For protection against distributed attacks, CloudBridge uses BGP-blackhole mechanisms (RFC 7999) and integration with upstream scrubbing providers. Overload detection is performed via Prometheus telemetry; system response time is less than 60 seconds from event to traffic filtering.

Zero-Trust architecture supports complete tenant isolation and centralized access policy control. All service interactions are encrypted and authenticated at the mutual TLS level.

DDoS Protection

CloudBridge integrates multi-level DDoS attack protection:

  • L3/L4 protection through BGP blackhole injection
  • Upstream scrubbing with Russian providers (Yandex Cloud, Qrator, RTK)
  • AI-powered detection with response time under 30 seconds
  • Real-time monitoring of scrubbing effectiveness

Practical Results

Test deployments showed:

  • 30–40% reduction in p95 RTT through optimized routing
  • SLA compliance improvement to 99.5% through automatic recovery
  • Complete elimination of “critical-zone” events thanks to BBRv2 and FEC
  • Compatibility with existing network protocols without operator equipment modification

Performance Metrics

relay_quic_throughput_bps{region="moscow"} 2.5e+09
relay_quic_rtt_p95_seconds{region="frankfurt"} 0.045
relay_quic_packet_loss_percent{region="amsterdam"} 0.001
relay_quic_fec_recovery_percent{region="singapore"} 94.7

Technology Stack

Transport Layer

  • QUIC v1 with connection migration support
  • MASQUE for UDP proxying over HTTP/3
  • BBRv2 congestion control for throughput optimization
  • Forward Error Correction for lost packet recovery

Control Plane

  • Zitadel for authentication and authorization (OIDC/OAuth2)
  • Cadence for workflow orchestration and automation
  • PostgreSQL HA with Patroni for state storage
  • Redis Sentinel for caching and sessions

Monitoring & Observability

  • Prometheus for metrics collection (300+ metrics)
  • Grafana for visualization and dashboards
  • Jaeger for distributed tracing
  • Falco for runtime security monitoring

Security

  • mTLS for inter-service encryption
  • OPA for access policy control
  • Network Policies for tenant isolation
  • BGP blackhole for automatic attack filtering

AI-Routing and Autonomous Optimization

CloudBridge uses machine learning for:

Channel Degradation Prediction

  • Analysis of historical RTT, loss, and load data
  • Prediction of overloads 5-15 minutes before events
  • Automatic switching to alternative routes

Real-Time Route Optimization

  • Multi-Armed Bandit algorithms for optimal path selection
  • Reinforcement Learning for adaptation to changing conditions
  • Balancing latency, reliability, and cost

Anomaly and Threat Detection

  • Isolation Forest for identifying unusual traffic patterns
  • Automatic threat classification (DDoS, intrusions, malware)
  • Proactive application of protective measures

Scaling and Fault Tolerance

Horizontal Scaling

  • Edge PoPs in 8+ regions (Moscow, St. Petersburg, Novosibirsk, Yekaterinburg, Minsk, Frankfurt, Singapore, Tokyo)
  • Auto-scaling based on load and latency metrics
  • Load balancing considering geographic proximity and channel quality

Vertical Fault Tolerance

  • PostgreSQL HA with automatic failover via Patroni
  • Redis Sentinel for high cache availability
  • Cadence workflows for automatic service recovery
  • Circuit breakers for isolating problematic components

Compliance and Regulatory Requirements

CloudBridge is designed with modern requirements in mind:

DORA (EU)

  • Continuous monitoring of operational resilience
  • Automated incident management
  • Centralized reporting and auditing

NIS2 (EU)

  • Enhanced cyber resilience measures
  • Mandatory segmentation and isolation
  • Supplier risk management

Zero Trust Architecture

  • “Never trust, always verify” principle
  • Minimal access privileges
  • Continuous device and user verification

Conclusion

CloudBridge demonstrates an approach to building self-adapting network layers where transport, analytics, and security are integrated into a unified management model. Such systems reflect a general shift toward programmable connectivity - networks that not only transmit data but understand how to do it efficiently and securely.

Key architectural advantages:

  • Autonomous optimization of routes without manual intervention
  • Proactive security with AI-powered threat detection
  • High performance through modern protocols
  • Complete observability through comprehensive monitoring
  • Regulatory compliance out of the box

CloudBridge represents not just a technological solution, but a fundamental shift in understanding how corporate networks should operate in the era of Zero Trust, AI, and modern transport protocols.

The convergence of advanced networking protocols, artificial intelligence, and Zero Trust security creates a new paradigm where networks become intelligent, self-managing systems that adapt to threats and optimize performance autonomously.

Supporting Sources