Architecture /0.1
Architecture Center
Deep dive into the HarchOS architecture. Understand the SENSE-THINK-ACT layers, explore reference architectures, and learn the well-architected framework for sovereign AI infrastructure.
Architecture Overview
SENSE. THINK. ACT.
HarchOS operates on three interconnected layers: SENSE captures signals from the physical and digital world, THINK makes intelligent decisions using ML models, and ACT executes those decisions in real-time. A complete perception-decision-action cycle in under 200ms.
SENSE
Data Ingestion Layer
The perception layer of HarchOS. SENSE captures every signal from the physical and digital world — IoT sensors, satellite imagery, API feeds, and industrial control data. It processes over 50,000 data points per second with 1-second granularity and 4-hour forecast windows.
Key Capabilities
Technical Specifications
Data Flow: Physical world → SENSE → THINK
Reference Architectures
Proven Deployment Patterns
Reference architectures for the most common HarchOS deployment scenarios. Each architecture includes component diagrams, configuration templates, and operational runbooks.
Sovereign AI Cloud
Complete sovereign AI cloud deployment with all data and compute remaining within Morocco jurisdiction. Full SENSE-THINK-ACT stack deployed across a single hub with dedicated GPU clusters.
Components
Best for: Government agencies, defense, critical infrastructure operators requiring absolute data sovereignty.
Edge Computing
Low-latency edge deployment for real-time inference at the data source. SENSE agents at the edge collect and pre-process data, forwarding to the central THINK layer for decision-making.
Components
Best for: Mining sites, agricultural fields, remote infrastructure with limited or intermittent connectivity.
Multi-Hub Deployment
Full mesh deployment across multiple HarchOS hubs for maximum availability, carbon optimization, and geographic redundancy. Workloads migrate between hubs based on THINK optimization.
Components
Best for: Enterprise customers needing high availability, carbon optimization, and sub-5ms latency to multiple regions.
Hybrid Cloud
Hybrid deployment connecting HarchOS sovereign mesh with public cloud providers for burst capacity or specialized workloads. Data sovereignty is enforced at the orchestration level.
Components
Best for: Organizations with existing cloud investments requiring sovereign compute with burst capacity to public clouds.
Well-Architected Framework
Five Pillars of Excellence
The HarchOS Well-Architected Framework provides a consistent approach to evaluate architectures against best practices. Each pillar includes design principles, review questions, and remediation guidance.
Security
Security is architectural in HarchOS, not additive. Zero-trust authentication, sovereign encryption with locally-managed keys, micro-segmentation, and continuous compliance monitoring are built into every layer.
Design Principles
Reliability
HarchOS is designed for 99.999% uptime with zero-downtime failover, live migration, and multi-hub redundancy. The ACT layer executes failover in under 200ms.
Design Principles
Performance
HarchOS delivers efficient scaling across 800 GPUs per hub (1,798 total), with sub-5ms latency to Europe and a 400Gbps inter-hub backbone. Carbon-aware scheduling automatically routes workloads to hubs with the lowest carbon intensity (~47 gCO2/kWh average).
Design Principles
Cost Optimization
Carbon-aware scheduling reduces energy costs by 35% compared to static scheduling. Workloads automatically follow renewable energy availability across hubs.
Design Principles
Operational Excellence
Automated operations, continuous monitoring, and infrastructure-as-code ensure consistent, repeatable deployments across the mesh.
Design Principles
Design Patterns
Common Patterns
Proven design patterns for HarchOS deployments. Each pattern addresses a specific challenge in sovereign AI infrastructure and can be combined for complex architectures.
Hub-Affinity Routing
Pin workloads to a specific hub for data sovereignty compliance. THINK respects affinity rules while optimizing within the allowed hub set.
Carbon-Follow Scheduler
Schedule batch training jobs to follow peak renewable energy production across time zones. Solar hubs during the day, wind hubs at night.
Pipeline-Fanout
Ingest data once in SENSE, then fan out to multiple THINK processors and ACT executors in parallel for different use cases.
Canary Deployment
Deploy new model versions to a small percentage of traffic, monitor for regressions, then gradually increase traffic on confirmation.
Circuit Breaker
Wrap external API calls in a circuit breaker pattern. When a downstream service fails, ACT automatically reroutes to a healthy hub.
Event-Sourced Audit
Store all state changes as immutable events. Enables full audit trail reconstruction, compliance reporting, and time-travel debugging.
Best Practices
Key Recommendations
Start with Sovereignty-First Design
Define your data residency requirements before choosing architecture. Set sovereignty to "strict" in your client configuration and let HarchOS enforce it at every layer.
Use Carbon-Aware Scheduling for Batch Workloads
Training and batch processing workloads benefit most from carbon-aware scheduling. Use "carbon-optimal" schedule mode to automatically align compute with renewable energy availability.
Implement Defense in Depth
Layer your security controls: mTLS between services, RBAC for API access, network micro-segmentation, and HSM-backed encryption. HarchOS provides all of these natively.
Design for Multi-Hub from Day One
Even if you start with a single hub, architect your workloads for multi-hub deployment. Use hub: "auto" in your deployment config to let THINK choose the optimal placement.
Monitor Carbon Intensity, Not Just Cost
Track the carbon intensity of your workloads alongside cost. HarchOS exposes energy source and carbon metrics for every inference request and training job.
Automate Everything with Infrastructure-as-Code
Use the HarchOS Terraform provider for all resource provisioning. Declarative configuration ensures reproducibility, auditability, and eliminates configuration drift.