Skip to main content

Chapter 3: System Architecture

3.1 Architectural Overview​

3.1.1 System Layers​

3.1.2 Core Components​

LayerComponentsPurpose
User InterfaceWeb Console, APIs, CLIUser interaction and control
ServiceAI Services, Storage, NetworkCore functionality
OrchestrationRay, Kubernetes, Service MeshResource management
InfrastructureCompute, Storage, NetworkPhysical resources

3.2 Infrastructure Layer​

3.2.1 Resource Types​

3.2.2 Node Specifications​

Node TypeMinimum SpecsRecommended SpecsUse Case
GPUT4, 16GB VRAMA100, 80GB VRAMAI Training
CPU4 cores, 8GB RAM32 cores, 128GB RAMGeneral Compute
Storage100GB SSD2TB NVMeData Storage

3.3 Orchestration Layer​

3.3.1 Ray Framework Integration​

3.3.2 Kubernetes Integration​

ComponentFunctionIntegration Point
Pod ManagementContainer orchestrationRay workers
Service DiscoveryNode communicationMesh network
Auto-scalingResource optimizationDemand prediction
Load BalancingTraffic distributionRequest routing

3.4 Service Layer​

3.4.1 AI Services Architecture​

3.4.2 Data Flow​

StageProcessTechnology
IngestionData upload and validationSecure channels
ProcessingDistributed computationRay clusters
StorageEncrypted data storageDistributed FS
DeliveryResult distributionMesh network

3.5 High Availability Design​

3.5.1 Redundancy Architecture​

3.5.2 Failover Mechanisms​

ComponentFailover StrategyRecovery Time
Compute NodesAutomatic redistribution< 30 seconds
StorageReal-time replication< 10 seconds
NetworkRoute optimization< 5 seconds

3.6 Performance Optimization​

3.6.1 Resource Optimization​

3.6.2 Performance Metrics​

MetricTargetMonitoring
Training Throughput>90% GPU utilizationReal-time
Network Latency50ms within regionContinuous
Storage IOPS100k IOPSPeriodic
Availability99.99%Constant

This architecture combines Ray's distributed computing capabilities with Kubernetes orchestration and Mesh networking to create a secure, scalable platform optimized for AI workloads. The system's layered approach ensures separation of concerns while maintaining high performance and reliability.