Architecture

The Soom AI platform is built on a modern, cloud-native architecture designed for scalability, security, and performance. Our architecture follows industry best practices and is optimized for enterprise-grade AI workloads.

System Architecture Overview

Core Components

API Gateway

The API Gateway serves as the single entry point for all client requests, providing:

• Load Balancing: Distributes traffic across multiple service instances
• Authentication & Authorization: Validates user credentials and permissions
• Rate Limiting: Prevents abuse and ensures fair resource usage
• Request Routing: Routes requests to appropriate microservices
• SSL Termination: Handles HTTPS encryption and decryption

Microservices Architecture

Our platform is built using a microservices architecture with the following core services:

Agent Service

• Manages AI agent lifecycle (creation, deployment, monitoring)
• Handles agent communication and orchestration
• Provides agent configuration and management APIs
• Implements agent scaling and load balancing

Application Service

• Manages pre-built and custom applications
• Handles application deployment and configuration
• Provides application marketplace functionality
• Manages application updates and versioning

API Service

• Exposes RESTful and GraphQL APIs
• Manages API versioning and backward compatibility
• Provides API documentation and testing tools
• Implements API analytics and monitoring

MCP Service

• Implements Model Context Protocol servers
• Manages MCP server lifecycle and configuration
• Provides protocol compliance validation
• Handles MCP server communication and routing

User Service

• Manages user accounts and authentication
• Handles role-based access control (RBAC)
• Provides user profile and preference management
• Implements user analytics and activity tracking

AI Infrastructure

Model Inference Engine

Our AI infrastructure is built on a distributed inference engine that provides:

• Model Serving: High-performance model inference serving
• Auto-scaling: Automatic scaling based on demand
• Model Versioning: Support for multiple model versions
• A/B Testing: Built-in model comparison and testing
• Performance Optimization: GPU acceleration and model optimization

Vector Database

For semantic search and retrieval-augmented generation (RAG):

• High-Dimensional Vectors: Efficient storage and retrieval of embeddings
• Similarity Search: Fast nearest neighbor search algorithms
• Indexing: Optimized indexing for large-scale vector operations
• Replication: Data replication for high availability

Memory Store

Persistent memory for AI agents and applications:

• Long-term Memory: Persistent storage for agent memories
• Context Management: Efficient context window management
• Memory Retrieval: Fast memory search and retrieval
• Memory Compression: Optimized memory storage and compression

Data Architecture

Primary Database (PostgreSQL)

• ACID Compliance: Ensures data consistency and reliability
• Horizontal Scaling: Read replicas and sharding support
• Backup & Recovery: Automated backups and point-in-time recovery
• Security: Encryption at rest and in transit

Caching Layer (Redis)

• Session Storage: User session and authentication data
• API Caching: Frequently accessed API responses
• Real-time Data: Pub/sub for real-time notifications
• Distributed Locking: Coordination between services

Object Storage

• File Storage: User uploads, model artifacts, and logs
• CDN Integration: Global content delivery network
• Versioning: File versioning and lifecycle management
• Security: Access control and encryption

Time Series Database

• Metrics Storage: System and application metrics
• Log Aggregation: Centralized log storage and analysis
• Analytics: Time-series analytics and reporting
• Retention Policies: Configurable data retention

Security Architecture

Network Security

• VPC Isolation: Virtual private cloud for network isolation
• Firewall Rules: Strict ingress and egress rules
• DDoS Protection: Distributed denial-of-service protection
• Network Monitoring: Real-time network traffic monitoring

Application Security

• Input Validation: Comprehensive input sanitization
• SQL Injection Prevention: Parameterized queries and ORM usage
• XSS Protection: Cross-site scripting prevention
• CSRF Protection: Cross-site request forgery prevention

Data Security

• Encryption at Rest: AES-256 encryption for stored data
• Encryption in Transit: TLS 1.3 for data in transit
• Key Management: Hardware security module (HSM) for key storage
• Data Masking: Sensitive data masking in non-production environments

Monitoring & Observability

Metrics Collection

• System Metrics: CPU, memory, disk, and network utilization
• Application Metrics: Request rates, response times, and error rates
• Business Metrics: User activity, feature usage, and revenue metrics
• Custom Metrics: Application-specific metrics and KPIs

Logging

• Structured Logging: JSON-formatted logs for easy parsing
• Log Aggregation: Centralized log collection and storage
• Log Analysis: Real-time log analysis and alerting
• Log Retention: Configurable log retention policies

Tracing

• Distributed Tracing: End-to-end request tracing across services
• Performance Analysis: Latency and bottleneck identification
• Dependency Mapping: Service dependency visualization
• Error Tracking: Detailed error tracking and debugging

Deployment Architecture

Container Orchestration

• Kubernetes: Container orchestration and management
• Helm Charts: Application packaging and deployment
• Service Mesh: Inter-service communication and security
• Auto-scaling: Horizontal and vertical pod autoscaling

CI/CD Pipeline

• Source Control: Git-based version control
• Build Automation: Automated build and testing
• Deployment Automation: Automated deployment to multiple environments
• Rollback Capabilities: Safe deployment rollback mechanisms

Environment Management

• Development: Local development environment
• Staging: Pre-production testing environment
• Production: Live production environment
• Disaster Recovery: Backup and recovery environment

Performance Optimization

Caching Strategy

• Multi-level Caching: Application, database, and CDN caching
• Cache Invalidation: Intelligent cache invalidation strategies
• Cache Warming: Proactive cache population
• Cache Monitoring: Cache hit rates and performance monitoring

Database Optimization

• Query Optimization: Optimized database queries and indexes
• Connection Pooling: Efficient database connection management
• Read Replicas: Read-only replicas for scaling read operations
• Partitioning: Database partitioning for large datasets

CDN Integration

• Global Distribution: Content delivery across multiple regions
• Edge Caching: Caching at edge locations for faster access
• Dynamic Content: Dynamic content acceleration
• Security: DDoS protection and security features

Scalability Design

Horizontal Scaling

• Stateless Services: Stateless service design for easy scaling
• Load Balancing: Intelligent load distribution
• Auto-scaling: Automatic scaling based on metrics
• Resource Optimization: Efficient resource utilization

Vertical Scaling

• Resource Monitoring: Continuous resource usage monitoring
• Performance Tuning: Application and infrastructure optimization
• Capacity Planning: Proactive capacity planning and scaling
• Cost Optimization: Cost-effective resource allocation

Next Steps

Ready to dive deeper into the platform? Explore these related topics:

1. Platform Overview - High-level platform overview
2. Key Features - Platform capabilities and features
3. Getting Started - Set up your development environment
4. Quick Start Guide - Build your first application