AlphaPulse Architecture Diagrams
This document provides comprehensive architectural diagrams for the AlphaPulse AI-powered algorithmic trading system using C4 model, data flow diagrams, sequence diagrams, and other visualization methods.
Table of Contents
- C4 Model Diagrams
- Data Flow Diagrams
- Sequence Diagrams
- Deployment Diagram
- State Diagrams
- Entity Relationship Diagram
C4 Model Diagrams
Level 1: System Context
C4Context
title System Context diagram for AlphaPulse Trading System
Person(trader, "Trader", "Human trader or investor using the system")
Person(admin, "System Admin", "Manages and monitors the system")
System(alphapulse, "AlphaPulse", "AI-powered algorithmic trading system that operates as an automated hedge fund")
System_Ext(exchanges, "Cryptocurrency Exchanges", "Trading venues (Binance, Coinbase, etc.)")
System_Ext(dataProviders, "Market Data Providers", "Real-time and historical market data")
System_Ext(newsAPIs, "News & Sentiment APIs", "Financial news and social sentiment data")
System_Ext(fundamentalData, "Fundamental Data Sources", "Company financials, economic indicators")
System_Ext(monitoring, "Monitoring Systems", "Prometheus, Grafana, AlertManager")
Rel(trader, alphapulse, "Configures strategies, monitors performance", "HTTPS/WebSocket")
Rel(admin, alphapulse, "Manages system, handles alerts", "HTTPS/SSH")
Rel(alphapulse, exchanges, "Executes trades, fetches prices", "REST/WebSocket")
Rel(dataProviders, alphapulse, "Provides market data", "REST/WebSocket")
Rel(newsAPIs, alphapulse, "Provides news and sentiment", "REST")
Rel(fundamentalData, alphapulse, "Provides fundamental data", "REST")
Rel(alphapulse, monitoring, "Exports metrics and logs", "Prometheus/Loki")
Level 2: Container Diagram
C4Container
title Container diagram for AlphaPulse Trading System
Person(trader, "Trader", "Human trader or investor")
Person(admin, "System Admin", "System administrator")
Container_Boundary(alphapulse, "AlphaPulse System") {
Container(web, "Web Dashboard", "React, TypeScript", "Trading interface and monitoring dashboard")
Container(api, "API Gateway", "FastAPI, Python", "REST API and WebSocket server")
Container(tradingEngine, "Trading Engine", "Python", "Core trading logic and orchestration")
Container(agents, "AI Trading Agents", "Python, PyTorch", "6 specialized trading agents")
Container(riskMgmt, "Risk Management", "Python", "Position sizing, stop-loss, risk controls")
Container(portfolio, "Portfolio Manager", "Python", "Portfolio optimization and allocation")
Container(execution, "Execution Engine", "Python, CCXT", "Order management and execution")
Container(dataPipeline, "Data Pipeline", "Python", "Real-time data processing")
Container(ml, "ML Services", "Python, PyTorch", "RL agents and ML models")
Container(monitoring, "Monitoring Service", "Python", "Metrics collection and alerting")
ContainerDb(timeseries, "TimescaleDB", "PostgreSQL", "Time-series market data")
ContainerDb(operational, "PostgreSQL", "PostgreSQL", "System state and configuration")
ContainerDb(redis, "Redis Cache", "Redis", "Real-time data cache")
}
System_Ext(exchanges, "Exchanges", "Trading venues")
System_Ext(dataFeeds, "Data Feeds", "Market data providers")
System_Ext(prometheus, "Prometheus", "Metrics storage")
Rel(trader, web, "Uses", "HTTPS")
Rel(web, api, "Makes API calls", "HTTPS/WSS")
Rel(api, tradingEngine, "Forwards requests", "gRPC")
Rel(tradingEngine, agents, "Orchestrates", "Internal")
Rel(tradingEngine, riskMgmt, "Validates trades", "Internal")
Rel(tradingEngine, portfolio, "Optimizes allocation", "Internal")
Rel(tradingEngine, execution, "Executes trades", "Internal")
Rel(agents, dataPipeline, "Consumes data", "Internal")
Rel(dataPipeline, redis, "Caches data", "TCP")
Rel(dataPipeline, timeseries, "Stores history", "TCP")
Rel(execution, exchanges, "Sends orders", "HTTPS/WSS")
Rel(dataFeeds, dataPipeline, "Streams data", "WSS")
Rel(monitoring, prometheus, "Exports metrics", "HTTP")
Rel(ml, agents, "Provides models", "Internal")
Level 3: Component Diagrams
Trading Agents Component Diagram
C4Component
title Component diagram for AI Trading Agents
Container_Boundary(agents, "AI Trading Agents Container") {
Component(orchestrator, "Agent Orchestrator", "Python", "Coordinates agent execution")
Component(technical, "Technical Agent", "Python", "Technical analysis signals")
Component(fundamental, "Fundamental Agent", "Python", "Value and financial analysis")
Component(sentiment, "Sentiment Agent", "Python, NLP", "News and social sentiment")
Component(value, "Value Agent", "Python", "Long-term value investing")
Component(activist, "Activist Agent", "Python", "Event-driven strategies")
Component(buffett, "Buffett Agent", "Python", "Warren Buffett style analysis")
Component(signalAgg, "Signal Aggregator", "Python", "Combines and weights signals")
Component(confidence, "Confidence Scorer", "Python", "Calculates signal confidence")
}
Container(dataPipeline, "Data Pipeline", "Python", "Market data provider")
Container(ml, "ML Services", "Python", "ML model inference")
Container(riskMgmt, "Risk Management", "Python", "Risk validation")
Rel(orchestrator, technical, "Executes", "Internal call")
Rel(orchestrator, fundamental, "Executes", "Internal call")
Rel(orchestrator, sentiment, "Executes", "Internal call")
Rel(orchestrator, value, "Executes", "Internal call")
Rel(orchestrator, activist, "Executes", "Internal call")
Rel(orchestrator, buffett, "Executes", "Internal call")
Rel(technical, dataPipeline, "Fetches OHLCV data", "API call")
Rel(fundamental, dataPipeline, "Fetches financials", "API call")
Rel(sentiment, dataPipeline, "Fetches news", "API call")
Rel(sentiment, ml, "Uses NLP models", "API call")
Rel(technical, signalAgg, "Provides signals", "Internal")
Rel(fundamental, signalAgg, "Provides signals", "Internal")
Rel(sentiment, signalAgg, "Provides signals", "Internal")
Rel(value, signalAgg, "Provides signals", "Internal")
Rel(activist, signalAgg, "Provides signals", "Internal")
Rel(buffett, signalAgg, "Provides signals", "Internal")
Rel(signalAgg, confidence, "Calculates confidence", "Internal")
Rel(confidence, riskMgmt, "Sends weighted signals", "API call")
Risk Management Component Diagram
C4Component
title Component diagram for Risk Management System
Container_Boundary(riskMgmt, "Risk Management Container") {
Component(riskEngine, "Risk Engine", "Python", "Core risk calculation engine")
Component(positionSizer, "Position Sizer", "Python", "Kelly Criterion & fixed fractional sizing")
Component(stopLoss, "Stop Loss Manager", "Python", "Dynamic stop-loss calculation")
Component(leverage, "Leverage Controller", "Python", "Manages position leverage")
Component(drawdown, "Drawdown Monitor", "Python", "Tracks and limits drawdowns")
Component(correlation, "Correlation Analyzer", "Python", "Portfolio correlation analysis")
Component(var, "VaR Calculator", "Python", "Value at Risk calculations")
Component(stress, "Stress Tester", "Python", "Scenario analysis")
Component(limits, "Limit Enforcer", "Python", "Enforces risk limits")
}
Container(portfolio, "Portfolio Manager", "Python", "Portfolio state")
Container(execution, "Execution Engine", "Python", "Trade executor")
Container(monitoring, "Monitoring", "Python", "Alerting system")
Rel(riskEngine, positionSizer, "Calculates size", "Internal")
Rel(riskEngine, stopLoss, "Sets stops", "Internal")
Rel(riskEngine, leverage, "Checks leverage", "Internal")
Rel(riskEngine, drawdown, "Monitors DD", "Internal")
Rel(riskEngine, correlation, "Analyzes", "Internal")
Rel(riskEngine, var, "Calculates VaR", "Internal")
Rel(riskEngine, stress, "Runs scenarios", "Internal")
Rel(limits, riskEngine, "Provides limits", "Internal")
Rel(portfolio, riskEngine, "Provides positions", "API call")
Rel(riskEngine, execution, "Approves trades", "API call")
Rel(riskEngine, monitoring, "Sends alerts", "Event")
Data Flow Diagrams
Real-time Data Processing Flow
flowchart TB
subgraph External["External Data Sources"]
EX[Exchange APIs]
NEWS[News APIs]
FUND[Fundamental Data]
SOCIAL[Social Media]
end
subgraph DataPipeline["Data Pipeline Layer"]
FETCH[Data Fetchers]
NORM[Normalizers]
VALID[Validators]
CACHE[Redis Cache]
QUEUE[Message Queue]
end
subgraph Processing["Processing Layer"]
TECH[Technical Indicators]
SENT[Sentiment Analysis]
FUND_PROC[Fundamental Processing]
ML_FEAT[Feature Engineering]
end
subgraph Storage["Storage Layer"]
TS[(TimescaleDB)]
PG[(PostgreSQL)]
S3[S3 Compatible Storage]
end
subgraph Consumers["Data Consumers"]
AGENTS[Trading Agents]
RISK[Risk Management]
DASH[Dashboard]
BACK[Backtesting]
end
EX -->|WebSocket/REST| FETCH
NEWS -->|REST| FETCH
FUND -->|REST| FETCH
SOCIAL -->|REST| FETCH
FETCH --> NORM
NORM --> VALID
VALID --> CACHE
VALID --> QUEUE
QUEUE --> TECH
QUEUE --> SENT
QUEUE --> FUND_PROC
QUEUE --> ML_FEAT
TECH --> TS
SENT --> PG
FUND_PROC --> PG
ML_FEAT --> S3
CACHE --> AGENTS
CACHE --> RISK
CACHE --> DASH
TS --> BACK
PG --> AGENTS
S3 --> AGENTS
Trading Signal Flow
flowchart LR
subgraph Agents["AI Trading Agents"]
TA[Technical Agent]
FA[Fundamental Agent]
SA[Sentiment Agent]
VA[Value Agent]
AA[Activist Agent]
BA[Buffett Agent]
end
subgraph Aggregation["Signal Processing"]
AGG[Signal Aggregator]
CONF[Confidence Scorer]
WEIGHT[Weight Calculator]
end
subgraph Risk["Risk Layer"]
RCHECK[Risk Checker]
PSIZE[Position Sizer]
STOP[Stop Loss Calc]
end
subgraph Portfolio["Portfolio Layer"]
OPT[Portfolio Optimizer]
ALLOC[Asset Allocator]
REBAL[Rebalancer]
end
subgraph Execution["Execution Layer"]
OBOOK[Order Book Analyzer]
OMAN[Order Manager]
EXEC[Trade Executor]
end
TA -->|Technical Signals| AGG
FA -->|Value Signals| AGG
SA -->|Sentiment Signals| AGG
VA -->|Value Signals| AGG
AA -->|Event Signals| AGG
BA -->|Quality Signals| AGG
AGG --> CONF
CONF --> WEIGHT
WEIGHT --> RCHECK
RCHECK -->|Approved| PSIZE
RCHECK -->|Rejected| AGG
PSIZE --> STOP
STOP --> OPT
OPT --> ALLOC
ALLOC --> REBAL
REBAL --> OBOOK
OBOOK --> OMAN
OMAN --> EXEC
EXEC -->|Feedback| AGG
Sequence Diagrams
Trade Execution Sequence
sequenceDiagram
participant User
participant Dashboard
participant API
participant TradingEngine
participant Agents
participant RiskMgmt
participant Portfolio
participant Execution
participant Exchange
User->>Dashboard: Configure strategy
Dashboard->>API: POST /strategies
API->>TradingEngine: Create strategy
loop Trading Loop
TradingEngine->>Agents: Request signals
Agents->>Agents: Analyze market
Agents-->>TradingEngine: Return signals
TradingEngine->>RiskMgmt: Validate signals
RiskMgmt->>RiskMgmt: Check limits
RiskMgmt->>RiskMgmt: Calculate position size
RiskMgmt-->>TradingEngine: Approved trades
TradingEngine->>Portfolio: Optimize allocation
Portfolio->>Portfolio: Run optimization
Portfolio-->>TradingEngine: Optimal weights
TradingEngine->>Execution: Execute trades
Execution->>Exchange: Place orders
Exchange-->>Execution: Order confirmation
Execution-->>TradingEngine: Execution report
TradingEngine->>Dashboard: Update status
Dashboard->>User: Show results
end
Real-time Data Processing Sequence
sequenceDiagram
participant Exchange
participant DataPipeline
participant Cache
participant TimescaleDB
participant Agents
participant Dashboard
Exchange->>DataPipeline: WebSocket stream
loop Real-time Processing
DataPipeline->>DataPipeline: Normalize data
DataPipeline->>DataPipeline: Validate data
par Parallel Processing
DataPipeline->>Cache: Store in Redis
and
DataPipeline->>TimescaleDB: Store history
end
Cache-->>Agents: Broadcast update
Cache-->>Dashboard: Push update
Agents->>Agents: Process new data
Dashboard->>Dashboard: Update UI
end
Agent Decision Making Sequence
sequenceDiagram
participant Orchestrator
participant TechnicalAgent
participant FundamentalAgent
participant SentimentAgent
participant MLService
participant Aggregator
Orchestrator->>TechnicalAgent: Request analysis
Orchestrator->>FundamentalAgent: Request analysis
Orchestrator->>SentimentAgent: Request analysis
par Parallel Analysis
TechnicalAgent->>TechnicalAgent: Calculate indicators
TechnicalAgent->>TechnicalAgent: Identify patterns
and
FundamentalAgent->>FundamentalAgent: Analyze financials
FundamentalAgent->>FundamentalAgent: Calculate ratios
and
SentimentAgent->>MLService: Get NLP analysis
MLService-->>SentimentAgent: Sentiment scores
SentimentAgent->>SentimentAgent: Process sentiment
end
TechnicalAgent-->>Aggregator: Technical signals
FundamentalAgent-->>Aggregator: Fundamental signals
SentimentAgent-->>Aggregator: Sentiment signals
Aggregator->>Aggregator: Weight signals
Aggregator->>Aggregator: Calculate confidence
Aggregator-->>Orchestrator: Final signal
Deployment Diagram
flowchart TB
subgraph Cloud["Cloud Infrastructure"]
subgraph K8s["Kubernetes Cluster"]
subgraph Services["Service Pods"]
API[API Gateway<br/>3 replicas]
TE[Trading Engine<br/>2 replicas]
DP[Data Pipeline<br/>3 replicas]
MON[Monitoring<br/>2 replicas]
end
subgraph Agents["Agent Pods"]
AG1[Agent Set 1<br/>6 agents]
AG2[Agent Set 2<br/>6 agents]
end
subgraph ML["ML Pods"]
MLS[ML Service<br/>GPU enabled]
RL[RL Training<br/>GPU enabled]
end
end
subgraph Data["Data Layer"]
subgraph DBCluster["Database Cluster"]
TS1[(TimescaleDB Primary)]
TS2[(TimescaleDB Replica)]
PG1[(PostgreSQL Primary)]
PG2[(PostgreSQL Replica)]
end
subgraph Cache["Cache Layer"]
R1[Redis Primary]
R2[Redis Replica]
end
S3[S3 Storage<br/>Model artifacts]
end
LB[Load Balancer]
CDN[CDN<br/>Static assets]
end
subgraph External["External Services"]
EX[Exchange APIs]
DATA[Data Providers]
PROM[Prometheus]
GRAF[Grafana]
end
subgraph Users["Users"]
TRADER[Traders]
ADMIN[Admins]
end
TRADER --> CDN
ADMIN --> LB
CDN --> LB
LB --> API
API --> TE
TE --> AG1
TE --> AG2
AG1 --> MLS
AG2 --> MLS
DP --> R1
DP --> TS1
TE --> PG1
MLS --> S3
MON --> PROM
PROM --> GRAF
EX --> DP
DATA --> DP
State Diagrams
Order Lifecycle State Machine
stateDiagram-v2
[*] --> SignalGenerated
SignalGenerated --> RiskValidation
RiskValidation --> Rejected: Risk check failed
RiskValidation --> Approved: Risk check passed
Rejected --> [*]
Approved --> PortfolioOptimization
PortfolioOptimization --> OrderCreation
OrderCreation --> OrderPlaced
OrderPlaced --> PartiallyFilled: Partial execution
OrderPlaced --> Filled: Full execution
OrderPlaced --> Cancelled: User cancelled
OrderPlaced --> Failed: Exchange rejected
PartiallyFilled --> Filled: Remaining filled
PartiallyFilled --> Cancelled: Timeout/User action
Filled --> PositionOpen
PositionOpen --> PositionClosed: Exit signal/Stop loss
PositionClosed --> [*]
Failed --> [*]
Cancelled --> [*]
System Health State Machine
stateDiagram-v2
[*] --> Initializing
Initializing --> HealthCheck
HealthCheck --> Healthy: All checks pass
HealthCheck --> Degraded: Some checks fail
HealthCheck --> Critical: Critical checks fail
Healthy --> Monitoring: Normal operation
Monitoring --> Healthy: Periodic check OK
Monitoring --> Warning: Minor issues
Monitoring --> Degraded: Service issues
Warning --> Monitoring: Issues resolved
Warning --> Degraded: Issues escalate
Degraded --> Recovery: Auto-healing
Degraded --> Critical: Further degradation
Recovery --> HealthCheck: Recovery complete
Critical --> EmergencyStop: Safety shutdown
EmergencyStop --> [*]
Entity Relationship Diagram
erDiagram
TRADER ||--o{ STRATEGY : creates
STRATEGY ||--o{ POSITION : generates
POSITION ||--o{ ORDER : contains
ORDER ||--o{ EXECUTION : results_in
STRATEGY ||--o{ AGENT_CONFIG : uses
AGENT_CONFIG ||--|| AGENT : configures
POSITION ||--|| ASSET : trades
ASSET ||--o{ MARKET_DATA : has
ASSET ||--o{ FUNDAMENTAL_DATA : has
ORDER ||--|| EXCHANGE : sent_to
EXCHANGE ||--o{ EXECUTION : processes
POSITION ||--o{ RISK_METRIC : tracked_by
RISK_METRIC ||--|| RISK_LIMIT : constrained_by
EXECUTION ||--o{ TRANSACTION : creates
TRANSACTION ||--|| PORTFOLIO : affects
PORTFOLIO ||--o{ PERFORMANCE_METRIC : measured_by
TRADER {
string trader_id PK
string name
string email
json preferences
timestamp created_at
}
STRATEGY {
string strategy_id PK
string trader_id FK
string name
json configuration
string status
timestamp created_at
}
POSITION {
string position_id PK
string strategy_id FK
string asset_id FK
decimal quantity
decimal entry_price
decimal current_price
decimal pnl
string status
timestamp opened_at
timestamp closed_at
}
ORDER {
string order_id PK
string position_id FK
string exchange_id FK
string type
string side
decimal quantity
decimal price
string status
timestamp created_at
}
ASSET {
string asset_id PK
string symbol
string name
string type
string exchange
json metadata
}
MARKET_DATA {
string asset_id FK
timestamp time
decimal open
decimal high
decimal low
decimal close
decimal volume
}
Architecture Decision Records (ADR)
ADR-001: Microservice vs Monolithic Architecture
Status: Accepted
Context: Need to decide between microservice and monolithic architecture for AlphaPulse.
Decision: Hybrid approach - monolithic core with service boundaries that can be easily extracted to microservices.
Consequences:
- Easier initial development and deployment
- Clear service boundaries for future scaling
- Can extract services as needed without major refactoring
ADR-002: Time-Series Database Selection
Status: Accepted
Context: Need specialized time-series storage for market data.
Decision: TimescaleDB (PostgreSQL extension)
Consequences:
- Native PostgreSQL compatibility
- Excellent time-series performance
- Built-in compression and retention policies
- SQL interface familiar to developers
ADR-003: Message Queue vs Direct Communication
Status: Accepted
Context: Inter-service communication pattern selection.
Decision: Direct API calls with Redis pub/sub for real-time events
Consequences:
- Lower latency for critical paths
- Simpler debugging and monitoring
- Redis provides event broadcasting when needed
- Can add message queue later if needed
Performance Architecture
Latency-Critical Path
flowchart LR
subgraph Hot Path ["< 10ms latency"]
MD[Market Data] -->|WebSocket| CACHE[Redis Cache]
CACHE --> AGENTS[Trading Agents]
AGENTS --> RISK[Risk Check]
RISK --> EXEC[Execution]
end
subgraph Async Path ["Async processing"]
CACHE -.-> TS[(TimescaleDB)]
CACHE -.-> ANALYTICS[Analytics]
EXEC -.-> REPORTING[Reporting]
end
style Hot Path fill:#ff9999
style Async Path fill:#99ccff
Caching Strategy
flowchart TB
subgraph L1["L1 Cache - In-Memory"]
PROC[Process Cache<br/>~1ms latency]
end
subgraph L2["L2 Cache - Redis"]
REDIS[Redis Cluster<br/>~5ms latency]
end
subgraph L3["L3 Storage - Database"]
DB[(TimescaleDB<br/>~20ms latency)]
end
REQUEST[Data Request] --> PROC
PROC -->|Miss| REDIS
REDIS -->|Miss| DB
DB --> REDIS
REDIS --> PROC
PROC --> RESPONSE[Response]
Security Architecture
flowchart TB
subgraph External["External Layer"]
USER[Users]
API[API Clients]
end
subgraph Edge["Edge Security"]
WAF[Web Application Firewall]
DDOS[DDoS Protection]
LB[Load Balancer<br/>SSL Termination]
end
subgraph App["Application Layer"]
AUTH[Auth Service<br/>JWT/OAuth2]
GATEWAY[API Gateway<br/>Rate Limiting]
RBAC[RBAC Engine]
end
subgraph Internal["Internal Services"]
SERVICES[Trading Services]
SECRETS[Secret Manager<br/>Vault]
AUDIT[Audit Logger]
end
subgraph Data["Data Layer"]
ENC[Encryption at Rest]
DB[(Encrypted Database)]
end
USER --> WAF
API --> WAF
WAF --> DDOS
DDOS --> LB
LB --> AUTH
AUTH --> GATEWAY
GATEWAY --> RBAC
RBAC --> SERVICES
SERVICES --> SECRETS
SERVICES --> AUDIT
SERVICES --> ENC
ENC --> DB
Monitoring and Observability
flowchart LR
subgraph Apps["Applications"]
API[API Service]
TRADING[Trading Engine]
AGENTS[AI Agents]
EXEC[Execution Service]
end
subgraph Telemetry["Telemetry Collection"]
METRICS[Prometheus Metrics]
LOGS[Structured Logs]
TRACES[Distributed Traces]
EVENTS[Business Events]
end
subgraph Storage["Storage & Processing"]
PROM[(Prometheus)]
LOKI[(Loki)]
TEMPO[(Tempo)]
KAFKA[Kafka]
end
subgraph Visualization["Visualization & Alerting"]
GRAF[Grafana]
ALERT[AlertManager]
SLACK[Slack]
PAGER[PagerDuty]
end
Apps --> METRICS
Apps --> LOGS
Apps --> TRACES
Apps --> EVENTS
METRICS --> PROM
LOGS --> LOKI
TRACES --> TEMPO
EVENTS --> KAFKA
PROM --> GRAF
LOKI --> GRAF
TEMPO --> GRAF
KAFKA --> GRAF
GRAF --> ALERT
ALERT --> SLACK
ALERT --> PAGER
This document provides a comprehensive view of the AlphaPulse architecture using various diagramming techniques. The diagrams cover:
- C4 Model: System context, containers, and components
- Data Flows: How data moves through the system
- Sequences: Step-by-step interaction flows
- Deployment: Infrastructure and deployment topology
- State Machines: Order and system state transitions
- Entity Relationships: Database schema overview
- Architecture Decisions: Key design choices
- Performance: Latency-critical paths and caching
- Security: Security layers and controls
- Monitoring: Observability architecture
Each diagram provides a different perspective on the system, helping developers, operators, and stakeholders understand how AlphaPulse works at various levels of abstraction.