deleted a lot of the stuff
This commit is contained in:
parent
d22f7aafa0
commit
3e451558ac
173 changed files with 1313 additions and 30205 deletions
|
|
@ -1,248 +0,0 @@
|
|||
# Stock Bot Platform - Service Progress Tracker
|
||||
|
||||
*Last Updated: June 3, 2025*
|
||||
|
||||
## Overall Platform Progress: 68%
|
||||
|
||||
---
|
||||
|
||||
## 🗄️ **DATABASE SERVICES**
|
||||
|
||||
### PostgreSQL (Primary Database) - 85%
|
||||
- ✅ Configuration module complete
|
||||
- ✅ Environment variables standardized (POSTGRES_*)
|
||||
- ✅ Connection pooling configured
|
||||
- ✅ SSL/TLS support
|
||||
- ⚠️ Migration system needs setup
|
||||
- ❌ Backup/restore automation pending
|
||||
- ❌ Performance monitoring integration
|
||||
|
||||
### QuestDB (Time-Series) - 75%
|
||||
- ✅ Configuration module complete
|
||||
- ✅ HTTP and PostgreSQL wire protocol ports
|
||||
- ✅ InfluxDB line protocol support
|
||||
- ✅ Docker integration
|
||||
- ⚠️ Schema design for OHLCV data pending
|
||||
- ❌ Data retention policies not configured
|
||||
- ❌ Monitoring dashboards missing
|
||||
|
||||
### MongoDB (Document Store) - 70%
|
||||
- ✅ Configuration module complete
|
||||
- ✅ Connection with authentication
|
||||
- ✅ Database and collection setup
|
||||
- ⚠️ Indexes for performance optimization needed
|
||||
- ❌ Aggregation pipelines for analytics
|
||||
- ❌ Full-text search configuration
|
||||
|
||||
### Dragonfly (Cache/Redis) - 90%
|
||||
- ✅ Configuration module complete
|
||||
- ✅ Connection pooling
|
||||
- ✅ TLS support
|
||||
- ✅ Cluster mode support
|
||||
- ✅ Memory management
|
||||
- ⚠️ Cache strategies need implementation
|
||||
- ❌ Pub/sub for real-time events
|
||||
|
||||
---
|
||||
|
||||
## 📊 **MONITORING & OBSERVABILITY**
|
||||
|
||||
### Prometheus (Metrics) - 60%
|
||||
- ✅ Configuration module complete
|
||||
- ✅ Docker service setup
|
||||
- ⚠️ Custom metrics collection pending
|
||||
- ❌ Alerting rules not configured
|
||||
- ❌ Service discovery setup
|
||||
- ❌ Retention policies
|
||||
|
||||
### Grafana (Dashboards) - 55%
|
||||
- ✅ Configuration module complete
|
||||
- ✅ Docker service setup
|
||||
- ✅ Prometheus data source
|
||||
- ⚠️ Trading-specific dashboards needed
|
||||
- ❌ Alert notifications
|
||||
- ❌ User management
|
||||
|
||||
### Loki (Logs) - 40%
|
||||
- ✅ Configuration module complete
|
||||
- ⚠️ Log aggregation setup pending
|
||||
- ❌ Log parsing rules
|
||||
- ❌ Integration with application logs
|
||||
- ❌ Log retention policies
|
||||
|
||||
---
|
||||
|
||||
## 🔧 **CONFIGURATION MANAGEMENT**
|
||||
|
||||
### Config Library (@stock-bot/config) - 95%
|
||||
- ✅ Migrated from Zod to Envalid
|
||||
- ✅ All service configurations complete
|
||||
- ✅ Environment variable validation
|
||||
- ✅ TypeScript type safety
|
||||
- ✅ Example documentation
|
||||
- ⚠️ Runtime configuration reloading
|
||||
|
||||
### Environment Management - 80%
|
||||
- ✅ Development environment (.env)
|
||||
- ✅ Docker environment (.env.docker)
|
||||
- ✅ Production templates
|
||||
- ⚠️ Secrets management (HashiCorp Vault?)
|
||||
- ❌ Environment-specific overrides
|
||||
|
||||
---
|
||||
|
||||
## 📈 **TRADING SERVICES**
|
||||
|
||||
### Risk Management - 30%
|
||||
- ✅ Risk configuration module
|
||||
- ✅ Position sizing parameters
|
||||
- ✅ Stop-loss/take-profit settings
|
||||
- ❌ Real-time risk calculation engine
|
||||
- ❌ Portfolio exposure monitoring
|
||||
- ❌ Circuit breaker implementation
|
||||
|
||||
### Data Providers - 45%
|
||||
- ✅ Configuration for multiple providers
|
||||
- ✅ Alpaca integration setup
|
||||
- ✅ Polygon.io configuration
|
||||
- ⚠️ Rate limiting implementation
|
||||
- ❌ Data normalization layer
|
||||
- ❌ Failover mechanisms
|
||||
|
||||
### Order Management - 0%
|
||||
- ❌ Order placement system
|
||||
- ❌ Order status tracking
|
||||
- ❌ Fill reporting
|
||||
- ❌ Position management
|
||||
- ❌ Trade execution logic
|
||||
|
||||
### Strategy Engine - 0%
|
||||
- ❌ Strategy framework
|
||||
- ❌ Backtesting engine
|
||||
- ❌ Live trading execution
|
||||
- ❌ Performance analytics
|
||||
- ❌ Strategy configuration
|
||||
|
||||
---
|
||||
|
||||
## 🏗️ **INFRASTRUCTURE**
|
||||
|
||||
### Docker Services - 85%
|
||||
- ✅ All database containers configured
|
||||
- ✅ Monitoring stack setup
|
||||
- ✅ Network configuration
|
||||
- ✅ Volume management
|
||||
- ⚠️ Health checks need refinement
|
||||
- ❌ Production orchestration (K8s?)
|
||||
|
||||
### Build System - 70%
|
||||
- ✅ Nx monorepo setup
|
||||
- ✅ TypeScript configuration
|
||||
- ✅ Library build processes
|
||||
- ⚠️ Testing framework setup
|
||||
- ❌ CI/CD pipeline
|
||||
- ❌ Deployment automation
|
||||
|
||||
---
|
||||
|
||||
## 🧪 **TESTING & QUALITY**
|
||||
|
||||
### Unit Testing - 10%
|
||||
- ⚠️ Test framework selection needed
|
||||
- ❌ Config library tests
|
||||
- ❌ Service layer tests
|
||||
- ❌ Integration tests
|
||||
- ❌ End-to-end tests
|
||||
|
||||
### Code Quality - 60%
|
||||
- ✅ TypeScript strict mode
|
||||
- ✅ ESLint configuration
|
||||
- ✅ Prettier formatting
|
||||
- ❌ Code coverage reporting
|
||||
- ❌ Security scanning
|
||||
|
||||
---
|
||||
|
||||
## 🔐 **SECURITY**
|
||||
|
||||
### Authentication & Authorization - 0%
|
||||
- ❌ User authentication system
|
||||
- ❌ API key management
|
||||
- ❌ Role-based access control
|
||||
- ❌ Session management
|
||||
- ❌ OAuth integration
|
||||
|
||||
### Data Security - 20%
|
||||
- ✅ Database connection encryption
|
||||
- ✅ Environment variable protection
|
||||
- ❌ Data encryption at rest
|
||||
- ❌ API rate limiting
|
||||
- ❌ Audit logging
|
||||
|
||||
---
|
||||
|
||||
## 📋 **IMMEDIATE NEXT STEPS**
|
||||
|
||||
### High Priority (Next 2 weeks)
|
||||
1. **Complete PostgreSQL setup** - Migrations, schemas
|
||||
2. **Implement basic logging integration** - Connect services to Loki
|
||||
3. **Create Grafana dashboards** - System and business metrics
|
||||
4. **Setup testing framework** - Jest/Vitest configuration
|
||||
5. **Risk management engine** - Core calculation logic
|
||||
|
||||
### Medium Priority (Next month)
|
||||
1. **Data provider integration** - Real market data ingestion
|
||||
2. **QuestDB schema design** - Time-series data structure
|
||||
3. **MongoDB indexing** - Performance optimization
|
||||
4. **CI/CD pipeline** - Automated testing and deployment
|
||||
5. **Basic order management** - Place and track orders
|
||||
|
||||
### Low Priority (Next quarter)
|
||||
1. **Strategy engine framework** - Backtesting and live trading
|
||||
2. **Security implementation** - Authentication and authorization
|
||||
3. **Production deployment** - Kubernetes or cloud setup
|
||||
4. **Advanced monitoring** - Custom metrics and alerting
|
||||
5. **Performance optimization** - System tuning and scaling
|
||||
|
||||
---
|
||||
|
||||
## 📊 **SERVICE COMPLETION SUMMARY**
|
||||
|
||||
| Service Category | Progress | Status |
|
||||
|------------------|----------|---------|
|
||||
| Configuration | 95% | ✅ Nearly Complete |
|
||||
| Databases | 77% | 🟡 Good Progress |
|
||||
| Monitoring | 52% | 🟡 Moderate Progress |
|
||||
| Infrastructure | 78% | 🟡 Good Progress |
|
||||
| Trading Services | 19% | 🔴 Early Stage |
|
||||
| Testing | 35% | 🔴 Needs Attention |
|
||||
| Security | 10% | 🔴 Critical Gap |
|
||||
|
||||
**Legend:**
|
||||
- ✅ Complete (90-100%)
|
||||
- 🟡 In Progress (50-89%)
|
||||
- 🔴 Early Stage (0-49%)
|
||||
- ⚠️ Partially Complete
|
||||
- ❌ Not Started
|
||||
|
||||
---
|
||||
|
||||
## 🎯 **SUCCESS METRICS**
|
||||
|
||||
### Technical Metrics
|
||||
- [ ] All services start without errors
|
||||
- [ ] Database connections stable
|
||||
- [ ] Monitoring dashboards operational
|
||||
- [ ] Tests achieve >90% coverage
|
||||
- [ ] Build time < 2 minutes
|
||||
|
||||
### Business Metrics
|
||||
- [ ] Can place live trades
|
||||
- [ ] Risk management active
|
||||
- [ ] Real-time data ingestion
|
||||
- [ ] Performance tracking
|
||||
- [ ] Error rate < 0.1%
|
||||
|
||||
---
|
||||
|
||||
*This document is automatically updated as services reach completion milestones.*
|
||||
|
|
@ -1,27 +0,0 @@
|
|||
# Core Services
|
||||
|
||||
Core services provide fundamental infrastructure and foundational capabilities for the stock trading platform.
|
||||
|
||||
## Services
|
||||
|
||||
### Market Data Gateway
|
||||
- **Purpose**: Real-time market data processing and distribution
|
||||
- **Key Functions**:
|
||||
- WebSocket streaming for live market data
|
||||
- Multi-source data aggregation (Alpaca, Yahoo Finance, etc.)
|
||||
- Data caching and normalization
|
||||
- Rate limiting and connection management
|
||||
- Error handling and reconnection logic
|
||||
|
||||
### Risk Guardian
|
||||
- **Purpose**: Real-time risk monitoring and controls
|
||||
- **Key Functions**:
|
||||
- Position monitoring and risk threshold enforcement
|
||||
- Portfolio risk assessment and alerting
|
||||
- Real-time risk metric calculations
|
||||
- Automated risk controls and circuit breakers
|
||||
- Risk reporting and compliance monitoring
|
||||
|
||||
## Architecture
|
||||
|
||||
Core services form the backbone of the trading platform, providing essential data flow and risk management capabilities that all other services depend upon. They handle the most critical and time-sensitive operations requiring high reliability and performance.
|
||||
|
|
@ -1,82 +0,0 @@
|
|||
# Market Data Gateway
|
||||
|
||||
## Overview
|
||||
The Market Data Gateway (MDG) service serves as the central hub for real-time market data processing and distribution within the stock-bot platform. It acts as the intermediary between external market data providers and internal platform services, ensuring consistent, normalized, and reliable market data delivery.
|
||||
|
||||
## Key Features
|
||||
|
||||
### Real-time Data Processing
|
||||
- **WebSocket Streaming**: Provides low-latency data streams for market updates
|
||||
- **Multi-source Aggregation**: Integrates data from multiple providers (Alpaca, Yahoo Finance, etc.)
|
||||
- **Normalized Data Model**: Transforms varied provider formats into a unified platform data model
|
||||
- **Subscription Management**: Allows services to subscribe to specific data streams
|
||||
|
||||
### Data Quality Management
|
||||
- **Validation & Sanitization**: Ensures data integrity through validation rules
|
||||
- **Anomaly Detection**: Identifies unusual price movements or data issues
|
||||
- **Gap Filling**: Interpolation strategies for missing data points
|
||||
- **Data Reconciliation**: Cross-validates data from multiple sources
|
||||
|
||||
### Performance Optimization
|
||||
- **Caching Layer**: In-memory cache for frequently accessed data
|
||||
- **Rate Limiting**: Protects against API quota exhaustion
|
||||
- **Connection Pooling**: Efficiently manages provider connections
|
||||
- **Compression**: Minimizes data transfer size for bandwidth efficiency
|
||||
|
||||
### Operational Resilience
|
||||
- **Automatic Reconnection**: Handles provider disconnections gracefully
|
||||
- **Circuit Breaking**: Prevents cascade failures during outages
|
||||
- **Failover Mechanisms**: Switches to alternative data sources when primary sources fail
|
||||
- **Health Monitoring**: Self-reports service health metrics
|
||||
|
||||
## Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Alpaca Markets API (primary data source)
|
||||
- Yahoo Finance API (secondary data source)
|
||||
- Potential future integrations with IEX, Polygon, etc.
|
||||
|
||||
### Downstream Consumers
|
||||
- Strategy Orchestrator
|
||||
- Risk Guardian
|
||||
- Trading Dashboard
|
||||
- Data Persistence Layer
|
||||
|
||||
## Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Messaging**: WebSockets for real-time streaming
|
||||
- **Caching**: Redis for shared cache
|
||||
- **Metrics**: Prometheus metrics for monitoring
|
||||
- **Configuration**: Environment-based with runtime updates
|
||||
|
||||
### Architecture Pattern
|
||||
- Event-driven microservice with publisher-subscriber model
|
||||
- Horizontally scalable to handle increased data volumes
|
||||
- Stateless design with external state management
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Error Handling
|
||||
- Detailed error classification and handling strategy
|
||||
- Graceful degradation during partial outages
|
||||
- Comprehensive error logging with context
|
||||
|
||||
### Testing Strategy
|
||||
- Unit tests for data transformation logic
|
||||
- Integration tests with mock data providers
|
||||
- Performance tests for throughput capacity
|
||||
- Chaos testing for resilience verification
|
||||
|
||||
### Observability
|
||||
- Detailed logs for troubleshooting
|
||||
- Performance metrics for optimization
|
||||
- Health checks for system monitoring
|
||||
- Tracing for request flow analysis
|
||||
|
||||
## Future Enhancements
|
||||
- Support for options and derivatives data
|
||||
- Real-time news and sentiment integration
|
||||
- Machine learning-based data quality improvements
|
||||
- Enhanced historical data query capabilities
|
||||
|
|
@ -1,84 +0,0 @@
|
|||
# Risk Guardian
|
||||
|
||||
## Overview
|
||||
The Risk Guardian service provides real-time risk monitoring and control mechanisms for the stock-bot platform. It serves as the protective layer that ensures trading activities remain within defined risk parameters, safeguarding the platform and its users from excessive market exposure and potential losses.
|
||||
|
||||
## Key Features
|
||||
|
||||
### Real-time Risk Monitoring
|
||||
- **Position Tracking**: Continuously monitors all open positions
|
||||
- **Risk Metric Calculation**: Calculates key risk metrics (VaR, volatility, exposure)
|
||||
- **Threshold Management**: Configurable risk thresholds with multiple severity levels
|
||||
- **Aggregated Risk Views**: Risk assessment at portfolio, strategy, and position levels
|
||||
|
||||
### Automated Risk Controls
|
||||
- **Pre-trade Validation**: Validates orders against risk limits before execution
|
||||
- **Circuit Breakers**: Automatically halts trading when thresholds are breached
|
||||
- **Position Liquidation**: Controlled unwinding of positions when necessary
|
||||
- **Trading Restrictions**: Enforces instrument, size, and frequency restrictions
|
||||
|
||||
### Risk Alerting
|
||||
- **Real-time Notifications**: Immediate alerts for threshold breaches
|
||||
- **Escalation Paths**: Multi-level alerting based on severity
|
||||
- **Alert History**: Maintains historical record of all risk events
|
||||
- **Custom Alert Rules**: Configurable alerting conditions and criteria
|
||||
|
||||
### Compliance Management
|
||||
- **Regulatory Reporting**: Assists with required regulatory reporting
|
||||
- **Audit Trails**: Comprehensive logging of risk-related decisions
|
||||
- **Rule-based Controls**: Implements compliance-driven trading restrictions
|
||||
- **Documentation**: Maintains evidence of risk control effectiveness
|
||||
|
||||
## Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Market Data Gateway (for price data)
|
||||
- Strategy Orchestrator (for active strategies)
|
||||
- Order Management System (for position tracking)
|
||||
|
||||
### Downstream Consumers
|
||||
- Trading Dashboard (for risk visualization)
|
||||
- Strategy Orchestrator (for trading restrictions)
|
||||
- Notification Service (for alerting)
|
||||
|
||||
## Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Database**: Time-series database for risk metrics
|
||||
- **Messaging**: Event-driven architecture with message bus
|
||||
- **Math Libraries**: Specialized libraries for risk calculations
|
||||
- **Caching**: In-memory risk state management
|
||||
|
||||
### Architecture Pattern
|
||||
- Reactive microservice with event sourcing
|
||||
- Command Query Responsibility Segregation (CQRS)
|
||||
- Rule engine for risk evaluation
|
||||
- Stateful service with persistence
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Risk Calculation Approach
|
||||
- Clear documentation of all risk formulas
|
||||
- Validation against industry standard calculations
|
||||
- Performance optimization for real-time processing
|
||||
- Regular backtesting of risk models
|
||||
|
||||
### Testing Strategy
|
||||
- Unit tests for risk calculation logic
|
||||
- Scenario-based testing for specific market conditions
|
||||
- Stress testing with extreme market movements
|
||||
- Performance testing for high-frequency updates
|
||||
|
||||
### Calibration Process
|
||||
- Documented process for risk model calibration
|
||||
- Historical data validation
|
||||
- Parameter sensitivity analysis
|
||||
- Regular recalibration schedule
|
||||
|
||||
## Future Enhancements
|
||||
- Machine learning for anomaly detection
|
||||
- Scenario analysis and stress testing
|
||||
- Custom risk models per strategy type
|
||||
- Enhanced visualization of risk exposures
|
||||
- Factor-based risk decomposition
|
||||
|
|
@ -1,43 +0,0 @@
|
|||
# Data Services
|
||||
|
||||
Data services manage data storage, processing, and discovery across the trading platform, providing structured access to market data, features, and metadata.
|
||||
|
||||
## Services
|
||||
|
||||
### Data Catalog
|
||||
- **Purpose**: Data asset management and discovery
|
||||
- **Key Functions**:
|
||||
- Data asset discovery and search capabilities
|
||||
- Metadata management and governance
|
||||
- Data lineage tracking
|
||||
- Schema registry and versioning
|
||||
- Data quality monitoring
|
||||
|
||||
### Data Processor
|
||||
- **Purpose**: Data transformation and processing pipelines
|
||||
- **Key Functions**:
|
||||
- ETL/ELT pipeline orchestration
|
||||
- Data cleaning and normalization
|
||||
- Batch and stream processing
|
||||
- Data validation and quality checks
|
||||
|
||||
### Feature Store
|
||||
- **Purpose**: ML feature management and serving
|
||||
- **Key Functions**:
|
||||
- Online and offline feature storage
|
||||
- Feature computation and serving
|
||||
- Feature statistics and monitoring
|
||||
- Feature lineage and versioning
|
||||
- Real-time feature retrieval for ML models
|
||||
|
||||
### Market Data Gateway
|
||||
- **Purpose**: Market data storage and historical access
|
||||
- **Key Functions**:
|
||||
- Historical market data storage
|
||||
- Data archival and retention policies
|
||||
- Query optimization for time-series data
|
||||
- Data backup and recovery
|
||||
|
||||
## Architecture
|
||||
|
||||
Data services create a unified data layer that enables efficient data discovery, processing, and consumption across the platform. They ensure data quality, consistency, and accessibility for both operational and analytical workloads.
|
||||
|
|
@ -1,86 +0,0 @@
|
|||
# Data Catalog
|
||||
|
||||
## Overview
|
||||
The Data Catalog service provides a centralized system for data asset discovery, management, and governance within the stock-bot platform. It serves as the single source of truth for all data assets, their metadata, and relationships, enabling efficient data discovery and utilization across the platform.
|
||||
|
||||
## Key Features
|
||||
|
||||
### Data Asset Management
|
||||
- **Asset Registration**: Automated and manual registration of data assets
|
||||
- **Metadata Management**: Comprehensive metadata for all data assets
|
||||
- **Versioning**: Tracks changes to data assets over time
|
||||
- **Schema Registry**: Central repository of data schemas and formats
|
||||
|
||||
### Data Discovery
|
||||
- **Search Capabilities**: Advanced search across all data assets
|
||||
- **Categorization**: Hierarchical categorization of data assets
|
||||
- **Tagging**: Flexible tagging system for improved findability
|
||||
- **Popularity Tracking**: Identifies most-used data assets
|
||||
|
||||
### Data Governance
|
||||
- **Access Control**: Fine-grained access control for data assets
|
||||
- **Lineage Tracking**: Visualizes data origins and transformations
|
||||
- **Quality Metrics**: Monitors and reports on data quality
|
||||
- **Compliance Tracking**: Ensures regulatory compliance for sensitive data
|
||||
|
||||
### Integration Framework
|
||||
- **API-first Design**: Comprehensive API for programmatic access
|
||||
- **Event Notifications**: Real-time notifications for data changes
|
||||
- **Bulk Operations**: Efficient handling of batch operations
|
||||
- **Extensibility**: Plugin architecture for custom extensions
|
||||
|
||||
## Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Data Processor (for processed data assets)
|
||||
- Feature Store (for feature metadata)
|
||||
- Market Data Gateway (for market data assets)
|
||||
|
||||
### Downstream Consumers
|
||||
- Strategy Development Environment
|
||||
- Data Analysis Tools
|
||||
- Machine Learning Pipeline
|
||||
- Reporting Systems
|
||||
|
||||
## Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Database**: Document database for flexible metadata storage
|
||||
- **Search**: Elasticsearch for advanced search capabilities
|
||||
- **API**: GraphQL for flexible querying
|
||||
- **UI**: React-based web interface
|
||||
|
||||
### Architecture Pattern
|
||||
- Domain-driven design for complex metadata management
|
||||
- Microservice architecture for scalability
|
||||
- Event sourcing for change tracking
|
||||
- CQRS for optimized read/write operations
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Metadata Standards
|
||||
- Adherence to common metadata standards
|
||||
- Required vs. optional metadata fields
|
||||
- Validation rules for metadata quality
|
||||
- Consistent naming conventions
|
||||
|
||||
### Extension Development
|
||||
- Plugin architecture documentation
|
||||
- Custom metadata field guidelines
|
||||
- Integration hook documentation
|
||||
- Testing requirements for extensions
|
||||
|
||||
### Performance Considerations
|
||||
- Indexing strategies for efficient search
|
||||
- Caching recommendations
|
||||
- Bulk operation best practices
|
||||
- Query optimization techniques
|
||||
|
||||
## Future Enhancements
|
||||
- Automated metadata extraction
|
||||
- Machine learning for data classification
|
||||
- Advanced lineage visualization
|
||||
- Enhanced data quality scoring
|
||||
- Collaborative annotations and discussions
|
||||
- Integration with external data marketplaces
|
||||
|
|
@ -1,86 +0,0 @@
|
|||
# Data Processor
|
||||
|
||||
## Overview
|
||||
The Data Processor service provides robust data transformation, cleaning, and enrichment capabilities for the stock-bot platform. It serves as the ETL (Extract, Transform, Load) backbone, handling both batch and streaming data processing needs to prepare raw data for consumption by downstream services.
|
||||
|
||||
## Key Features
|
||||
|
||||
### Data Transformation
|
||||
- **Format Conversion**: Transforms data between different formats (JSON, CSV, Parquet, etc.)
|
||||
- **Schema Mapping**: Maps between different data schemas
|
||||
- **Normalization**: Standardizes data values and formats
|
||||
- **Aggregation**: Creates summary data at different time intervals
|
||||
|
||||
### Data Quality Management
|
||||
- **Validation Rules**: Enforces data quality rules and constraints
|
||||
- **Cleansing**: Removes or corrects invalid data
|
||||
- **Missing Data Handling**: Strategies for handling incomplete data
|
||||
- **Anomaly Detection**: Identifies and flags unusual data patterns
|
||||
|
||||
### Pipeline Orchestration
|
||||
- **Workflow Definition**: Configurable data processing workflows
|
||||
- **Scheduling**: Time-based and event-based pipeline execution
|
||||
- **Dependency Management**: Handles dependencies between processing steps
|
||||
- **Error Handling**: Graceful error recovery and retry mechanisms
|
||||
|
||||
### Data Enrichment
|
||||
- **Reference Data Integration**: Enhances data with reference sources
|
||||
- **Feature Engineering**: Creates derived features for analysis
|
||||
- **Cross-source Joins**: Combines data from multiple sources
|
||||
- **Temporal Enrichment**: Adds time-based context and features
|
||||
|
||||
## Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Market Data Gateway (for raw market data)
|
||||
- External Data Connectors (for alternative data)
|
||||
- Data Lake/Storage (for historical data)
|
||||
|
||||
### Downstream Consumers
|
||||
- Feature Store (for processed features)
|
||||
- Data Catalog (for processed datasets)
|
||||
- Intelligence Services (for analysis input)
|
||||
- Data Warehouse (for reporting data)
|
||||
|
||||
## Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Processing Frameworks**: Apache Spark for batch, Kafka Streams for streaming
|
||||
- **Storage**: Object storage for intermediate data
|
||||
- **Orchestration**: Airflow for pipeline management
|
||||
- **Configuration**: YAML-based pipeline definitions
|
||||
|
||||
### Architecture Pattern
|
||||
- Data pipeline architecture
|
||||
- Pluggable transformation components
|
||||
- Separation of pipeline definition from execution
|
||||
- Idempotent processing for reliability
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Pipeline Development
|
||||
- Modular transformation development
|
||||
- Testing requirements for transformations
|
||||
- Performance optimization techniques
|
||||
- Documentation requirements
|
||||
|
||||
### Data Quality Controls
|
||||
- Quality rule definition standards
|
||||
- Error handling and reporting
|
||||
- Data quality metric collection
|
||||
- Threshold-based alerting
|
||||
|
||||
### Operational Considerations
|
||||
- Monitoring requirements
|
||||
- Resource utilization guidelines
|
||||
- Scaling recommendations
|
||||
- Failure recovery procedures
|
||||
|
||||
## Future Enhancements
|
||||
- Machine learning-based data cleaning
|
||||
- Advanced schema evolution handling
|
||||
- Visual pipeline builder
|
||||
- Enhanced pipeline monitoring dashboard
|
||||
- Automated data quality remediation
|
||||
- Real-time processing optimizations
|
||||
|
|
@ -1,86 +0,0 @@
|
|||
# Feature Store
|
||||
|
||||
## Overview
|
||||
The Feature Store service provides a centralized repository for managing, serving, and monitoring machine learning features within the stock-bot platform. It bridges the gap between data engineering and machine learning, ensuring consistent feature computation and reliable feature access for both training and inference.
|
||||
|
||||
## Key Features
|
||||
|
||||
### Feature Management
|
||||
- **Feature Registry**: Central catalog of all ML features
|
||||
- **Feature Definitions**: Standardized declarations of feature computation logic
|
||||
- **Feature Versioning**: Tracks changes to feature definitions over time
|
||||
- **Feature Groups**: Logical grouping of related features
|
||||
|
||||
### Serving Capabilities
|
||||
- **Online Serving**: Low-latency access for real-time predictions
|
||||
- **Offline Serving**: Batch access for model training
|
||||
- **Point-in-time Correctness**: Historical feature values for specific timestamps
|
||||
- **Feature Vectors**: Grouped feature retrieval for models
|
||||
|
||||
### Data Quality & Monitoring
|
||||
- **Statistics Tracking**: Monitors feature distributions and statistics
|
||||
- **Drift Detection**: Identifies shifts in feature patterns
|
||||
- **Validation Rules**: Enforces constraints on feature values
|
||||
- **Alerting**: Notifies of anomalies or quality issues
|
||||
|
||||
### Operational Features
|
||||
- **Caching**: Performance optimization for frequently-used features
|
||||
- **Backfilling**: Recomputation of historical feature values
|
||||
- **Feature Lineage**: Tracks data sources and transformations
|
||||
- **Access Controls**: Security controls for feature access
|
||||
|
||||
## Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Data Processor (for feature computation)
|
||||
- Market Data Gateway (for real-time input data)
|
||||
- Data Catalog (for feature metadata)
|
||||
|
||||
### Downstream Consumers
|
||||
- Signal Engine (for feature consumption)
|
||||
- Strategy Orchestrator (for real-time feature access)
|
||||
- Backtest Engine (for historical feature access)
|
||||
- Model Training Pipeline
|
||||
|
||||
## Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Online Storage**: Redis for low-latency access
|
||||
- **Offline Storage**: Parquet files in object storage
|
||||
- **Metadata Store**: Document database for feature registry
|
||||
- **API**: RESTful and gRPC interfaces
|
||||
|
||||
### Architecture Pattern
|
||||
- Dual-storage architecture (online/offline)
|
||||
- Event-driven feature computation
|
||||
- Schema-on-read with strong validation
|
||||
- Separation of storage from compute
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Feature Definition
|
||||
- Feature specification format
|
||||
- Transformation function requirements
|
||||
- Testing requirements for features
|
||||
- Documentation standards
|
||||
|
||||
### Performance Considerations
|
||||
- Caching strategies
|
||||
- Batch vs. streaming computation
|
||||
- Storage optimization techniques
|
||||
- Query patterns and optimization
|
||||
|
||||
### Quality Controls
|
||||
- Feature validation requirements
|
||||
- Monitoring configuration
|
||||
- Alerting thresholds
|
||||
- Remediation procedures
|
||||
|
||||
## Future Enhancements
|
||||
- Feature discovery and recommendations
|
||||
- Automated feature generation
|
||||
- Enhanced visualization of feature relationships
|
||||
- Feature importance tracking
|
||||
- Integrated A/B testing for features
|
||||
- On-demand feature computation
|
||||
|
|
@ -1,37 +0,0 @@
|
|||
# Execution Services
|
||||
|
||||
Execution services handle trade execution, order management, and broker integrations for the trading platform.
|
||||
|
||||
## Services
|
||||
|
||||
*Currently in planning phase - no active services deployed*
|
||||
|
||||
## Planned Capabilities
|
||||
|
||||
### Order Management System (OMS)
|
||||
- **Purpose**: Centralized order lifecycle management
|
||||
- **Planned Functions**:
|
||||
- Order routing and execution
|
||||
- Order validation and risk checks
|
||||
- Execution quality monitoring
|
||||
- Fill reporting and trade confirmations
|
||||
|
||||
### Broker Gateway
|
||||
- **Purpose**: Multi-broker connectivity and abstraction
|
||||
- **Planned Functions**:
|
||||
- Broker API integration and management
|
||||
- Order routing optimization
|
||||
- Execution venue selection
|
||||
- Trade settlement and clearing
|
||||
|
||||
### Portfolio Manager
|
||||
- **Purpose**: Position tracking and portfolio management
|
||||
- **Planned Functions**:
|
||||
- Real-time position tracking
|
||||
- Portfolio rebalancing
|
||||
- Corporate actions processing
|
||||
- P&L calculation and reporting
|
||||
|
||||
## Architecture
|
||||
|
||||
Execution services will form the operational core of trade execution, ensuring reliable and efficient order processing while maintaining proper risk controls and compliance requirements.
|
||||
|
|
@ -1,88 +0,0 @@
|
|||
# Broker Gateway
|
||||
|
||||
## Overview
|
||||
The Broker Gateway service will provide a unified interface for connecting to multiple broker APIs and trading venues within the stock-bot platform. It will abstract the complexities of different broker systems, providing a standardized way to route orders, receive executions, and manage account information across multiple execution venues.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### Broker Integration
|
||||
- **Multi-broker Support**: Connectivity to multiple brokerage platforms
|
||||
- **Unified API**: Standardized interface across different brokers
|
||||
- **Credential Management**: Secure handling of broker authentication
|
||||
- **Connection Management**: Monitoring and maintenance of broker connections
|
||||
- **Error Handling**: Standardized error processing across providers
|
||||
|
||||
### Order Routing
|
||||
- **Smart Routing**: Intelligent selection of optimal execution venues
|
||||
- **Route Optimization**: Cost and execution quality-based routing decisions
|
||||
- **Failover Routing**: Automatic rerouting in case of broker issues
|
||||
- **Split Orders**: Distribution of large orders across multiple venues
|
||||
- **Order Translation**: Mapping platform orders to broker-specific formats
|
||||
|
||||
### Account Management
|
||||
- **Balance Tracking**: Real-time account balance monitoring
|
||||
- **Position Reconciliation**: Verification of position data with brokers
|
||||
- **Margin Calculation**: Standardized margin requirement calculation
|
||||
- **Account Limits**: Enforcement of account-level trading restrictions
|
||||
- **Multi-account Support**: Management of multiple trading accounts
|
||||
|
||||
### Market Access
|
||||
- **Market Data Proxying**: Standardized access to broker market data
|
||||
- **Instrument Coverage**: Management of tradable instrument universe
|
||||
- **Trading Hours**: Handling of exchange trading calendars
|
||||
- **Fee Structure**: Tracking of broker-specific fee models
|
||||
- **Corporate Actions**: Processing of splits, dividends, and other events
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Order Management System (for order routing)
|
||||
- Risk Guardian (for account risk monitoring)
|
||||
- Authentication Service (for user permissions)
|
||||
|
||||
### Downstream Connections
|
||||
- External Broker APIs (e.g., Alpaca, Interactive Brokers)
|
||||
- Market Data Providers
|
||||
- Clearing Systems
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Database**: Fast key-value store for state management
|
||||
- **Messaging**: Message bus for order events
|
||||
- **Authentication**: Secure credential vault
|
||||
- **Monitoring**: Real-time connection monitoring
|
||||
|
||||
### Architecture Pattern
|
||||
- Adapter pattern for broker integrations
|
||||
- Circuit breaker for fault tolerance
|
||||
- Rate limiting for API compliance
|
||||
- Idempotent operations for reliability
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Broker Integration
|
||||
- API implementation requirements
|
||||
- Authentication methods
|
||||
- Error mapping standards
|
||||
- Testing requirements
|
||||
|
||||
### Performance Considerations
|
||||
- Latency expectations
|
||||
- Throughput requirements
|
||||
- Resource utilization guidelines
|
||||
- Connection pooling recommendations
|
||||
|
||||
### Reliability Measures
|
||||
- Retry strategies
|
||||
- Circuit breaker configurations
|
||||
- Monitoring requirements
|
||||
- Failover procedures
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Core integration with primary broker (Alpaca)
|
||||
2. Order routing and execution tracking
|
||||
3. Account management and position reconciliation
|
||||
4. Additional broker integrations
|
||||
5. Smart routing and optimization features
|
||||
|
|
@ -1,88 +0,0 @@
|
|||
# Order Management System
|
||||
|
||||
## Overview
|
||||
The Order Management System (OMS) will provide centralized order lifecycle management for the stock-bot platform. It will handle the entire order process from creation through routing, execution, and settlement, ensuring reliable and efficient trade processing while maintaining proper audit trails.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### Order Lifecycle Management
|
||||
- **Order Creation**: Clean API for creating various order types
|
||||
- **Order Validation**: Pre-execution validation and risk checks
|
||||
- **Order Routing**: Intelligent routing to appropriate brokers/venues
|
||||
- **Execution Tracking**: Real-time tracking of order status
|
||||
- **Fill Management**: Processing of full and partial fills
|
||||
- **Cancellation & Modification**: Handling order changes and cancellations
|
||||
|
||||
### Order Types & Algorithms
|
||||
- **Market & Limit Orders**: Basic order type handling
|
||||
- **Stop & Stop-Limit Orders**: Risk-controlling conditional orders
|
||||
- **Time-in-Force Options**: Day, GTC, IOC, FOK implementations
|
||||
- **Algorithmic Orders**: TWAP, VWAP, Iceberg, and custom algorithms
|
||||
- **Bracket Orders**: OCO (One-Cancels-Other) and other complex orders
|
||||
|
||||
### Execution Quality
|
||||
- **Best Execution**: Strategies for achieving optimal execution prices
|
||||
- **Transaction Cost Analysis**: Measurement and optimization of execution costs
|
||||
- **Slippage Monitoring**: Tracking of execution vs. expected prices
|
||||
- **Fill Reporting**: Comprehensive reporting on execution quality
|
||||
|
||||
### Operational Features
|
||||
- **Audit Trail**: Complete history of all order events
|
||||
- **Reconciliation**: Matching of orders with executions
|
||||
- **Exception Handling**: Management of rejected or failed orders
|
||||
- **Compliance Rules**: Implementation of regulatory requirements
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Strategy Orchestrator (order requests)
|
||||
- Risk Guardian (risk validation)
|
||||
- Authentication Services (permission validation)
|
||||
|
||||
### Downstream Consumers
|
||||
- Broker Gateway (order routing)
|
||||
- Portfolio Manager (position impact)
|
||||
- Trading Dashboard (order visualization)
|
||||
- Data Warehouse (execution analytics)
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Database**: High-performance transactional database
|
||||
- **Messaging**: Low-latency message bus for order events
|
||||
- **API**: RESTful and WebSocket interfaces
|
||||
- **Persistence**: Event sourcing for order history
|
||||
|
||||
### Architecture Pattern
|
||||
- Event-driven architecture for real-time processing
|
||||
- CQRS for optimized read/write operations
|
||||
- Microservice decomposition by functionality
|
||||
- High availability and fault tolerance design
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Order Management
|
||||
- Order state machine definitions
|
||||
- Order type specifications
|
||||
- Validation rule implementation
|
||||
- Exception handling procedures
|
||||
|
||||
### Performance Requirements
|
||||
- Order throughput expectations
|
||||
- Latency budgets by component
|
||||
- Scaling approaches
|
||||
- Resource utilization guidelines
|
||||
|
||||
### Testing Strategy
|
||||
- Unit testing requirements
|
||||
- Integration testing approach
|
||||
- Performance testing methodology
|
||||
- Compliance verification procedures
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Core order types and lifecycle management
|
||||
2. Basic routing and execution tracking
|
||||
3. Advanced order types and algorithms
|
||||
4. Execution quality analytics and optimization
|
||||
5. Compliance and regulatory reporting features
|
||||
|
|
@ -1,90 +0,0 @@
|
|||
# Portfolio Manager
|
||||
|
||||
## Overview
|
||||
The Portfolio Manager service will provide comprehensive position tracking, portfolio analysis, and management capabilities for the stock-bot platform. It will maintain the current state of all trading portfolios, calculate performance metrics, and support portfolio-level decision making.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### Position Management
|
||||
- **Real-time Position Tracking**: Accurate tracking of all open positions
|
||||
- **Position Reconciliation**: Validation against broker records
|
||||
- **Average Price Calculation**: Tracking of position entry prices
|
||||
- **Lot Management**: FIFO/LIFO/average cost basis tracking
|
||||
- **Multi-currency Support**: Handling positions across different currencies
|
||||
|
||||
### Portfolio Analytics
|
||||
- **Performance Metrics**: Return calculation (absolute, relative, time-weighted)
|
||||
- **Risk Metrics**: Volatility, beta, correlation, VaR calculations
|
||||
- **Attribution Analysis**: Performance attribution by sector, strategy, asset class
|
||||
- **Scenario Analysis**: What-if analysis for portfolio changes
|
||||
- **Benchmark Comparison**: Performance vs. standard benchmarks
|
||||
|
||||
### Corporate Action Processing
|
||||
- **Dividend Processing**: Impact of cash and stock dividends
|
||||
- **Split Adjustments**: Handling of stock splits and reverse splits
|
||||
- **Merger & Acquisition Handling**: Position adjustments for M&A events
|
||||
- **Rights & Warrants**: Processing of corporate rights events
|
||||
- **Spin-offs**: Management of position changes from spin-off events
|
||||
|
||||
### Portfolio Construction
|
||||
- **Rebalancing Tools**: Portfolio rebalancing against targets
|
||||
- **Optimization**: Portfolio optimization for various objectives
|
||||
- **Constraint Management**: Enforcement of portfolio constraints
|
||||
- **Tax-aware Trading**: Consideration of tax implications
|
||||
- **Cash Management**: Handling of cash positions and forecasting
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Order Management System (for executed trades)
|
||||
- Broker Gateway (for position verification)
|
||||
- Market Data Gateway (for pricing)
|
||||
- Strategy Orchestrator (for allocation decisions)
|
||||
|
||||
### Downstream Consumers
|
||||
- Risk Guardian (for portfolio risk assessment)
|
||||
- Trading Dashboard (for portfolio visualization)
|
||||
- Reporting System (for performance reporting)
|
||||
- Tax Reporting (for tax calculations)
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Database**: Fast database with transaction support
|
||||
- **Calculation Engine**: Optimized financial calculation libraries
|
||||
- **API**: RESTful interface with WebSocket updates
|
||||
- **Caching**: In-memory position cache for performance
|
||||
|
||||
### Architecture Pattern
|
||||
- Event sourcing for position history
|
||||
- CQRS for optimized read/write operations
|
||||
- Eventual consistency for distributed state
|
||||
- Snapshotting for performance optimization
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Position Calculations
|
||||
- Cost basis methodologies
|
||||
- Corporate action handling
|
||||
- FX conversion approaches
|
||||
- Performance calculation standards
|
||||
|
||||
### Data Consistency
|
||||
- Reconciliation procedures
|
||||
- Error detection and correction
|
||||
- Data validation requirements
|
||||
- Audit trail requirements
|
||||
|
||||
### Performance Optimization
|
||||
- Caching strategies
|
||||
- Calculation optimization
|
||||
- Query patterns
|
||||
- Batch processing approaches
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Basic position tracking and P&L calculation
|
||||
2. Portfolio analytics and performance metrics
|
||||
3. Corporate action processing
|
||||
4. Advanced portfolio construction tools
|
||||
5. Tax and regulatory reporting features
|
||||
|
|
@ -1,45 +0,0 @@
|
|||
# Integration Services
|
||||
|
||||
Integration services provide connectivity, messaging, and interoperability between internal services and external systems.
|
||||
|
||||
## Services
|
||||
|
||||
*Currently in planning phase - no active services deployed*
|
||||
|
||||
## Planned Capabilities
|
||||
|
||||
### Message Bus
|
||||
- **Purpose**: Event-driven communication between services
|
||||
- **Planned Functions**:
|
||||
- Event publishing and subscription
|
||||
- Message routing and transformation
|
||||
- Dead letter queue handling
|
||||
- Event sourcing and replay capabilities
|
||||
|
||||
### API Gateway
|
||||
- **Purpose**: Unified API management and routing
|
||||
- **Planned Functions**:
|
||||
- API endpoint consolidation
|
||||
- Authentication and authorization
|
||||
- Rate limiting and throttling
|
||||
- Request/response transformation
|
||||
|
||||
### External Data Connectors
|
||||
- **Purpose**: Third-party data source integration
|
||||
- **Planned Functions**:
|
||||
- Alternative data provider connections
|
||||
- News and sentiment data feeds
|
||||
- Economic indicator integrations
|
||||
- Social media sentiment tracking
|
||||
|
||||
### Notification Service
|
||||
- **Purpose**: Multi-channel alerting and notifications
|
||||
- **Planned Functions**:
|
||||
- Email, SMS, and push notifications
|
||||
- Alert routing and escalation
|
||||
- Notification templates and personalization
|
||||
- Delivery tracking and analytics
|
||||
|
||||
## Architecture
|
||||
|
||||
Integration services will provide the connectivity fabric that enables seamless communication between all platform components and external systems, ensuring loose coupling and high scalability.
|
||||
|
|
@ -1,89 +0,0 @@
|
|||
# API Gateway
|
||||
|
||||
## Overview
|
||||
The API Gateway service will provide a unified entry point for all external API requests to the stock-bot platform. It will handle request routing, composition, protocol translation, authentication, and other cross-cutting concerns, providing a simplified interface for clients while abstracting the internal microservice architecture.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### Request Management
|
||||
- **Routing**: Direct requests to appropriate backend services
|
||||
- **Aggregation**: Combine results from multiple microservices
|
||||
- **Transformation**: Convert between different data formats and protocols
|
||||
- **Parameter Validation**: Validate request parameters before forwarding
|
||||
- **Service Discovery**: Dynamically locate service instances
|
||||
|
||||
### Security Features
|
||||
- **Authentication**: Centralized authentication for all API requests
|
||||
- **Authorization**: Role-based access control for API endpoints
|
||||
- **API Keys**: Management of client API keys and quotas
|
||||
- **JWT Validation**: Token-based authentication handling
|
||||
- **OAuth Integration**: Support for OAuth 2.0 flows
|
||||
|
||||
### Traffic Management
|
||||
- **Rate Limiting**: Protect services from excessive requests
|
||||
- **Throttling**: Client-specific request throttling
|
||||
- **Circuit Breaking**: Prevent cascading failures
|
||||
- **Load Balancing**: Distribute requests among service instances
|
||||
- **Retries**: Automatic retry of failed requests
|
||||
|
||||
### Operational Features
|
||||
- **Request Logging**: Comprehensive logging of API activity
|
||||
- **Metrics Collection**: Performance and usage metrics
|
||||
- **Caching**: Response caching for improved performance
|
||||
- **Documentation**: Auto-generated API documentation
|
||||
- **Versioning**: Support for multiple API versions
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Frontend Connections
|
||||
- Trading Dashboard (web client)
|
||||
- Mobile applications
|
||||
- Third-party integrations
|
||||
- Partner systems
|
||||
|
||||
### Backend Services
|
||||
- All platform microservices
|
||||
- Authentication services
|
||||
- Monitoring and logging systems
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **API Gateway**: Kong, AWS API Gateway, or custom solution
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Documentation**: OpenAPI/Swagger
|
||||
- **Cache**: Redis for response caching
|
||||
- **Storage**: Database for API configurations
|
||||
|
||||
### Architecture Pattern
|
||||
- Backend for Frontend (BFF) pattern
|
||||
- API Gateway pattern
|
||||
- Circuit breaker pattern
|
||||
- Bulkhead pattern for isolation
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### API Design
|
||||
- RESTful API design standards
|
||||
- Error response format
|
||||
- Versioning strategy
|
||||
- Resource naming conventions
|
||||
|
||||
### Security Implementation
|
||||
- Authentication requirements
|
||||
- Authorization approach
|
||||
- API key management
|
||||
- Rate limit configuration
|
||||
|
||||
### Performance Optimization
|
||||
- Caching strategies
|
||||
- Request batching techniques
|
||||
- Response compression
|
||||
- Timeout configurations
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Core routing and basic security features
|
||||
2. Traffic management and monitoring
|
||||
3. Request aggregation and transformation
|
||||
4. Advanced security features
|
||||
5. Developer portal and documentation
|
||||
|
|
@ -1,84 +0,0 @@
|
|||
# Message Bus
|
||||
|
||||
## Overview
|
||||
The Message Bus service will provide the central event-driven communication infrastructure for the stock-bot platform. It will enable reliable, scalable, and decoupled interaction between services through asynchronous messaging, event streaming, and publish-subscribe patterns.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### Messaging Infrastructure
|
||||
- **Topic-based Messaging**: Publish-subscribe communication model
|
||||
- **Message Queuing**: Reliable message delivery with persistence
|
||||
- **Event Streaming**: Real-time event processing with replay capabilities
|
||||
- **Message Routing**: Dynamic routing based on content and metadata
|
||||
- **Quality of Service**: Various delivery guarantee levels (at-least-once, exactly-once)
|
||||
|
||||
### Message Processing
|
||||
- **Message Transformation**: Content transformation and enrichment
|
||||
- **Message Filtering**: Rules-based filtering of messages
|
||||
- **Schema Validation**: Enforcement of message format standards
|
||||
- **Serialization Formats**: Support for JSON, Protocol Buffers, Avro
|
||||
- **Compression**: Message compression for efficiency
|
||||
|
||||
### Operational Features
|
||||
- **Dead Letter Handling**: Management of unprocessable messages
|
||||
- **Message Tracing**: End-to-end tracing of message flow
|
||||
- **Event Sourcing**: Event storage and replay capability
|
||||
- **Rate Limiting**: Protection against message floods
|
||||
- **Back-pressure Handling**: Flow control mechanisms
|
||||
|
||||
### Integration Capabilities
|
||||
- **Service Discovery**: Dynamic discovery of publishers/subscribers
|
||||
- **Protocol Bridging**: Support for multiple messaging protocols
|
||||
- **External System Integration**: Connectors for external message systems
|
||||
- **Legacy System Adapters**: Integration with non-event-driven systems
|
||||
- **Web Integration**: WebSocket and SSE support for web clients
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Service Connections
|
||||
- All platform microservices as publishers and subscribers
|
||||
- Trading Dashboard (for real-time updates)
|
||||
- External Data Sources (for ingestion)
|
||||
- Monitoring Systems (for operational events)
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Messaging Platform**: Kafka or RabbitMQ
|
||||
- **Client Libraries**: Native TypeScript SDK
|
||||
- **Monitoring**: Prometheus integration for metrics
|
||||
- **Management**: Admin interface for topic/queue management
|
||||
- **Storage**: Optimized storage for event persistence
|
||||
|
||||
### Architecture Pattern
|
||||
- Event-driven architecture
|
||||
- Publish-subscribe pattern
|
||||
- Command pattern for request-response
|
||||
- Circuit breaker for resilience
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Message Design
|
||||
- Event schema standards
|
||||
- Versioning approach
|
||||
- Backward compatibility requirements
|
||||
- Message size considerations
|
||||
|
||||
### Integration Patterns
|
||||
- Event notification pattern
|
||||
- Event-carried state transfer
|
||||
- Command messaging pattern
|
||||
- Request-reply pattern implementations
|
||||
|
||||
### Operational Considerations
|
||||
- Monitoring requirements
|
||||
- Scaling guidelines
|
||||
- Disaster recovery approach
|
||||
- Message retention policies
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Core messaging infrastructure
|
||||
2. Service integration patterns
|
||||
3. Operational tooling and monitoring
|
||||
4. Advanced features (replay, transformation)
|
||||
5. External system connectors and adapters
|
||||
|
|
@ -1,36 +0,0 @@
|
|||
# Intelligence Services
|
||||
|
||||
Intelligence services provide AI/ML capabilities, strategy execution, and algorithmic trading intelligence for the platform.
|
||||
|
||||
## Services
|
||||
|
||||
### Backtest Engine
|
||||
- **Purpose**: Historical strategy testing and performance analysis
|
||||
- **Key Functions**:
|
||||
- Strategy backtesting with historical data
|
||||
- Performance analytics and metrics calculation
|
||||
- Vectorized and event-based processing modes
|
||||
- Risk-adjusted return analysis
|
||||
- Strategy comparison and optimization
|
||||
|
||||
### Signal Engine
|
||||
- **Purpose**: Trading signal generation and processing
|
||||
- **Key Functions**:
|
||||
- Technical indicator calculations
|
||||
- Signal generation from multiple sources
|
||||
- Signal aggregation and filtering
|
||||
- Real-time signal processing
|
||||
- Signal quality assessment
|
||||
|
||||
### Strategy Orchestrator
|
||||
- **Purpose**: Trading strategy execution and management
|
||||
- **Key Functions**:
|
||||
- Strategy lifecycle management
|
||||
- Event-driven strategy execution
|
||||
- Multi-strategy coordination
|
||||
- Strategy performance monitoring
|
||||
- Risk integration and position management
|
||||
|
||||
## Architecture
|
||||
|
||||
Intelligence services form the "brain" of the trading platform, combining market analysis, machine learning, and algorithmic decision-making to generate actionable trading insights. They work together to create a comprehensive trading intelligence pipeline from signal generation to strategy execution.
|
||||
|
|
@ -1,86 +0,0 @@
|
|||
# Backtest Engine
|
||||
|
||||
## Overview
|
||||
The Backtest Engine service provides comprehensive historical simulation capabilities for trading strategies within the stock-bot platform. It enables strategy developers to evaluate performance, risk, and robustness of trading algorithms using historical market data before deploying them to production.
|
||||
|
||||
## Key Features
|
||||
|
||||
### Simulation Framework
|
||||
- **Event-based Processing**: True event-driven simulation of market activities
|
||||
- **Vectorized Processing**: High-performance batch processing for speed
|
||||
- **Multi-asset Support**: Simultaneous testing across multiple instruments
|
||||
- **Historical Market Data**: Access to comprehensive price and volume history
|
||||
|
||||
### Performance Analytics
|
||||
- **Return Metrics**: CAGR, absolute return, risk-adjusted metrics
|
||||
- **Risk Metrics**: Drawdown, volatility, VaR, expected shortfall
|
||||
- **Transaction Analysis**: Slippage modeling, fee impact, market impact
|
||||
- **Statistical Analysis**: Win rate, profit factor, Sharpe/Sortino ratios
|
||||
|
||||
### Realistic Simulation
|
||||
- **Order Book Simulation**: Realistic market depth modeling
|
||||
- **Latency Modeling**: Simulates execution and market data delays
|
||||
- **Fill Probability Models**: Realistic order execution simulation
|
||||
- **Market Impact Models**: Adjusts prices based on order sizes
|
||||
|
||||
### Development Tools
|
||||
- **Parameter Optimization**: Grid search and genetic algorithm optimization
|
||||
- **Walk-forward Testing**: Time-based validation with parameter stability
|
||||
- **Monte Carlo Analysis**: Probability distribution of outcomes
|
||||
- **Sensitivity Analysis**: Impact of parameter changes on performance
|
||||
|
||||
## Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Market Data Gateway (for historical data)
|
||||
- Feature Store (for historical feature values)
|
||||
- Strategy Repository (for strategy definitions)
|
||||
|
||||
### Downstream Consumers
|
||||
- Strategy Orchestrator (for optimized parameters)
|
||||
- Risk Guardian (for risk model validation)
|
||||
- Trading Dashboard (for backtest visualization)
|
||||
- Strategy Development Environment
|
||||
|
||||
## Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Computation Engine**: Optimized numerical libraries
|
||||
- **Storage**: Time-series database for results
|
||||
- **Visualization**: Interactive performance charts
|
||||
- **Distribution**: Parallel processing for large backtests
|
||||
|
||||
### Architecture Pattern
|
||||
- Pipeline architecture for data flow
|
||||
- Plugin system for custom components
|
||||
- Separation of strategy logic from simulation engine
|
||||
- Reproducible random state management
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Strategy Development
|
||||
- Strategy interface definition
|
||||
- Testing harness documentation
|
||||
- Performance optimization guidelines
|
||||
- Validation requirements
|
||||
|
||||
### Simulation Configuration
|
||||
- Parameter specification format
|
||||
- Simulation control options
|
||||
- Market assumption configuration
|
||||
- Execution model settings
|
||||
|
||||
### Results Analysis
|
||||
- Standard metrics calculation
|
||||
- Custom metric development
|
||||
- Visualization best practices
|
||||
- Comparative analysis techniques
|
||||
|
||||
## Future Enhancements
|
||||
- Agent-based simulation for market microstructure
|
||||
- Cloud-based distributed backtesting
|
||||
- Real market data replay with tick data
|
||||
- Machine learning for parameter optimization
|
||||
- Strategy combination and portfolio optimization
|
||||
- Enhanced visualization and reporting capabilities
|
||||
|
|
@ -1,87 +0,0 @@
|
|||
# Signal Engine
|
||||
|
||||
## Overview
|
||||
The Signal Engine service generates, processes, and manages trading signals within the stock-bot platform. It transforms raw market data and feature inputs into actionable trading signals that inform strategy execution decisions, serving as the analytical brain of the trading system.
|
||||
|
||||
## Key Features
|
||||
|
||||
### Signal Generation
|
||||
- **Technical Indicators**: Comprehensive library of technical analysis indicators
|
||||
- **Statistical Models**: Mean-reversion, momentum, and other statistical signals
|
||||
- **Pattern Recognition**: Identification of chart patterns and formations
|
||||
- **Custom Signal Definition**: Framework for creating proprietary signals
|
||||
|
||||
### Signal Processing
|
||||
- **Filtering**: Noise reduction and signal cleaning
|
||||
- **Aggregation**: Combining multiple signals into composite indicators
|
||||
- **Normalization**: Standardizing signals across different instruments
|
||||
- **Ranking**: Relative strength measurement across instruments
|
||||
|
||||
### Quality Management
|
||||
- **Signal Strength Metrics**: Quantitative assessment of signal reliability
|
||||
- **Historical Performance**: Tracking of signal predictive power
|
||||
- **Decay Modeling**: Time-based degradation of signal relevance
|
||||
- **Correlation Analysis**: Identifying redundant or correlated signals
|
||||
|
||||
### Operational Features
|
||||
- **Real-time Processing**: Low-latency signal generation
|
||||
- **Batch Processing**: Overnight/weekend comprehensive signal computation
|
||||
- **Signal Repository**: Historical storage of generated signals
|
||||
- **Signal Subscription**: Event-based notification of new signals
|
||||
|
||||
## Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Market Data Gateway (for price and volume data)
|
||||
- Feature Store (for derived trading features)
|
||||
- Alternative Data Services (for sentiment, news factors)
|
||||
- Data Processor (for preprocessed data)
|
||||
|
||||
### Downstream Consumers
|
||||
- Strategy Orchestrator (for signal consumption)
|
||||
- Backtest Engine (for signal effectiveness analysis)
|
||||
- Trading Dashboard (for signal visualization)
|
||||
- Risk Guardian (for risk factor identification)
|
||||
|
||||
## Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **Calculation Engine**: Optimized numerical libraries
|
||||
- **Storage**: Time-series database for signal storage
|
||||
- **Messaging**: Event-driven notification system
|
||||
- **Parallel Processing**: Multi-threaded computation for intensive signals
|
||||
|
||||
### Architecture Pattern
|
||||
- Pipeline architecture for signal flow
|
||||
- Pluggable signal component design
|
||||
- Separation of data preparation from signal generation
|
||||
- Event sourcing for signal versioning
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Signal Development
|
||||
- Signal specification format
|
||||
- Performance optimization techniques
|
||||
- Testing requirements and methodology
|
||||
- Documentation standards
|
||||
|
||||
### Quality Controls
|
||||
- Validation methodology
|
||||
- Backtesting requirements
|
||||
- Correlation thresholds
|
||||
- Signal deprecation process
|
||||
|
||||
### Operational Considerations
|
||||
- Computation scheduling
|
||||
- Resource utilization guidelines
|
||||
- Monitoring requirements
|
||||
- Failover procedures
|
||||
|
||||
## Future Enhancements
|
||||
- Machine learning-based signal generation
|
||||
- Adaptive signal weighting
|
||||
- Real-time signal quality feedback
|
||||
- Advanced signal visualization
|
||||
- Cross-asset class signals
|
||||
- Alternative data integration
|
||||
|
|
@ -1,87 +0,0 @@
|
|||
# Strategy Orchestrator
|
||||
|
||||
## Overview
|
||||
The Strategy Orchestrator service coordinates the execution and lifecycle management of trading strategies within the stock-bot platform. It serves as the central orchestration engine that translates trading signals into executable orders while managing strategy state, performance monitoring, and risk integration.
|
||||
|
||||
## Key Features
|
||||
|
||||
### Strategy Lifecycle Management
|
||||
- **Strategy Registration**: Onboarding and configuration of trading strategies
|
||||
- **Version Control**: Management of strategy versions and deployments
|
||||
- **State Management**: Tracking of strategy execution state
|
||||
- **Activation/Deactivation**: Controlled enabling and disabling of strategies
|
||||
|
||||
### Execution Coordination
|
||||
- **Signal Processing**: Consumes and processes signals from Signal Engine
|
||||
- **Order Generation**: Translates signals into executable trading orders
|
||||
- **Execution Timing**: Optimizes order timing based on market conditions
|
||||
- **Multi-strategy Coordination**: Manages interactions between strategies
|
||||
|
||||
### Performance Monitoring
|
||||
- **Real-time Metrics**: Tracks strategy performance metrics in real-time
|
||||
- **Alerting**: Notifies on strategy performance anomalies
|
||||
- **Execution Quality**: Measures and reports on execution quality
|
||||
- **Strategy Attribution**: Attributes P&L to specific strategies
|
||||
|
||||
### Risk Integration
|
||||
- **Pre-trade Risk Checks**: Validates orders against risk parameters
|
||||
- **Position Tracking**: Monitors strategy position and exposure
|
||||
- **Risk Limit Enforcement**: Ensures compliance with risk thresholds
|
||||
- **Circuit Breakers**: Implements strategy-specific circuit breakers
|
||||
|
||||
## Integration Points
|
||||
|
||||
### Upstream Connections
|
||||
- Signal Engine (for trading signals)
|
||||
- Feature Store (for real-time feature access)
|
||||
- Market Data Gateway (for market data)
|
||||
- Backtest Engine (for optimized parameters)
|
||||
|
||||
### Downstream Consumers
|
||||
- Order Management System (for order execution)
|
||||
- Risk Guardian (for risk monitoring)
|
||||
- Trading Dashboard (for strategy visualization)
|
||||
- Data Catalog (for strategy performance data)
|
||||
|
||||
## Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Runtime**: Node.js with TypeScript
|
||||
- **State Management**: Redis for distributed state
|
||||
- **Messaging**: Event-driven architecture with message bus
|
||||
- **Database**: Time-series database for performance metrics
|
||||
- **API**: RESTful API for management functions
|
||||
|
||||
### Architecture Pattern
|
||||
- Event-driven architecture for reactive processing
|
||||
- Command pattern for strategy operations
|
||||
- State machine for strategy lifecycle
|
||||
- Circuit breaker pattern for fault tolerance
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Strategy Integration
|
||||
- Strategy interface specification
|
||||
- Required callback implementations
|
||||
- Configuration schema definition
|
||||
- Testing and validation requirements
|
||||
|
||||
### Performance Optimization
|
||||
- Event processing efficiency
|
||||
- State management best practices
|
||||
- Resource utilization guidelines
|
||||
- Latency minimization techniques
|
||||
|
||||
### Operational Procedures
|
||||
- Strategy deployment process
|
||||
- Monitoring requirements
|
||||
- Troubleshooting guidelines
|
||||
- Failover procedures
|
||||
|
||||
## Future Enhancements
|
||||
- Advanced multi-strategy optimization
|
||||
- Machine learning for execution optimization
|
||||
- Enhanced strategy analytics dashboard
|
||||
- Dynamic parameter adjustment
|
||||
- Auto-scaling based on market conditions
|
||||
- Strategy recommendation engine
|
||||
|
|
@ -1,98 +0,0 @@
|
|||
# Migration Guide: From packages to libs
|
||||
|
||||
This guide will help you migrate your service to use the new library structure for better separation of concerns.
|
||||
|
||||
## Steps for each service
|
||||
|
||||
1. Update your `package.json` dependencies to use the new libraries:
|
||||
|
||||
```diff
|
||||
"dependencies": {
|
||||
- "@stock-bot/types": "workspace:*",
|
||||
+ "@stock-bot/types": "workspace:*",
|
||||
+ "@stock-bot/utils": "workspace:*",
|
||||
+ "@stock-bot/event-bus": "workspace:*",
|
||||
+ "@stock-bot/api-client": "workspace:*",
|
||||
...
|
||||
}
|
||||
```
|
||||
|
||||
2. Update your imports to use the domain-specific modules:
|
||||
|
||||
```diff
|
||||
- import { OHLCV, Strategy, Order } from '@stock-bot/types';
|
||||
+ import { OHLCV } from '@stock-bot/types';
|
||||
+ import { Strategy } from '@stock-bot/types';
|
||||
+ import { Order } from '@stock-bot/types';
|
||||
```
|
||||
|
||||
For logging:
|
||||
```diff
|
||||
- // Custom logging or console.log usage
|
||||
+ import { createLogger, LogLevel } from '@stock-bot/utils';
|
||||
+
|
||||
+ const logger = createLogger('your-service-name');
|
||||
+ logger.info('Message');
|
||||
```
|
||||
|
||||
For API client usage:
|
||||
```diff
|
||||
- // Manual axios calls
|
||||
+ import { createBacktestClient, createStrategyClient } from '@stock-bot/api-client';
|
||||
+
|
||||
+ const backtestClient = createBacktestClient();
|
||||
+ const result = await backtestClient.runBacktest(config);
|
||||
```
|
||||
|
||||
For event-based communication:
|
||||
```diff
|
||||
- // Manual Redis/Dragonfly usage
|
||||
+ import { createEventBus } from '@stock-bot/event-bus';
|
||||
+ import { MarketDataEvent } from '@stock-bot/types';
|
||||
+
|
||||
+ const eventBus = createEventBus({
|
||||
+ redisHost: process.env.REDIS_HOST || 'localhost',
|
||||
+ redisPort: parseInt(process.env.REDIS_PORT || '6379')
|
||||
+ });
|
||||
+
|
||||
+ eventBus.subscribe('market.data', async (event) => {
|
||||
+ // Handle event
|
||||
+ });
|
||||
```
|
||||
|
||||
## Example: Updating BacktestEngine
|
||||
|
||||
```typescript
|
||||
// Before
|
||||
import { Strategy, BacktestConfig } from '@stock-bot/types';
|
||||
import Redis from 'ioredis';
|
||||
|
||||
// After
|
||||
import { Strategy } from '@stock-bot/types';
|
||||
import { BacktestConfig } from '@stock-bot/types';
|
||||
import { createLogger } from '@stock-bot/utils';
|
||||
import { createEventBus } from '@stock-bot/event-bus';
|
||||
|
||||
const logger = createLogger('backtest-engine');
|
||||
const eventBus = createEventBus({
|
||||
redisHost: process.env.REDIS_HOST || 'localhost',
|
||||
redisPort: parseInt(process.env.REDIS_PORT || '6379')
|
||||
});
|
||||
```
|
||||
|
||||
## Updating build scripts
|
||||
|
||||
If your turbo.json configuration references specific packages, update the dependencies:
|
||||
|
||||
```diff
|
||||
"backtest": {
|
||||
"dependsOn": [
|
||||
"^build",
|
||||
- "packages/types#build"
|
||||
+ "libs/types#build",
|
||||
+ "libs/utils#build",
|
||||
+ "libs/event-bus#build",
|
||||
+ "libs/api-client#build"
|
||||
],
|
||||
}
|
||||
```
|
||||
|
|
@ -1,53 +0,0 @@
|
|||
# Platform Services
|
||||
|
||||
Platform services provide foundational infrastructure, monitoring, and operational capabilities that support all other services.
|
||||
|
||||
## Services
|
||||
|
||||
*Currently in planning phase - no active services deployed*
|
||||
|
||||
## Planned Capabilities
|
||||
|
||||
### Service Discovery
|
||||
- **Purpose**: Dynamic service registration and discovery
|
||||
- **Planned Functions**:
|
||||
- Service health monitoring
|
||||
- Load balancing and routing
|
||||
- Service mesh coordination
|
||||
- Configuration management
|
||||
|
||||
### Logging & Monitoring
|
||||
- **Purpose**: Observability and operational insights
|
||||
- **Planned Functions**:
|
||||
- Centralized logging aggregation
|
||||
- Metrics collection and analysis
|
||||
- Distributed tracing
|
||||
- Performance monitoring and alerting
|
||||
|
||||
### Configuration Management
|
||||
- **Purpose**: Centralized configuration and secrets management
|
||||
- **Planned Functions**:
|
||||
- Environment-specific configurations
|
||||
- Secrets encryption and rotation
|
||||
- Dynamic configuration updates
|
||||
- Configuration versioning and rollback
|
||||
|
||||
### Authentication & Authorization
|
||||
- **Purpose**: Security and access control
|
||||
- **Planned Functions**:
|
||||
- User authentication and session management
|
||||
- Role-based access control (RBAC)
|
||||
- API security and token management
|
||||
- Audit logging and compliance
|
||||
|
||||
### Backup & Recovery
|
||||
- **Purpose**: Data protection and disaster recovery
|
||||
- **Planned Functions**:
|
||||
- Automated backup scheduling
|
||||
- Point-in-time recovery
|
||||
- Cross-region replication
|
||||
- Disaster recovery orchestration
|
||||
|
||||
## Architecture
|
||||
|
||||
Platform services provide the operational foundation that enables reliable, secure, and observable operation of the entire trading platform. They implement cross-cutting concerns and best practices for production deployments.
|
||||
|
|
@ -1,90 +0,0 @@
|
|||
# Authentication & Authorization
|
||||
|
||||
## Overview
|
||||
The Authentication & Authorization service will provide comprehensive security controls for the stock-bot platform. It will manage user identity, authentication, access control, and security policy enforcement across all platform components, ensuring proper security governance and compliance with regulatory requirements.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### User Management
|
||||
- **User Provisioning**: Account creation and management
|
||||
- **Identity Sources**: Local and external identity providers
|
||||
- **User Profiles**: Customizable user attributes
|
||||
- **Group Management**: User grouping and organization
|
||||
- **Account Lifecycle**: Comprehensive user lifecycle management
|
||||
|
||||
### Authentication
|
||||
- **Multiple Factors**: Support for MFA/2FA
|
||||
- **Single Sign-On**: Integration with enterprise SSO solutions
|
||||
- **Social Login**: Support for third-party identity providers
|
||||
- **Session Management**: Secure session handling and expiration
|
||||
- **Password Policies**: Configurable password requirements
|
||||
|
||||
### Authorization
|
||||
- **Role-Based Access Control**: Fine-grained permission management
|
||||
- **Attribute-Based Access**: Context-aware access decisions
|
||||
- **Permission Management**: Centralized permission administration
|
||||
- **Dynamic Policies**: Rule-based access policies
|
||||
- **Delegated Administration**: Hierarchical permission management
|
||||
|
||||
### Security Features
|
||||
- **Token Management**: JWT and OAuth token handling
|
||||
- **API Security**: Protection of API endpoints
|
||||
- **Rate Limiting**: Prevention of brute force attacks
|
||||
- **Audit Logging**: Comprehensive security event logging
|
||||
- **Compliance Reporting**: Reports for regulatory requirements
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Service Integration
|
||||
- All platform microservices
|
||||
- API Gateway
|
||||
- Frontend applications
|
||||
- External systems and partners
|
||||
|
||||
### Identity Providers
|
||||
- Internal identity store
|
||||
- Enterprise directory services
|
||||
- Social identity providers
|
||||
- OAuth/OIDC providers
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Identity Server**: Keycloak or Auth0
|
||||
- **API Protection**: OAuth 2.0 and OpenID Connect
|
||||
- **Token Format**: JWT with appropriate claims
|
||||
- **Storage**: Secure credential and policy storage
|
||||
- **Encryption**: Industry-standard encryption for sensitive data
|
||||
|
||||
### Architecture Pattern
|
||||
- Identity as a service
|
||||
- Policy-based access control
|
||||
- Token-based authentication
|
||||
- Layered security model
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Authentication Integration
|
||||
- Authentication flow implementation
|
||||
- Token handling best practices
|
||||
- Session management requirements
|
||||
- Credential security standards
|
||||
|
||||
### Authorization Implementation
|
||||
- Permission modeling approach
|
||||
- Policy definition format
|
||||
- Access decision points
|
||||
- Contextual authorization techniques
|
||||
|
||||
### Security Considerations
|
||||
- Token security requirements
|
||||
- Key rotation procedures
|
||||
- Security event monitoring
|
||||
- Penetration testing requirements
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Core user management and authentication
|
||||
2. Basic role-based authorization
|
||||
3. API security and token management
|
||||
4. Advanced access control policies
|
||||
5. Compliance reporting and auditing
|
||||
|
|
@ -1,91 +0,0 @@
|
|||
# Backup & Recovery
|
||||
|
||||
## Overview
|
||||
The Backup & Recovery service will provide comprehensive data protection, disaster recovery, and business continuity capabilities for the stock-bot platform. It will ensure that critical data and system configurations are preserved, with reliable recovery options in case of system failures, data corruption, or catastrophic events.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### Backup Management
|
||||
- **Automated Backups**: Scheduled backup of all critical data
|
||||
- **Incremental Backups**: Efficient storage of incremental changes
|
||||
- **Multi-tier Backup**: Different retention policies by data importance
|
||||
- **Backup Verification**: Automated testing of backup integrity
|
||||
- **Backup Catalog**: Searchable index of available backups
|
||||
|
||||
### Recovery Capabilities
|
||||
- **Point-in-time Recovery**: Restore to specific moments in time
|
||||
- **Granular Recovery**: Restore specific objects or datasets
|
||||
- **Self-service Recovery**: User portal for simple recovery operations
|
||||
- **Recovery Testing**: Regular validation of recovery procedures
|
||||
- **Recovery Performance**: Optimized for minimal downtime
|
||||
|
||||
### Disaster Recovery
|
||||
- **Cross-region Replication**: Geographic data redundancy
|
||||
- **Recovery Site**: Standby environment for critical services
|
||||
- **Failover Automation**: Scripted failover procedures
|
||||
- **Recovery Orchestration**: Coordinated multi-system recovery
|
||||
- **DR Testing**: Regular disaster scenario testing
|
||||
|
||||
### Data Protection
|
||||
- **Encryption**: At-rest and in-transit data encryption
|
||||
- **Access Controls**: Restricted access to backup data
|
||||
- **Retention Policies**: Compliance with data retention requirements
|
||||
- **Immutable Backups**: Protection against ransomware
|
||||
- **Air-gapped Storage**: Ultimate protection for critical backups
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Data Sources
|
||||
- Platform databases (MongoDB, PostgreSQL)
|
||||
- Object storage and file systems
|
||||
- Service configurations
|
||||
- Message queues and event streams
|
||||
- User data and preferences
|
||||
|
||||
### System Integration
|
||||
- Infrastructure as Code systems
|
||||
- Monitoring and alerting
|
||||
- Compliance reporting
|
||||
- Operations management tools
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Backup Tools**: Cloud-native backup solutions
|
||||
- **Storage**: Object storage with versioning
|
||||
- **Orchestration**: Infrastructure as Code for recovery
|
||||
- **Monitoring**: Backup health and status monitoring
|
||||
- **Automation**: Scripted recovery procedures
|
||||
|
||||
### Architecture Pattern
|
||||
- Centralized backup management
|
||||
- Distributed backup agents
|
||||
- Immutable backup storage
|
||||
- Recovery validation automation
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Backup Strategy
|
||||
- Backup frequency guidelines
|
||||
- Retention period standards
|
||||
- Versioning requirements
|
||||
- Validation procedures
|
||||
|
||||
### Recovery Procedures
|
||||
- Recovery time objectives
|
||||
- Recovery point objectives
|
||||
- Testing frequency requirements
|
||||
- Documentation standards
|
||||
|
||||
### Security Requirements
|
||||
- Encryption standards
|
||||
- Access control implementation
|
||||
- Audit requirements
|
||||
- Secure deletion procedures
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Core database backup capabilities
|
||||
2. Basic recovery procedures
|
||||
3. Cross-region replication
|
||||
4. Automated recovery testing
|
||||
5. Advanced protection features
|
||||
|
|
@ -1,90 +0,0 @@
|
|||
# Configuration Management
|
||||
|
||||
## Overview
|
||||
The Configuration Management service will provide centralized management of application and service configurations across the stock-bot platform. It will handle environment-specific settings, dynamic configuration updates, secrets management, and configuration versioning to ensure consistent and secure system configuration.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### Configuration Storage
|
||||
- **Hierarchical Configuration**: Nested configuration structure
|
||||
- **Environment Separation**: Environment-specific configurations
|
||||
- **Schema Validation**: Configuration format validation
|
||||
- **Default Values**: Fallback configuration defaults
|
||||
- **Configuration as Code**: Version-controlled configuration
|
||||
|
||||
### Dynamic Configuration
|
||||
- **Runtime Updates**: Changes without service restart
|
||||
- **Configuration Propagation**: Real-time distribution of changes
|
||||
- **Subscription Model**: Configuration change notifications
|
||||
- **Batch Updates**: Atomic multi-value changes
|
||||
- **Feature Flags**: Dynamic feature enablement
|
||||
|
||||
### Secrets Management
|
||||
- **Secure Storage**: Encrypted storage of sensitive values
|
||||
- **Access Control**: Fine-grained access to secrets
|
||||
- **Secret Versioning**: Historical versions of secrets
|
||||
- **Automatic Rotation**: Scheduled credential rotation
|
||||
- **Key Management**: Management of encryption keys
|
||||
|
||||
### Operational Features
|
||||
- **Configuration History**: Tracking of configuration changes
|
||||
- **Rollbacks**: Revert to previous configurations
|
||||
- **Audit Trail**: Comprehensive change logging
|
||||
- **Configuration Comparison**: Diff between configurations
|
||||
- **Import/Export**: Bulk configuration operations
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Service Integration
|
||||
- All platform microservices
|
||||
- CI/CD pipelines
|
||||
- Infrastructure components
|
||||
- Development environments
|
||||
|
||||
### External Systems
|
||||
- Secret management services
|
||||
- Source control systems
|
||||
- Operational monitoring
|
||||
- Compliance systems
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Configuration Server**: Spring Cloud Config or custom solution
|
||||
- **Secret Store**: HashiCorp Vault or AWS Secrets Manager
|
||||
- **Storage**: Git-backed or database storage
|
||||
- **API**: RESTful interface with versioning
|
||||
- **SDK**: Client libraries for service integration
|
||||
|
||||
### Architecture Pattern
|
||||
- Configuration as a service
|
||||
- Event-driven configuration updates
|
||||
- Layered access control model
|
||||
- High-availability design
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Configuration Structure
|
||||
- Naming conventions
|
||||
- Hierarchy organization
|
||||
- Type validation
|
||||
- Documentation requirements
|
||||
|
||||
### Secret Management
|
||||
- Secret classification
|
||||
- Rotation requirements
|
||||
- Access request process
|
||||
- Emergency access procedures
|
||||
|
||||
### Integration Approach
|
||||
- Client library usage
|
||||
- Caching recommendations
|
||||
- Failure handling
|
||||
- Update processing
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Static configuration management
|
||||
2. Basic secrets storage
|
||||
3. Dynamic configuration updates
|
||||
4. Advanced secret management features
|
||||
5. Operational tooling and integration
|
||||
|
|
@ -1,91 +0,0 @@
|
|||
# Logging & Monitoring
|
||||
|
||||
## Overview
|
||||
The Logging & Monitoring service will provide comprehensive observability capabilities for the stock-bot platform. It will collect, process, store, and visualize logs, metrics, and traces from all platform components, enabling effective operational monitoring, troubleshooting, and performance optimization.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### Centralized Logging
|
||||
- **Log Aggregation**: Collection of logs from all services
|
||||
- **Structured Logging**: Standardized log format across services
|
||||
- **Log Processing**: Parsing, enrichment, and transformation
|
||||
- **Log Storage**: Efficient storage with retention policies
|
||||
- **Log Search**: Advanced search capabilities with indexing
|
||||
|
||||
### Metrics Collection
|
||||
- **System Metrics**: CPU, memory, disk, network usage
|
||||
- **Application Metrics**: Custom application-specific metrics
|
||||
- **Business Metrics**: Trading and performance indicators
|
||||
- **SLI/SLO Tracking**: Service level indicators and objectives
|
||||
- **Alerting Thresholds**: Metric-based alert configuration
|
||||
|
||||
### Distributed Tracing
|
||||
- **Request Tracing**: End-to-end tracing of requests
|
||||
- **Span Collection**: Detailed operation timing
|
||||
- **Trace Correlation**: Connect logs, metrics, and traces
|
||||
- **Latency Analysis**: Performance bottleneck identification
|
||||
- **Dependency Mapping**: Service dependency visualization
|
||||
|
||||
### Alerting & Notification
|
||||
- **Alert Rules**: Multi-condition alert definitions
|
||||
- **Notification Channels**: Email, SMS, chat integrations
|
||||
- **Alert Grouping**: Intelligent alert correlation
|
||||
- **Escalation Policies**: Tiered notification escalation
|
||||
- **On-call Management**: Rotation and scheduling
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Data Sources
|
||||
- All platform microservices
|
||||
- Infrastructure components
|
||||
- Databases and storage systems
|
||||
- Message bus and event streams
|
||||
- External dependencies
|
||||
|
||||
### Consumers
|
||||
- Operations team dashboards
|
||||
- Incident management systems
|
||||
- Capacity planning tools
|
||||
- Automated remediation systems
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Logging**: ELK Stack (Elasticsearch, Logstash, Kibana) or similar
|
||||
- **Metrics**: Prometheus and Grafana
|
||||
- **Tracing**: Jaeger or Zipkin
|
||||
- **Alerting**: AlertManager or PagerDuty
|
||||
- **Collection**: Vector, Fluentd, or similar collectors
|
||||
|
||||
### Architecture Pattern
|
||||
- Centralized collection with distributed agents
|
||||
- Push and pull metric collection models
|
||||
- Sampling for high-volume telemetry
|
||||
- Buffering for resilient data collection
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Instrumentation Standards
|
||||
- Logging best practices
|
||||
- Metric naming conventions
|
||||
- Trace instrumentation approach
|
||||
- Cardinality management
|
||||
|
||||
### Performance Impact
|
||||
- Sampling strategies
|
||||
- Buffer configurations
|
||||
- Resource utilization limits
|
||||
- Batching recommendations
|
||||
|
||||
### Data Management
|
||||
- Retention policies
|
||||
- Aggregation strategies
|
||||
- Storage optimization
|
||||
- Query efficiency guidelines
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Core logging infrastructure
|
||||
2. Basic metrics collection
|
||||
3. Critical alerting capability
|
||||
4. Distributed tracing
|
||||
5. Advanced analytics and visualization
|
||||
|
|
@ -1,84 +0,0 @@
|
|||
# Service Discovery
|
||||
|
||||
## Overview
|
||||
The Service Discovery component will provide dynamic registration, discovery, and health monitoring of services within the stock-bot platform. It will enable services to locate and communicate with each other without hardcoded endpoints, supporting a flexible and resilient microservices architecture.
|
||||
|
||||
## Planned Features
|
||||
|
||||
### Service Registration
|
||||
- **Automatic Registration**: Self-registration of services on startup
|
||||
- **Metadata Management**: Service capabilities and endpoint information
|
||||
- **Instance Tracking**: Multiple instances of the same service
|
||||
- **Version Information**: Service version and compatibility data
|
||||
- **Registration Expiry**: TTL-based registration with renewal
|
||||
|
||||
### Service Discovery
|
||||
- **Name-based Lookup**: Find services by logical names
|
||||
- **Filtering**: Discovery based on metadata and attributes
|
||||
- **Load Balancing**: Client or server-side load balancing
|
||||
- **Caching**: Client-side caching of service information
|
||||
- **DNS Integration**: Optional DNS-based discovery
|
||||
|
||||
### Health Monitoring
|
||||
- **Health Checks**: Customizable health check protocols
|
||||
- **Automatic Deregistration**: Removal of unhealthy instances
|
||||
- **Status Propagation**: Health status notifications
|
||||
- **Dependency Health**: Cascading health status for dependencies
|
||||
- **Self-healing**: Automatic recovery procedures
|
||||
|
||||
### Configuration Management
|
||||
- **Dynamic Configuration**: Runtime configuration updates
|
||||
- **Environment-specific Settings**: Configuration by environment
|
||||
- **Configuration Versioning**: History and rollback capabilities
|
||||
- **Secret Management**: Secure handling of sensitive configuration
|
||||
- **Configuration Change Events**: Notifications of config changes
|
||||
|
||||
## Planned Integration Points
|
||||
|
||||
### Service Integration
|
||||
- All platform microservices
|
||||
- External service dependencies
|
||||
- Infrastructure components
|
||||
- Monitoring systems
|
||||
|
||||
## Planned Technical Implementation
|
||||
|
||||
### Technology Stack
|
||||
- **Service Registry**: Consul, etcd, or ZooKeeper
|
||||
- **Client Libraries**: TypeScript SDK for services
|
||||
- **Health Check**: HTTP, TCP, and custom health checks
|
||||
- **Configuration Store**: Distributed key-value store
|
||||
- **Load Balancer**: Client-side or service mesh integration
|
||||
|
||||
### Architecture Pattern
|
||||
- Service registry pattern
|
||||
- Client-side discovery pattern
|
||||
- Health check pattern
|
||||
- Circuit breaker integration
|
||||
|
||||
## Development Guidelines
|
||||
|
||||
### Service Integration
|
||||
- Registration process
|
||||
- Discovery implementation
|
||||
- Health check implementation
|
||||
- Configuration consumption
|
||||
|
||||
### Resilience Practices
|
||||
- Caching strategy
|
||||
- Fallback mechanisms
|
||||
- Retry configuration
|
||||
- Circuit breaker settings
|
||||
|
||||
### Operational Considerations
|
||||
- High availability setup
|
||||
- Disaster recovery approach
|
||||
- Scaling guidelines
|
||||
- Monitoring requirements
|
||||
|
||||
## Implementation Roadmap
|
||||
1. Core service registry implementation
|
||||
2. Basic health checking
|
||||
3. Service discovery integration
|
||||
4. Configuration management
|
||||
5. Advanced health monitoring with dependency tracking
|
||||
|
|
@ -1,358 +0,0 @@
|
|||
# 🏗️ Stock Bot System Architecture
|
||||
|
||||
## System Communication Flow Diagram
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
%% External Systems
|
||||
subgraph "External APIs"
|
||||
AV[Alpha Vantage API]
|
||||
YF[Yahoo Finance API]
|
||||
AL[Alpaca Broker API]
|
||||
IB[Interactive Brokers]
|
||||
NEWS[News APIs]
|
||||
end
|
||||
|
||||
%% Core Services Layer
|
||||
subgraph "Core Services"
|
||||
MDG[Market Data Gateway<br/>:3001]
|
||||
RG[Risk Guardian<br/>:3002]
|
||||
EE[Execution Engine<br/>:3003]
|
||||
PM[Portfolio Manager<br/>:3004]
|
||||
end
|
||||
|
||||
%% Intelligence Services Layer
|
||||
subgraph "Intelligence Services"
|
||||
SO[Strategy Orchestrator<br/>:4001]
|
||||
SG[Signal Generator<br/>:4002]
|
||||
BA[Backtesting Engine<br/>:4003]
|
||||
ML[ML Pipeline<br/>:4004]
|
||||
end
|
||||
|
||||
%% Data Services Layer
|
||||
subgraph "Data Services"
|
||||
HDS[Historical Data Service<br/>:5001]
|
||||
AS[Analytics Service<br/>:5002]
|
||||
DQS[Data Quality Service<br/>:5003]
|
||||
ETLS[ETL Service<br/>:5004]
|
||||
end
|
||||
|
||||
%% Platform Services Layer
|
||||
subgraph "Platform Services"
|
||||
LM[Log Manager<br/>:6001]
|
||||
CM[Config Manager<br/>:6002]
|
||||
AM[Alert Manager<br/>:6003]
|
||||
SM[Service Monitor<br/>:6004]
|
||||
end
|
||||
|
||||
%% Integration Services Layer
|
||||
subgraph "Integration Services"
|
||||
BAS[Broker Adapter<br/>:7001]
|
||||
DAS[Data Adapter<br/>:7002]
|
||||
NS[Notification Service<br/>:7003]
|
||||
WHS[Webhook Service<br/>:7004]
|
||||
end
|
||||
|
||||
%% Interface Services Layer
|
||||
subgraph "Interface Services"
|
||||
TD[Trading Dashboard<br/>:5173]
|
||||
API[REST API Gateway<br/>:8001]
|
||||
WS[WebSocket Server<br/>Embedded]
|
||||
end
|
||||
|
||||
%% Storage Layer
|
||||
subgraph "Storage Layer"
|
||||
DRAGONFLY[(Dragonfly<br/>Events & Cache)]
|
||||
QDB[(QuestDB<br/>Time Series)]
|
||||
PGDB[(PostgreSQL<br/>Relational)]
|
||||
FS[(File System<br/>Logs & Config)]
|
||||
end
|
||||
|
||||
%% Communication Flows
|
||||
|
||||
%% External to Core
|
||||
AV --> MDG
|
||||
YF --> MDG
|
||||
AL --> BAS
|
||||
IB --> BAS
|
||||
NEWS --> DAS
|
||||
|
||||
%% Core Service Communications
|
||||
MDG -->|Market Data Events| DRAGONFLY
|
||||
MDG -->|Real-time Stream| WS
|
||||
MDG -->|Cache| DRAGONFLY
|
||||
|
||||
RG -->|Risk Events| DRAGONFLY
|
||||
RG -->|Risk Alerts| AM
|
||||
RG -->|Position Limits| PM
|
||||
|
||||
EE -->|Order Events| DRAGONFLY
|
||||
EE -->|Trade Execution| BAS
|
||||
EE -->|Order Status| PM
|
||||
|
||||
PM -->|Portfolio Events| DRAGONFLY
|
||||
PM -->|P&L Updates| TD
|
||||
PM -->|Position Data| RG
|
||||
|
||||
%% Intelligence Communications
|
||||
SO -->|Strategy Events| DRAGONFLY
|
||||
SO -->|Signal Requests| SG
|
||||
SO -->|Execution Orders| EE
|
||||
SO -->|Risk Check| RG
|
||||
|
||||
SG -->|Trading Signals| SO
|
||||
SG -->|ML Requests| ML
|
||||
SG -->|Market Data| DRAGONFLY
|
||||
|
||||
BA -->|Backtest Results| SO
|
||||
BA -->|Historical Data| HDS
|
||||
|
||||
ML -->|Predictions| SG
|
||||
ML -->|Training Data| HDS
|
||||
|
||||
%% Data Service Communications
|
||||
HDS -->|Store Data| QDB
|
||||
HDS -->|Query Data| QDB
|
||||
HDS -->|Data Events| DRAGONFLY
|
||||
|
||||
AS -->|Analytics| QDB
|
||||
AS -->|Metrics| SM
|
||||
AS -->|Reports| TD
|
||||
|
||||
DQS -->|Data Quality| DRAGONFLY
|
||||
DQS -->|Alerts| AM
|
||||
|
||||
ETLS -->|Raw Data| DAS
|
||||
ETLS -->|Processed Data| HDS
|
||||
|
||||
%% Platform Communications
|
||||
LM -->|Logs| FS
|
||||
LM -->|Log Events| DRAGONFLY
|
||||
|
||||
CM -->|Config| FS
|
||||
CM -->|Config Updates| DRAGONFLY
|
||||
|
||||
AM -->|Alerts| NS
|
||||
AM -->|Alert Events| DRAGONFLY
|
||||
|
||||
SM -->|Health Checks| DRAGONFLY
|
||||
SM -->|Metrics| QDB
|
||||
|
||||
%% Integration Communications
|
||||
BAS -->|Orders| AL
|
||||
BAS -->|Orders| IB
|
||||
BAS -->|Order Updates| EE
|
||||
|
||||
DAS -->|Data Feed| MDG
|
||||
DAS -->|External Data| HDS
|
||||
|
||||
NS -->|Notifications| WHS
|
||||
NS -->|Alerts| TD
|
||||
|
||||
WHS -->|Webhooks| External
|
||||
|
||||
%% Interface Communications
|
||||
TD -->|API Calls| API
|
||||
TD -->|WebSocket| WS
|
||||
TD -->|Dashboard Data| PM
|
||||
|
||||
API -->|Service Calls| SO
|
||||
API -->|Data Queries| HDS
|
||||
API -->|System Status| SM
|
||||
|
||||
WS -->|Real-time Data| TD
|
||||
WS -->|Events| DRAGONFLY
|
||||
|
||||
%% Storage Access DRAGONFLY -.->|Events| SO
|
||||
DRAGONFLY -.->|Events| RG
|
||||
DRAGONFLY -.->|Events| PM
|
||||
DRAGONFLY -.->|Cache| MDG
|
||||
|
||||
QDB -.->|Time Series| HDS
|
||||
QDB -.->|Analytics| AS
|
||||
QDB -.->|Metrics| SM
|
||||
|
||||
PGDB -.->|Relational| PM
|
||||
PGDB -.->|Config| CM
|
||||
PGDB -.->|Users| API
|
||||
|
||||
%% Styling
|
||||
classDef external fill:#ff9999
|
||||
classDef core fill:#99ccff
|
||||
classDef intelligence fill:#99ff99
|
||||
classDef data fill:#ffcc99
|
||||
classDef platform fill:#cc99ff
|
||||
classDef integration fill:#ffff99
|
||||
classDef interface fill:#ff99cc
|
||||
classDef storage fill:#cccccc
|
||||
|
||||
class AV,YF,AL,IB,NEWS external
|
||||
class MDG,RG,EE,PM core
|
||||
class SO,SG,BA,ML intelligence
|
||||
class HDS,AS,DQS,ETLS data
|
||||
class LM,CM,AM,SM platform
|
||||
class BAS,DAS,NS,WHS integration
|
||||
class TD,API,WS interface
|
||||
class DRAGONFLY,QDB,PGDB,FS storage
|
||||
```
|
||||
|
||||
## Communication Patterns
|
||||
|
||||
### 1. **Event-Driven Architecture (Dragonfly Streams)**
|
||||
```
|
||||
┌─────────────┐ Dragonfly Events ┌─────────────┐
|
||||
│ Service │ ─────────────────→ │ Service │
|
||||
│ A │ │ B │
|
||||
└─────────────┘ └─────────────┘
|
||||
```
|
||||
|
||||
**Event Types:**
|
||||
- `MARKET_DATA` - Real-time price updates
|
||||
- `ORDER_CREATED/FILLED/CANCELLED` - Order lifecycle
|
||||
- `SIGNAL_GENERATED` - Trading signals
|
||||
- `RISK_ALERT` - Risk threshold violations
|
||||
- `PORTFOLIO_UPDATE` - Position changes
|
||||
- `STRATEGY_START/STOP` - Strategy lifecycle
|
||||
|
||||
### 2. **Request-Response (HTTP/REST)**
|
||||
```
|
||||
┌─────────────┐ HTTP Request ┌─────────────┐
|
||||
│ Client │ ─────────────────→ │ Service │
|
||||
│ │ ←───────────────── │ │
|
||||
└─────────────┘ HTTP Response └─────────────┘
|
||||
```
|
||||
|
||||
**API Endpoints:**
|
||||
- `/api/market-data/:symbol` - Current market data
|
||||
- `/api/portfolio/positions` - Portfolio positions
|
||||
- `/api/strategies` - Strategy management
|
||||
- `/api/orders` - Order management
|
||||
- `/api/health` - Service health checks
|
||||
|
||||
### 3. **Real-time Streaming (WebSocket)**
|
||||
```
|
||||
┌─────────────┐ WebSocket ┌─────────────┐
|
||||
│ Client │ ←═════════════════→ │ Server │
|
||||
│ │ Bidirectional │ │
|
||||
└─────────────┘ └─────────────┘
|
||||
```
|
||||
|
||||
**WebSocket Messages:**
|
||||
- Market data subscriptions
|
||||
- Portfolio updates
|
||||
- Trading signals
|
||||
- Risk alerts
|
||||
- System notifications
|
||||
|
||||
### 4. **Data Persistence**
|
||||
```
|
||||
┌─────────────┐ Store/Query ┌─────────────┐
|
||||
│ Service │ ─────────────────→ │ Database │
|
||||
│ │ ←───────────────── │ │
|
||||
└─────────────┘ └─────────────┘
|
||||
```
|
||||
|
||||
**Storage Types:**
|
||||
- **Dragonfly**: Events, cache, sessions
|
||||
- **QuestDB**: Time-series data, metrics
|
||||
- **PostgreSQL**: Configuration, users, metadata
|
||||
- **File System**: Logs, configurations
|
||||
|
||||
## Service Communication Matrix
|
||||
|
||||
| Service | Publishes Events | Subscribes to Events | HTTP APIs | WebSocket | Storage |
|
||||
|---------|-----------------|---------------------|-----------|-----------|---------|
|
||||
| Market Data Gateway | ✅ Market Data | - | ✅ REST | ✅ Server | Dragonfly Cache |
|
||||
| Risk Guardian | ✅ Risk Alerts | ✅ All Events | ✅ REST | - | PostgreSQL |
|
||||
| Strategy Orchestrator | ✅ Strategy Events | ✅ Market Data, Signals | ✅ REST | - | PostgreSQL |
|
||||
| Execution Engine | ✅ Order Events | ✅ Strategy Events | ✅ REST | - | PostgreSQL |
|
||||
| Portfolio Manager | ✅ Portfolio Events | ✅ Order Events | ✅ REST | - | PostgreSQL |
|
||||
| Trading Dashboard | - | ✅ All Events | ✅ Client | ✅ Client | - |
|
||||
|
||||
## Data Flow Example: Trade Execution
|
||||
|
||||
```mermaid
|
||||
sequenceDiagram
|
||||
participant TD as Trading Dashboard
|
||||
participant SO as Strategy Orchestrator
|
||||
participant SG as Signal Generator
|
||||
participant RG as Risk Guardian
|
||||
participant EE as Execution Engine
|
||||
participant BAS as Broker Adapter
|
||||
participant PM as Portfolio Manager
|
||||
participant DRAGONFLY as Dragonfly Events
|
||||
|
||||
Note over TD,DRAGONFLY: User starts a trading strategy
|
||||
|
||||
TD->>SO: POST /api/strategies/start
|
||||
SO->>DRAGONFLY: Publish STRATEGY_START event
|
||||
|
||||
Note over SO,SG: Strategy generates signals
|
||||
|
||||
SO->>SG: Request signals for AAPL
|
||||
SG->>SO: Return BUY signal
|
||||
SO->>DRAGONFLY: Publish SIGNAL_GENERATED event
|
||||
|
||||
Note over SO,RG: Risk check before execution
|
||||
|
||||
SO->>RG: Check risk limits
|
||||
RG->>SO: Risk approved
|
||||
|
||||
Note over SO,EE: Execute the trade
|
||||
|
||||
SO->>EE: Submit order
|
||||
EE->>DRAGONFLY: Publish ORDER_CREATED event
|
||||
EE->>BAS: Send order to broker
|
||||
BAS->>EE: Order filled
|
||||
EE->>DRAGONFLY: Publish ORDER_FILLED event
|
||||
|
||||
Note over PM,TD: Update portfolio and notify user
|
||||
|
||||
PM->>DRAGONFLY: Subscribe to ORDER_FILLED
|
||||
PM->>PM: Update positions PM->>DRAGONFLY: Publish PORTFOLIO_UPDATE
|
||||
TD->>DRAGONFLY: Subscribe to PORTFOLIO_UPDATE
|
||||
TD->>TD: Update dashboard
|
||||
```
|
||||
|
||||
## Port Allocation
|
||||
|
||||
| Service Category | Port Range | Services |
|
||||
|-----------------|------------|----------|
|
||||
| Core Services | 3001-3099 | Market Data Gateway (3001), Risk Guardian (3002) |
|
||||
| Intelligence Services | 4001-4099 | Strategy Orchestrator (4001), Signal Generator (4002) |
|
||||
| Data Services | 5001-5099 | Historical Data (5001), Analytics (5002) |
|
||||
| Platform Services | 6001-6099 | Log Manager (6001), Config Manager (6002) |
|
||||
| Integration Services | 7001-7099 | Broker Adapter (7001), Data Adapter (7002) |
|
||||
| Interface Services | 8001-8099 | API Gateway (8001), Dashboard (5173-Vite) |
|
||||
|
||||
## Security & Authentication
|
||||
|
||||
```mermaid
|
||||
graph LR
|
||||
subgraph "Security Layer"
|
||||
JWT[JWT Tokens]
|
||||
API_KEY[API Keys]
|
||||
TLS[TLS/HTTPS]
|
||||
RBAC[Role-Based Access]
|
||||
end
|
||||
|
||||
subgraph "External Security"
|
||||
BROKER_AUTH[Broker Authentication]
|
||||
DATA_AUTH[Data Provider Auth]
|
||||
WEBHOOK_SIG[Webhook Signatures]
|
||||
end
|
||||
|
||||
JWT --> API_KEY
|
||||
API_KEY --> TLS
|
||||
TLS --> RBAC
|
||||
RBAC --> BROKER_AUTH
|
||||
BROKER_AUTH --> DATA_AUTH
|
||||
DATA_AUTH --> WEBHOOK_SIG
|
||||
```
|
||||
|
||||
This architecture provides:
|
||||
- **Scalability**: Services can be scaled independently
|
||||
- **Reliability**: Event-driven communication with retry mechanisms
|
||||
- **Maintainability**: Clear separation of concerns
|
||||
- **Observability**: Centralized logging and monitoring
|
||||
- **Security**: Multiple layers of authentication and authorization
|
||||
|
|
@ -1,140 +0,0 @@
|
|||
# 📊 Stock Bot System Communication - Quick Reference
|
||||
|
||||
## Current System (Active)
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────────────┐
|
||||
│ TRADING BOT SYSTEM │
|
||||
└─────────────────────────────────────────────────────────────────────┘
|
||||
|
||||
External APIs Core Services Interface Services
|
||||
┌─────────────┐ ┌─────────────────┐ ┌─────────────────┐
|
||||
│ Demo Data │──────▶│ Market Data │◀──────▶│ Trading │
|
||||
│ Alpha Vant. │ │ Gateway │ │ Dashboard │
|
||||
│ Yahoo Fin. │ │ Port: 3001 │ │ Port: 5173 │
|
||||
└─────────────┘ │ Status: ✅ LIVE │ │ Status: ✅ LIVE │
|
||||
└─────────────────┘ └─────────────────┘
|
||||
│ ▲
|
||||
▼ │
|
||||
┌─────────────────┐ │
|
||||
│ Dragonfly Events │─────────────────┘
|
||||
│ Cache & Streams │
|
||||
│ Status: ✅ READY│
|
||||
└─────────────────┘
|
||||
```
|
||||
|
||||
## Next Phase (Ready to Implement)
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────────────┐
|
||||
│ EXPANDED TRADING SYSTEM │
|
||||
└─────────────────────────────────────────────────────────────────────┘
|
||||
|
||||
Intelligence Services Core Services Interface Services
|
||||
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
|
||||
│ Strategy │◀────▶│ Market Data │◀───▶│ Trading │
|
||||
│ Orchestrator │ │ Gateway │ │ Dashboard │
|
||||
│ Port: 4001 │ │ Port: 3001 │ │ Port: 5173 │
|
||||
│ Status: 📋 PLAN │ │ Status: ✅ LIVE │ │ Status: ✅ LIVE │
|
||||
└─────────────────┘ └─────────────────┘ └─────────────────┘
|
||||
▲ │ ▲
|
||||
│ ▼ │
|
||||
│ ┌─────────────────┐ │
|
||||
└──────────────▶│ Dragonfly Event │◀─────────────┘
|
||||
│ Stream Hub │
|
||||
│ Status: ✅ READY│
|
||||
└─────────────────┘
|
||||
▲
|
||||
│
|
||||
┌─────────────────┐
|
||||
│ Risk Guardian │
|
||||
│ Port: 3002 │
|
||||
│ Status: 📋 PLAN │
|
||||
└─────────────────┘
|
||||
```
|
||||
|
||||
## Communication Protocols
|
||||
|
||||
### HTTP REST API
|
||||
```
|
||||
Client ──── GET/POST ───▶ Server
|
||||
◀─── JSON ────────
|
||||
```
|
||||
|
||||
### WebSocket Real-time
|
||||
```
|
||||
Client ◀═══ Stream ═══▶ Server
|
||||
◀═══ Events ══▶
|
||||
```
|
||||
|
||||
### Dragonfly Event Bus
|
||||
```
|
||||
Service A ──── Publish ───▶ Dragonfly ──── Subscribe ───▶ Service B
|
||||
◀─── Confirm ──── ◀─── Events ────
|
||||
```
|
||||
|
||||
## Event Types
|
||||
|
||||
| Event Type | Publisher | Subscribers | Frequency |
|
||||
|------------|-----------|-------------|-----------|
|
||||
| `MARKET_DATA` | Market Data Gateway | Dashboard, Strategy Orchestrator | Every 5s |
|
||||
| `SIGNAL_GENERATED` | Strategy Orchestrator | Risk Guardian, Execution Engine | As needed |
|
||||
| `RISK_ALERT` | Risk Guardian | Dashboard, Alert Manager | As needed |
|
||||
| `PORTFOLIO_UPDATE` | Portfolio Manager | Dashboard, Risk Guardian | On trades |
|
||||
|
||||
## Service Status Matrix
|
||||
|
||||
| Service | Port | Status | Dependencies | Ready to Implement |
|
||||
|---------|------|--------|--------------|-------------------|
|
||||
| Market Data Gateway | 3001 | ✅ Running | Dragonfly, Config | ✅ Complete |
|
||||
| Trading Dashboard | 5173 | ✅ Running | MDG API | ✅ Complete |
|
||||
| Strategy Orchestrator | 4001 | 📋 Planned | Dragonfly, MDG | ✅ Package Ready |
|
||||
| Risk Guardian | 3002 | 📋 Planned | Dragonfly, Config | ✅ Package Ready |
|
||||
| Portfolio Manager | 3004 | ⏳ Future | Database, Orders | ❌ Not Started |
|
||||
| Execution Engine | 3003 | ⏳ Future | Brokers, Portfolio | ❌ Not Started |
|
||||
|
||||
## Data Flow Summary
|
||||
|
||||
1. **Market Data Flow**
|
||||
```
|
||||
External APIs → Market Data Gateway → Dragonfly Events → Dashboard
|
||||
→ Strategy Orchestrator
|
||||
```
|
||||
|
||||
2. **Trading Signal Flow**
|
||||
```
|
||||
Market Data → Strategy Orchestrator → Trading Signals → Risk Guardian
|
||||
→ Execution Engine
|
||||
```
|
||||
|
||||
3. **Risk Management Flow**
|
||||
```
|
||||
All Events → Risk Guardian → Risk Alerts → Alert Manager
|
||||
→ Risk Blocks → Strategy Orchestrator
|
||||
```
|
||||
|
||||
4. **User Interface Flow**
|
||||
```
|
||||
WebSocket ← Dashboard → REST API → Services
|
||||
Events ← → Commands →
|
||||
```
|
||||
|
||||
## Implementation Priority
|
||||
|
||||
### Phase 1 (Current) ✅
|
||||
- [x] Market Data Gateway
|
||||
- [x] Trading Dashboard
|
||||
- [x] Dragonfly Infrastructure
|
||||
- [x] WebSocket Communication
|
||||
|
||||
### Phase 2 (Next) 📋
|
||||
- [ ] Strategy Orchestrator
|
||||
- [ ] Risk Guardian
|
||||
- [ ] Event-driven Strategy Execution
|
||||
- [ ] Risk Monitoring & Alerts
|
||||
|
||||
### Phase 3 (Future) ⏳
|
||||
- [ ] Portfolio Manager
|
||||
- [ ] Execution Engine
|
||||
- [ ] Broker Integration
|
||||
- [ ] Database Persistence
|
||||
|
||||
The system is designed for incremental development where each service can be implemented and tested independently while maintaining full system functionality.
|
||||
|
|
@ -1,247 +0,0 @@
|
|||
# WebSocket API Documentation - Strategy Orchestrator
|
||||
|
||||
## Overview
|
||||
|
||||
This document outlines the WebSocket API provided by the Strategy Orchestrator service for real-time communication between the backend and frontend.
|
||||
|
||||
## Connection Endpoints
|
||||
|
||||
- **Strategy Orchestrator WebSocket:** `ws://localhost:8082`
|
||||
- **Market Data Gateway WebSocket:** `ws://localhost:3001/ws`
|
||||
- **Risk Guardian WebSocket:** `ws://localhost:3002/ws`
|
||||
|
||||
## Message Format
|
||||
|
||||
All WebSocket messages follow this standard format:
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "message_type",
|
||||
"timestamp": "ISO-8601 timestamp",
|
||||
"data": {
|
||||
// Message-specific data
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Client to Server Messages
|
||||
|
||||
### Get Active Strategies
|
||||
|
||||
Request information about all active strategies.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "get_active_strategies"
|
||||
}
|
||||
```
|
||||
|
||||
### Start Strategy
|
||||
|
||||
Start a specific strategy.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "start_strategy",
|
||||
"id": "strategy-id",
|
||||
"config": {
|
||||
"symbols": ["AAPL", "MSFT"],
|
||||
"dataResolution": "1m",
|
||||
"realTrading": false,
|
||||
"maxPositionValue": 10000,
|
||||
"maxOrdersPerMinute": 5,
|
||||
"stopLossPercentage": 0.02
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Stop Strategy
|
||||
|
||||
Stop a running strategy.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "stop_strategy",
|
||||
"id": "strategy-id"
|
||||
}
|
||||
```
|
||||
|
||||
### Pause Strategy
|
||||
|
||||
Pause a running strategy.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "pause_strategy",
|
||||
"id": "strategy-id"
|
||||
}
|
||||
```
|
||||
|
||||
## Server to Client Messages
|
||||
|
||||
### Strategy Status List
|
||||
|
||||
Response to `get_active_strategies` request.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "strategy_status_list",
|
||||
"timestamp": "2023-07-10T12:34:56Z",
|
||||
"data": [
|
||||
{
|
||||
"id": "strategy-123",
|
||||
"name": "Moving Average Crossover",
|
||||
"status": "ACTIVE",
|
||||
"symbols": ["AAPL", "MSFT"],
|
||||
"positions": [
|
||||
{
|
||||
"symbol": "AAPL",
|
||||
"quantity": 10,
|
||||
"entryPrice": 150.25,
|
||||
"currentValue": 1550.50
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### Strategy Started
|
||||
|
||||
Notification that a strategy has been started.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "strategy_started",
|
||||
"timestamp": "2023-07-10T12:34:56Z",
|
||||
"data": {
|
||||
"strategyId": "strategy-123",
|
||||
"name": "Moving Average Crossover",
|
||||
"symbols": ["AAPL", "MSFT"]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Strategy Stopped
|
||||
|
||||
Notification that a strategy has been stopped.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "strategy_stopped",
|
||||
"timestamp": "2023-07-10T12:34:56Z",
|
||||
"data": {
|
||||
"strategyId": "strategy-123",
|
||||
"name": "Moving Average Crossover"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Strategy Paused
|
||||
|
||||
Notification that a strategy has been paused.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "strategy_paused",
|
||||
"timestamp": "2023-07-10T12:34:56Z",
|
||||
"data": {
|
||||
"strategyId": "strategy-123",
|
||||
"name": "Moving Average Crossover"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Strategy Signal
|
||||
|
||||
Trading signal generated by a strategy.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "strategy_signal",
|
||||
"timestamp": "2023-07-10T12:34:56Z",
|
||||
"data": {
|
||||
"id": "sig_123456789",
|
||||
"strategyId": "strategy-123",
|
||||
"name": "Moving Average Crossover",
|
||||
"symbol": "AAPL",
|
||||
"price": 152.75,
|
||||
"action": "BUY",
|
||||
"quantity": 10,
|
||||
"metadata": { "orderType": "MARKET" },
|
||||
"timestamp": "2023-07-10T12:34:56Z",
|
||||
"confidence": 0.9
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Strategy Trade
|
||||
|
||||
Notification of a trade executed by a strategy.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "strategy_trade",
|
||||
"timestamp": "2023-07-10T12:34:56Z",
|
||||
"data": {
|
||||
"id": "trade_123456789",
|
||||
"strategyId": "strategy-123",
|
||||
"orderId": "order-123",
|
||||
"symbol": "AAPL",
|
||||
"side": "BUY",
|
||||
"quantity": 10,
|
||||
"entryPrice": 152.75,
|
||||
"entryTime": "2023-07-10T12:34:56Z",
|
||||
"status": "FILLED",
|
||||
"timestamp": "2023-07-10T12:34:56Z"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Execution Service Status
|
||||
|
||||
Notification about the overall execution service status.
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "execution_service_status",
|
||||
"timestamp": "2023-07-10T12:34:56Z",
|
||||
"data": {
|
||||
"status": "RUNNING" // or "STOPPED"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Frontend Integration
|
||||
|
||||
The frontend can use the `WebSocketService` to interact with the WebSocket API:
|
||||
|
||||
```typescript
|
||||
// Subscribe to strategy signals
|
||||
webSocketService.getStrategySignals(strategyId)
|
||||
.subscribe(signal => {
|
||||
// Handle the signal
|
||||
});
|
||||
|
||||
// Subscribe to strategy trades
|
||||
webSocketService.getStrategyTrades(strategyId)
|
||||
.subscribe(trade => {
|
||||
// Handle the trade
|
||||
});
|
||||
|
||||
// Subscribe to strategy status updates
|
||||
webSocketService.getStrategyUpdates()
|
||||
.subscribe(update => {
|
||||
// Handle the update
|
||||
});
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
|
||||
WebSocket connections will automatically attempt to reconnect if disconnected. The frontend can monitor connection status using:
|
||||
|
||||
```typescript
|
||||
webSocketService.isConnected() // Returns a boolean signal indicating connection status
|
||||
```
|
||||
|
||||
If a WebSocket message fails to process, the error will be logged, but the connection will be maintained.
|
||||
Loading…
Add table
Add a link
Reference in a new issue