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Infrastructure for Quantitative Trading

This directory contains templates and configurations for the technology infrastructure needed to operate quantitative trading systems at a professional scale.

Structure

infrastructure/
├── docker/              # Docker containers for services
├── kubernetes/          # Orchestration and scaling
├── monitoring/          # Monitoring and alerts
├── data-pipeline/       # Real-time data pipelines
└── README.md

Main Components

1. Docker Containers

  • Trading Engine: Core strategy execution engine
  • Market Data: Data collection and normalization
  • Risk Management: Real-time risk management system
  • Backtesting: Distributed backtesting engine
  • Analytics: Performance analysis and reporting

2. Kubernetes Orchestration

  • Auto-scaling: Automatic load-based scaling
  • High Availability: High availability configurations
  • Service Mesh: Secure inter-service communication
  • Config Management: Centralized configuration management

3. Monitoring and Observability

  • Metrics: Prometheus + Grafana for metrics
  • Logs: ELK Stack for log aggregation
  • Tracing: Jaeger for distributed tracing
  • Alerts: Multi-channel alert system

4. Data Pipeline

  • Stream Processing: Apache Kafka + Kafka Streams
  • Real-time Analytics: Apache Flink
  • Data Lake: MinIO for storage
  • Time Series DB: InfluxDB for market data

Quick Start

  1. Local Development: 
    cd docker/
docker-compose up -d
  2. Kubernetes Production: 
    cd kubernetes/
kubectl apply -f namespace.yaml
kubectl apply -f .
  3. Monitoring: 
    cd monitoring/
helm install monitoring ./charts/monitoring

Requirements

  • Docker 20.10+
  • Kubernetes 1.21+
  • Helm 3.0+
  • MinIO/S3 compatible storage
  • PostgreSQL/TimescaleDB

Configuration

Each component includes:

  • Environment variables
  • Secrets management
  • Health checks
  • Resource limits
  • Security policies

Scalability

  • Horizontal: Auto-scaling of pods based on CPU/memory
  • Vertical: Automatic resource adjustment
  • Storage: Persistent volumes with auto-provisioning
  • Network: Service mesh for efficient communication

Security

  • RBAC for access control
  • Network policies for isolation
  • Secrets encryption at rest
  • TLS for all communications
  • Compliance with financial regulations