Building a High-Throughput Multi-Cloud Trading Architecture  

Time to read: 4 min | 15 June, 2023 | Saurabh Nandedkar

Building a global trading platform presents unique challenges in latency, reliability, and regulatory compliance. This article explores the evolution of our trading architecture from a single-cloud deployment to a sophisticated multi-cloud solution, focusing on the technical decisions and architectural patterns that enabled us to achieve sub-10ms trading performance across global markets.

Technical Requirements

Initial system requirements:

  1. Latency: < 10ms trade execution
  2. Throughput: 4,000+ TPS
  3. Reliability: 99.99% uptime
  4. Compliance: Regional regulatory requirements
  5. Scalability: Support for 100,000+ concurrent users

Architecture Evolution

Phase 1: Single Cloud Implementation

Initial AWS us-east-1 architecture:

  1. Technical Limitations

    • 50-100ms latency for US traders
    • 150-200ms APAC market delays
    • Cross-region database replication bottlenecks
    • Regional API limits constraining growth
  2. Performance Constraints

    • Network latency to distant markets
    • Database replication delays
    • Limited regional scalability
    • Resource utilization inefficiencies

Phase 2: Dual-Cloud Architecture

AWS + GCP hybrid implementation:

  1. Workload Distribution Strategy

    • Market data processing in GCP Asia
    • Core trading engine in AWS US
    • Cross-cloud data synchronization
    • Regional cache layers
  2. Technical Challenges

    • Complex request routing logic
    • Cross-cloud networking costs
    • Data consistency management
    • Operational complexity

Phase 3: Multi-Cloud Architecture

Final architecture across AWS, GCP, and Azure:

  1. Regional Architecture Components

    AWS (US Markets):

    • Primary trading engine
    • US market data processing
    • Real-time order matching
    • Historical data storage
    • Compliance systems

    GCP (Asian Markets):

    • Local market data processing
    • Order validation and routing
    • Regional cache layers
    • Compliance data storage
    • Performance monitoring

    Azure (European Markets):

    • MiFID II compliance systems
    • European market connectivity
    • Regional order processing
    • Regulatory reporting systems
    • Data sovereignty management
  2. Data Distribution Architecture

    Market Data Flow:

    • Local market data ingestion
    • Regional data processing
    • Cross-region synchronization
    • Hierarchical caching system
    • Real-time feed optimization

    Order Processing Flow:

    • Regional order validation
    • Cross-region order routing
    • Global order book synchronization
    • Atomic transaction handling
    • Position management
  3. Resilience Patterns

    Active-Active Configuration:

    • All regions actively serving requests
    • Real-time workload distribution
    • Automatic failover capabilities
    • Load-based request routing
    • Health monitoring systems

    Data Consistency Management:

    • Eventually consistent user data
    • Strongly consistent order books
    • Real-time position management
    • Cross-region transaction integrity
    • Conflict resolution mechanisms

Technical Implementation Details

Market Data Processing

  1. Regional Processing Architecture

    • Local market data ingestion systems
    • Region-specific aggregation services
    • Optimized feed distribution
    • Cross-region synchronization
    • Latency optimization
  2. Caching Strategy

    • L1: In-memory market data (sub-millisecond)
    • L2: Regional cache clusters (1-5ms)
    • L3: Global persistent store (5-10ms)
    • Cache invalidation patterns
    • Consistency protocols

Order Processing System

  1. Routing Logic Implementation

    • Latency-based routing algorithms
    • Cost-optimized path selection
    • Regulatory compliance verification
    • Smart order routing systems
    • Cross-region coordination
  2. Transaction Processing

    • Regional order validation
    • Cross-region synchronization
    • Atomic execution guarantees
    • Position reconciliation
    • Risk management integration

Performance Optimization

  1. Latency Optimization

    • Network route optimization
    • Regional processing prioritization
    • Cache hierarchy implementation
    • Connection pooling
    • Protocol optimization
  2. Throughput Enhancement

    • Parallel processing pipelines
    • Batch processing optimization
    • Resource allocation strategies
    • Queue management
    • Load distribution

Monitoring and Operations

  1. Global Observability

    • Per-region performance metrics
    • Cross-region latency monitoring
    • Resource utilization tracking
    • Cost attribution metrics
    • Anomaly detection
  2. Operational Insights

    • Real-time trading patterns
    • Regional capacity utilization
    • Cross-cloud network performance
    • Global system health
    • Predictive analytics

Performance Results

  1. Latency Improvements

    • US Markets: 50ms → 5ms
    • Asian Markets: 200ms → 8ms
    • European Markets: 150ms → 7ms
    • Cross-region: 300ms → 15ms
  2. Throughput Enhancements

    • Global: 1,000 → 4,000 TPS
    • Regional: 300 → 1,500 TPS
    • Market Data: 50,000 → 200,000 messages/second
    • Order Processing: 500 → 2,000 orders/second

Technical Insights

  1. Regional Optimization

    • Local processing crucial for performance
    • Data sovereignty drives architecture
    • Regional autonomy enables scaling
    • Cache locality impacts performance
  2. Data Management

    • Consistency requirements vary by data type
    • Caching strategy critical for performance
    • Cross-region synchronization patterns matter
    • Conflict resolution mechanisms essential
  3. Operational Complexity

    • Multi-cloud expertise required
    • Unified monitoring essential
    • Automation crucial for operations
    • Cost optimization strategies important

Future Technical Roadmap

  1. Architecture Evolution

    • Edge computing integration
    • Advanced analytics capabilities
    • Machine learning optimization
    • Enhanced automation
  2. Performance Enhancements

    • Further latency reduction
    • Increased throughput capacity
    • Improved resource utilization
    • Enhanced monitoring capabilities

The implementation of this multi-cloud trading architecture demonstrates how careful consideration of regional requirements, data flow patterns, and performance optimization can create a globally efficient trading platform. The combination of local processing, sophisticated data distribution, and comprehensive monitoring enables sub-10ms trading performance while maintaining regulatory compliance across global markets.