Product Architecture Overview

use.com's product architecture is designed for modularity, scalability, and fault isolation. Rather than a monolithic system, the platform consists of independent microservices that communicate through well-defined interfaces.

Architecture Principles

Microservices Design: Each major function (matching, risk, custody, user management) operates as an independent service. This enables:

• Independent Scaling: Scale matching engines without scaling user databases

• Fault Isolation: One service failure doesn't cascade to others

• Technology Flexibility: Use optimal technology for each service

• Deployment Independence: Update services without system-wide downtime

Event-Driven Communication: Services communicate through event streams rather than direct calls, enabling:

• Loose Coupling: Services don't need to know about each other

• Audit Trail: Every action is recorded as an immutable event

• Replay Capability: Reconstruct any historical state

• Real-Time Processing: Multiple services can react to same event

Core Services

Matching Engine Service

Purpose: Execute trades with sub-millisecond latency

Key Features:

• Symbol-sharded architecture (one instance per trading pair)

• Strict price-time priority

• 100,000+ orders/second per shard

• Event-sourced state management

Performance Target: < 800 µs matching latency (p99)

Risk Engine Service

Purpose: Calculate margin requirements and trigger liquidations

Key Features:

• Real-time position monitoring

• Published liquidation formulas

• Automated liquidation ladder (25%, 25%, 50%)

• Insurance fund management

Liquidation Formula: $Liquidation_{Long} = Entry \times \left(1 - \frac{MMR}{1 + Leverage}\right)$

Custody Service

Purpose: Secure asset storage and withdrawal processing

Key Features:

• MPC + HSM key management

• Hot/warm/cold wallet segregation

• Automated rebalancing

• Withdrawal policy engine with risk scoring

Security Target: Reserve ratio > 105%

User Service

Purpose: Account management, KYC, and authentication

Key Features:

• Tiered KYC (4 levels)

• Multi-factor authentication

• Session management

• Jurisdiction-aware access control

Compliance Target: KYC completion < 24 hours

Market Data Service

Purpose: Real-time and historical market data distribution

Key Features:

• WebSocket streaming

• REST API for historical data

• Configurable update frequency

• Global edge distribution

Latency Target: < 50 ms data propagation globally

Data Flow Example

Order Placement Flow:

1. User submits order via API

2. Authentication Service validates credentials

3. Risk Service checks margin requirements

4. Matching Service executes order

5. Settlement Service updates balances

6. Market Data Service publishes trade

7. User receives confirmation

Total Time: < 15 ms (p99)

Scalability Model

Horizontal Scaling: $Capacity = \sum_{i=1}^{n} Service\_Capacity_i$

Each service scales independently based on load:

• Matching: Add shards for new trading pairs

• Risk: Add instances for position monitoring

• API: Add edge POPs for geographic coverage

• Data: Add read replicas for query load

Example: Supporting 100 trading pairs with 100,000 orders/second each requires 100 matching shards, but only 10 risk engine instances (monitoring all positions centrally).

Fault Tolerance

Service Redundancy: Each service runs multiple instances across availability zones

Graceful Degradation: If a service fails:

• Matching: Symbol-specific impact only

• Risk: Use cached margin calculations

• API: Route to healthy edge POPs

• Data: Serve from cache

Recovery Time Objective (RTO): < 5 minutes for any service

Monitoring and Observability

Real-Time Metrics:

• Service health (CPU, memory, latency)

• Business metrics (orders/second, fills/second)

• Error rates and types

• Queue depths and processing times

Alerting Thresholds:

• Critical: Service down, latency > 2× target

• Warning: Latency > 1.5× target, error rate > 0.1%

• Info: Capacity > 70%, unusual patterns

Conclusion

use.com's microservices architecture enables independent scaling, fault isolation, and technology optimization while maintaining sub-millisecond matching performance and high availability. This design supports current requirements while providing flexibility for future growth.

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Related Sections:

• Infrastructure & Scalability

• Security Architecture