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99.99%

Platform Uptime

Case study · Financial Services

Real-Time Trading Platform with Sub-100ms Latency

A full-stack trading platform with real-time market data, WebSocket-driven UI, and microservices backend handling 10K+ concurrent users.

Node.jsNode.jsReactReactTypeScriptTypeScriptAWSAWSWebSocketRedisRedisPostgreSQLPostgreSQLDockerDocker

Project details

Client
Fintech startup (Series B)
Industry
Financial Services
Timeline
18 weeks
Architecture
Microservices on AWS

The challenge

What we walked into.

The client was building a low-latency trading platform. Real-time market data, no perceptible lag. Their prototype polled every 2 seconds. For active traders that meant stale prices, missed entries, and a UI that felt slow next to the institutional terminals they had used at past desks.

The platform needed to handle 10,000+ concurrent users during market hours, with each user receiving personalized data streams based on their watchlists and open positions. Any downtime during trading hours was unacceptable — regulatory requirements demanded 99.99% availability with full audit trails for every transaction.

They needed a team that understood both the real-time engineering challenges and the compliance requirements of financial services.

What we built

The engineering decisions.

WebSocket Data Pipeline

We replaced the polling architecture with a persistent WebSocket layer. Market data flows from exchange feeds through a Node.js ingestion service, gets normalized and enriched in Redis Streams, and is pushed to connected clients in under 50ms. Each user's connection receives only the data relevant to their watchlist — no wasted bandwidth.

Microservices Backend

The backend was decomposed into focused services: order management, portfolio tracking, market data ingestion, user auth, and audit logging. Each service runs in Docker containers on ECS with auto-scaling policies tuned to market hours. Inter-service communication uses a combination of synchronous gRPC for latency-sensitive paths and async SQS for eventual-consistency workflows.

React Trading Dashboard

The frontend is a React application optimized for real-time rendering. Virtualized lists handle thousands of tickers without DOM thrashing. Canvas-based charting renders price history at 60fps. State management uses a custom event-driven architecture that batches WebSocket updates to avoid unnecessary re-renders.

Compliance & Audit Infrastructure

Every order, modification, and cancellation is logged to an immutable audit trail in PostgreSQL with append-only tables. User sessions are recorded with full activity logs. The entire infrastructure runs in AWS with SOC 2-aligned controls — encryption at rest and in transit, least-privilege IAM, and audit-grade logging — handed off audit-ready to the client's compliance partner.

The results

Measured outcomes.

99.99%

Uptime since launch

<100ms

Data delivery latency

10K+

Concurrent users supported

  • 99.99% uptime maintained across 6 months of live trading — zero outages during market hours
  • Data latency reduced from 2s (polling) to sub-100ms (WebSocket) — a 20x improvement
  • Platform handles 10K+ concurrent WebSocket connections with headroom to 50K
  • SOC 2-aligned controls implemented end-to-end — audit-ready posture handed off to client's compliance team
  • Trading volume grew 3x in 4 months post-launch, with infrastructure costs scaling linearly

The engineering behind this

Web & Mobile AppsThe application surface engineered.Cloud & InfrastructureThe infra under a real-time platform.AI & Deep LearningThe intelligence layer behind it.

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