Quant trading bot cluster

Multi-exchange market data and automated strategy execution.

Workflow Automation

Quant trading bot cluster

Challenge

Strategies spanned several exchanges; feed latency and API rate limits caused missed fills, manual monitoring could not cover 24/7, and per-venue capital exposure was hard to control.

Solution

A WebSocket aggregation layer unified the feeds; strategies run as isolated containers with built-in capital allocation, circuit-breaker risk controls and anomaly alerting — fully automated, 24/7.

Process

  1. Market-data layer first

    Built the WebSocket aggregation layer before any strategy work — feeds, rate limits and reconnection logic all handled in one place, so strategies consume clean, uniform data with measurable latency. The root cause of missed fills went first.

  2. Containerised strategies & capital allocation

    Each strategy runs as an isolated container — one crashing cannot take down the rest. A shared capital-allocation layer caps exposure per venue and per strategy, rejecting orders that would breach the limit.

  3. Circuit breakers, alerting & hands-off ops

    Defined circuit-breaker conditions — consecutive losses, abnormal feeds, spiking API errors — that halt trading and alert on trigger. Ran small live positions until stable before scaling up, and only then retired manual monitoring in favour of 24/7 alerting.

Deliverables

  • Market-data aggregation engine
  • Strategy execution framework
  • Circuit-breaker risk controls
  • Monitoring & alerting

Results

  • <50msorder latency
  • 99.98%uptime
  • 7×24unattended operation

Stack

  • Node.js
  • Redis
  • Docker

Timeline

6 weeks + strategy iterations

FAQ

No. We build the market-data, execution and risk infrastructure; your strategies plug in as isolated containers and their logic stays yours to maintain. Anything we do see is covered by confidentiality.

The design principle is fail-safe: on disconnects or anomalies the system stops trading rather than guessing, and a tripped breaker freezes activity and alerts until a human confirms. More important than the uptime figure is that failure behaviour is predictable.

The architecture is market-agnostic — aggregation, strategy containers and circuit breakers do not care what is being traded. A new market just means a new data-feed and execution adapter.

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