FX Order Flow Diagnostics Lab

Java and Spring Boot service that reconstructs FX order timelines from component events and surfaces duplicates, invalid transitions, stuck orders, and downstream rejections.

Why this project exists

The goal is to show a realistic graduate-level engineering problem in FX technology: understanding how an order moved through multiple components and why it failed or stalled. The repo focuses on diagnostics and root-cause thinking, not on pretending to be a full execution platform.

What it demonstrates

• Java 17 and Spring Boot service design
• event-driven diagnostics for trading flows
• lifecycle validation
• incident classification
• summary and timeline APIs
• automated tests and CI

API

• GET /actuator/health
• GET /api/v1/health
• POST /api/v1/events
• POST /api/v1/demo/load-sample
• POST /api/v1/incidents/analyze
• GET /api/v1/orders
• GET /api/v1/orders/{clientOrderId}/timeline
• GET /api/v1/incidents
• GET /api/v1/summary

Example event request:

{
  "clientOrderId": "FX-9001",
  "currencyPair": "EURUSD",
  "component": "gateway",
  "eventType": "RECEIVED",
  "eventTime": "2026-04-25T10:00:00Z",
  "detail": "client order accepted"
}

Sample summary: docs/sample_summary.json

Quick start

./gradlew bootRun

Run tests:

./gradlew test

More detail:

• docs/architecture.md
• docs/fx-order-notes.md
• docs/roadmap.md

Resume-safe wording

• Built a Java and Spring Boot diagnostics service that reconstructs FX order timelines from component events and highlights duplicate orders, invalid transitions, stuck orders, and downstream rejections.
• Implemented incident analysis APIs, per-order timeline inspection, automated tests, and sample event flows to model root-cause investigation in a distributed trading stack.