Logistics Fleet Optimization System
Executive Summary
- The Challenge: A mid-sized logistics network was losing $50,000 monthly due to inefficient routing and unscheduled vehicle breakdowns.
- The Solution: We launched an event-driven microservices architecture within 8 weeks.
- The Impact: Significant reduction in operational overhead and measurable ROI.
The Challenge
A mid-sized logistics network was losing $50,000 monthly due to inefficient routing and unscheduled vehicle breakdowns. Their existing dispatch software was a monolithic, on-premise system that couldn't handle real-time GPS telemetry from hundreds of trucks. They required a cloud-native SaaS platform capable of processing high-velocity location data and generating dynamic route optimizations.
The Solution Architecture
We launched an event-driven microservices architecture within 8 weeks. We decoupled the heavy telemetry processing from the main application thread using BullMQ and Redis. A React Native driver app was built to push location data via WebSockets to a Node.js backend. We also integrated Google OR-Tools to dynamically calculate optimal delivery routes based on real-time traffic and delivery windows. **System Architecture:** Frontend: Next.js, React Native | Backend: Node.js, Redis, BullMQ | Algorithm: Google OR-Tools | Infrastructure: Kubernetes (AWS EKS), Docker | Database: MongoDB.
The Impact & Key Results
- 40% Reduction in Cloud Compute Costs
- 20% Decrease in Fleet Fuel Consumption
- Zero Downtime during Microservices Migration
- 99.99% Uptime Maintained
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