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📊 Engineering & System Performance Metrics

Scalable Event-Driven Ride-Sharing Platform

This document defines the quantifiable engineering KPIs used to evaluate system health, scalability, and ML/dispatch performance.

🚀 1. System Throughput Metrics

Metric Description Target
Driver Location Events / sec Number of GPS updates processed by the event bus 5,000+
Ride Requests / sec Number of concurrent rider requests 1,000+
Dispatch Allocation Latency Time from ride request → driver assignment < 50 ms
Event Bus Latency Kafka-style event propagation < 10 ms

🧠 2. Machine Learning / Matching Metrics

Metric Description Target
Matching Accuracy Driver chosen is truly the nearest available 95%+
ETA Prediction Error Avg difference between predicted vs actual < 10%
Surge Detection Speed Time to detect abnormal demand spikes < 2 seconds

🗺 3. Geospatial Data Metrics

Metric Description Target
Driver Location Freshness Age of last GPS ping < 2 seconds
H3 Cell Mapping Latency Time to compute hex cell → service region < 1 ms
Nearby Driver Lookup Query driver store for availability < 5 ms

🧩 4. Microservice Reliability Metrics

Metric Description Target
Service Uptime Availability of all services 99.9%
Error Rate Failed requests < 0.01%
Circuit Breaker Trips Fault tolerance activations < 5 per day
Backpressure Handling Queue build-up under traffic spikes Auto-scale within 3 seconds

🧱 5. Infrastructure & DevOps Metrics

Metric Description Target
Container Launch Time Docker/K8s spin-up < 2 seconds
Auto-scaling Reaction Ability to scale microservices < 8 seconds
CI/CD Pipeline Time Build → test → deploy < 90 seconds
API Cold Start First request after idle < 40 ms

🔐 6. Security Metrics

Metric Description Target
Failed Auth Attempts Unexpected login attempts < 0.1%
Token Validation Time JWT verification < 2 ms
PII Encryption Overhead Performance penalty < 5%

📞 7. User Experience Metrics

Metric Description Target
Rider Request Response Time to view ETA after request < 80 ms
Cancellation Rate Canceled rides < 5%
Driver Acceptance Rate Drivers accepting assigned rides > 90%

🏁 Summary

This project demonstrates Big-Tech-grade metrics, covering:

  • Dispatch performance
  • Real-time geospatial processing
  • Event-driven microservices
  • Scalability & fault tolerance
  • User experience KPIs

These metrics elevate the repo to L5/L6 system-design readiness.