PPI-F™ Applied: Ride-Hailing System Architecture

Performance Pressure Index framework mapped to a ride-hailing platform

Interactive view with the four PPI-F dimensions — Performance, Production Readiness, Infrastructure Efficiency, Failure Resilience

0
Live requests (sim)
12 ms
Avg latency (sim)
20%
System pressure
200

Pressure propagation along path

Select a workflow above to see how PPI pressure (from maturity 0–5) propagates at each step. Nodes on the diagram are tinted by pressure when the flow runs.

Performance Production Readiness Infrastructure Efficiency Failure Resilience
PPI scoring (aligned with PPI-F Diagnostic): Reference maturity 0–5 per dimension; Pressure = (5 − Maturity) / 5. Click a node to see per-dimension maturity and PPI pressure. Run full PPI-F assessment →

Python — component implementation

Example flows & interaction

Flows: Request trip (Rider → Gateway → Matching → Trip → Pricing). Accept trip (Driver → Gateway → Trip → Pricing). Complete & pay (Trip → Payments → Kafka → DB). Real-time location (Driver → Gateway → Location Stream → ETA/Kafka). Surge pricing (Pricing → Trip/Matching). Driver onboarding (Driver App → Auth → DB). Rider payment (Rider App → Payments → DB). Interact: Use the traffic slider to simulate load (live request counter and system pressure update). Switch to Level 2 to see containers (API Layer, Core, Billing, Real-time, Data). Click any component to see its PPI-F dimensions and pressure. High traffic adds a pulse animation to nodes.

Performance

Latency, throughput, scalability. Pressure sources and invariants.

  • API Gateway, Matching, ETA/Maps, Trip Service

Production Readiness

Deployment, observability, propagation and levers.

  • API Gateway, CI/CD, Observability, Trip Service

Infrastructure Efficiency

Cost, utilization, right-sizing, cost-to-serve.

  • Kafka, Database, Pricing, Payments

Failure Resilience

HA, DR, failure modes, recovery friction.

  • Payments, Database, Trip Service, API Gateway