Logistics IS & WMS

Why logistics needs specialized IS¶

A generic ERP warehouse module isn’t enough when you’re processing thousands of shipments per hour. Logistics operations require real-time processing, hardware integration (scanners, sorters, scales), and fault tolerance. A one-minute outage at a sorting hub means hundreds of unprocessed shipments and a cascade of delays.

Architecture that endures¶

Our logistics IS are built on event-driven architecture with Apache Kafka as the backbone. Every operation — shipment scan, re-sorting, vehicle loading — generates an event. Downstream systems (tracking, billing, reporting, customer notifications) consume events independently.

Why event-driven: - Resilience — Outage of one system doesn’t stop sorting. Events wait in Kafka. - Scalability — Adding new consumer (new reporting, new integration) without changing producer. - Auditability — Complete history of every shipment from events. - Decoupling — Teams work independently on their services.

Typical WMS architecture¶

┌──────────────────────────────────────────────────────────┐
│  DEVICES (Edge)                                           │
│  Scanners, sorting lines, scales, printers              │
│  → Edge processing, offline buffer                       │
└──────────────┬───────────────────────────────────────────┘
               │ MQTT / REST
               ▼
┌──────────────────────────────────────────────────────────┐
│  INGESTION LAYER                                          │
│  API Gateway → Event Validation → Kafka                  │
└──────────────┬───────────────────────────────────────────┘
               │
               ▼
┌──────────────────────────────────────────────────────────┐
│  PROCESSING LAYER                                         │
│  Sorting Engine │ Routing Engine │ Inventory Manager     │
│  Rules Engine   │ Exception Handler │ SLA Monitor        │
└──────────────┬───────────────────────────────────────────┘
               │
               ▼
┌──────────────────────────────────────────────────────────┐
│  INTEGRATION LAYER                                        │
│  ERP Sync │ Customer Notifications │ Partner APIs        │
│  Billing  │ Reporting │ Analytics                        │
└──────────────────────────────────────────────────────────┘

Sorting Engine — heart of the sorting hub¶

The sorting engine decides where a shipment goes — based on destination, weight, dimensions, priority, and SLA. The decision must be made in under 10ms because the shipment physically passes through the sorting line.

How it works: 1. Scanner reads barcode/QR → event to Kafka 2. Sorting engine queries routing rules (Redis cache, < 1ms) 3. Decision → command to sorting line 4. Confirmation → event about successful sorting

Rules change without deployment — operator modifies routing in admin UI, change propagates to cache in seconds. A/B testing of new rules on portion of traffic.

Hardware integration¶

We integrate with everything you’ll find in a logistics depot:

• Scanners — Zebra, Honeywell, Datalogic. REST API or SDK.
• Sorting lines — OPC-UA, Modbus, proprietary protocols.
• Scales — Industrial scales with automatic reading.
• Label printers — ZPL, EPL, PDF direct print.
• AMR robots — REST API for task assignment, fleet coordination.

Real-time tracking¶

Customer sees where their shipment is — in real time, not with hour delay. Event-driven architecture enables this natively: every scan generates event, tracking service consumes it and updates status. WebSocket push for live tracking on web/app.

Scaling for peaks¶

Christmas, Black Friday, e-commerce campaigns — throughput grows 3-5×. Our architecture is ready for this:

• Kafka partitioning — parallel processing, horizontal consumer scaling
• Kubernetes HPA — automatic scale-up based on queue depth
• Load testing — k6 simulates peaks months in advance
• Capacity planning — we know how much we need before we need it

Monitoring and alerting¶

• Business metrics — shipments/hour, sorting error rate, SLA compliance
• Technical metrics — Kafka lag, API latency, error rate
• Hardware monitoring — scanner status, sorters, connectivity
• Alerting — PagerDuty/OpsGenie, escalation rules, runbooks

Dashboards in Grafana — one for management (business KPIs), one for operations (technical metrics), one for support (troubleshooting specific shipment).

Souvisí s