August 13, 2025 by Mishael Ochu

Building a Technical Analysis Hub for Enterprise Logistics

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Centralizing Knowledge for a Complex Multi-Tenant System

Working with a large-scale logistics platform spanning 537 database tables, 20+ repositories, and deployments across 14+ countries requires systematic knowledge management. I built a technical analysis hub that serves as the central reference for architecture decisions, code reviews, and implementation planning.

The Scale of the Challenge

My client’s platform includes:

  • Legacy Core - Multi-tenant enterprise shipping system (PHP/MySQL)
  • Modern API - Next-generation frontend (Java Spring Boot 3)
  • Legacy System - Specialized freight management (AU, US, UK variants)
  • Third-party Integrations - 10+ carrier APIs (DHL, FedEx, UPS, Canada Post, etc.)

Understanding how these systems interconnect and maintaining consistency across teams requires more than tribal knowledge.

What the Analysis Hub Contains

Code Review Documentation

  • Detailed analysis of 130+ pull requests
  • Test results and critical issue identification
  • Coding standards extracted from team conventions

Architecture Documentation

  • Complete database schema mapping (537 tables)
  • Business function inventory (20+ domains, 150+ controller mappings)
  • Three-tier architecture documentation (Vendor → Core → Regional)

Implementation Guides

  • Feature planning documents (warranty services, freight management, quote APIs)
  • Step-by-step implementation approaches
  • Integration patterns for carrier APIs

Operational Guides

  • Developer onboarding materials
  • Deployment procedures
  • Authentication and testing workflows

Database Schema Understanding

With 537 tables using composite keys and code-based primary keys, understanding the data model is critical:

-- Example: Multi-tenant data isolation
SELECT * FROM shipments
WHERE franchise_code = '100'
  AND customer_code = '10001';

-- Code-based keys enable efficient franchisee filtering

The analysis hub documents these patterns, naming conventions, and relationships that aren’t obvious from the schema alone.

Consistent Code Review Standards

Extracted from PR #124 and subsequent reviews, the hub maintains coding standards:

  • Service layer patterns with DTOs and Value Objects
  • MapStruct usage for object mapping
  • Soft delete patterns and archive table conventions
  • Multi-currency and multi-country considerations

These standards ensure consistency whether reviewing legacy PHP code or new Spring Boot services.

Sprint-Based Tracking

With 82+ sprints tracked for the legacy system alone, the hub provides historical context for decisions and implementations. This institutional memory prevents re-solving problems and helps new team members understand why things are built the way they are.

The Value of Systematic Documentation

When a bug appears in the AU freight system, having documented the dispatch flow, carrier integration patterns, and database schema means debugging starts from understanding rather than exploration. When planning a new feature, previous implementation guides provide templates and warn of pitfalls.

In complex enterprise systems, documentation isn’t overhead - it’s the foundation that makes sustainable velocity possible.

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