Business Context & Release Paralysis
A high-volume B2B logistics platform orchestrating thousands of daily supply chain operations faced soaring maintenance costs on an 8-year-old monolith exceeding 450,000 lines of code.
As billing logic and courier integrations grew increasingly complex, the legacy system started strangling business velocity:
- 30+ Day Release Cycles: Because of tightly coupled dependencies (a classic Big Ball of Mud), the engineering team feared making production deployments.
- Uncontrolled Regressions: A minor adjustment in freight tariff calculations would break VAT invoice generation in the accounting module.
- Exhausting Manual QA Cycles: Prior to every release, engineers and QA spent 3 to 5 full days running manual regression checklists.
The Board faced an executive crossroads: greenlight an 18-month "Big Bang Rewrite" with enormous budgetary risk, or find a safe, battle-tested engineering alternative.
Transitional Architecture: The Strangler Fig Pattern
We immediately dismissed the idea of rewriting everything from scratch. Instead, we implemented the Strangler Fig Pattern in tandem with Traefik Reverse Proxy and Vertical Slice Architecture.
[B2B Clients / API Consumers]
│
▼
[Traefik Reverse Proxy (Dynamic Routing)]
│ │
│ (90% legacy traffic) │ (Carved out domain slices)
▼ ▼
[8-Year Monolith] [New Vertical Slices (DDD)]
(Legacy Database) - Invoicing Module
- Dispatching Module
(Dedicated PostgreSQL DB)
▲
│ (Event Sync / RabbitMQ)
▼
[CDC / Debezium Outbox]
Core Architectural Directives:
- Zero Downtime: Operational shipment processing and corporate revenue generation were never interrupted for even a single minute.
- Incremental Domain Extraction: We applied Domain-Driven Design (DDD) and Event Storming to establish airtight Bounded Contexts.
- Transactional Outbox & Change Data Capture (CDC): Data synchronization between the legacy database and new microservices was decoupled via the Outbox Pattern and RabbitMQ, guaranteeing eventual consistency without shared database anti-patterns.
Step-by-Step Technical Execution
Phase 1: Edge Routing Layer (Traefik)
We placed Traefik at the network edge as an intelligent reverse proxy. Initially, 100% of inbound traffic was forwarded to the legacy monolith. As new domain slices matured, declarative routing rules redirected specific endpoints without requiring third-party API clients to change their integrations.
Phase 2: Extracting Invoicing to a Vertical Slice
The invoicing domain was chosen as the first candidate. Instead of traditional horizontal technical layers (Controllers -> Services -> Repositories), we adopted Vertical Slice Architecture: all business logic, validation, and data mutations for a specific command (e.g., GenerateInvoiceCommand) reside within a self-contained autonomous directory.
Phase 3: GitOps CI/CD Automation & OpenAPI Contracts
We enforced strict Consumer-Driven Contract Testing backed by OpenAPI schemas. Automated CI/CD pipeline execution in containerized Docker testbeds finished in under 4 minutes.
Measurable Business & Engineering Outcomes
- Deployment Frequency: Surged from 1 release per month to 14 production deployments per week (+56x).
- Regression Detection Speed: Dropped from 3–5 days of manual QA down to 4 minutes in automated CI/CD (instant developer feedback loop).
- System Availability During Migration: 100.00% uptime (0.00 seconds of downtime) for logistics partners.
- Engineering Morale: Deploying on Friday is no longer dreaded; releases became a predictable, automated background non-event.
Key Takeaway for Technology Leaders
Rewriting an entire system from scratch is the leading cause of enterprise IT budget catastrophes. The Strangler Fig pattern proves that even the most convoluted monolith can be decoupled safely, unlocking tangible business ROI in weeks rather than years.