Enterprise Order Management Platform

The engagement centered on decomposing a 15-year-old .NET Framework monolith that handled order intake, pricing, and fulfillment for a multi-brand retail portfolio. Business growth had outpaced the system's capacity to evolve independently per brand, and release cycles stretched to six weeks due to tightly coupled modules. I defined a target architecture organized around order, inventory, pricing, and fulfillment bounded contexts with clear aggregate boundaries and asynchronous integration. The rollout followed a strangler-fig pattern over 18 months, preserving transactional integrity while enabling each domain team to deploy on independent cadences.

Order processing latency during peak retail events exceeded SLA thresholds by 3x, and a single deployment failure could halt fulfillment across all brands. Legacy stored procedures embedded business rules that were duplicated across regions, creating reconciliation drift between ERP instances. Leadership required a platform that could absorb acquisitions without re-platforming and provide auditable order state across the full lifecycle. Cost of downtime was estimated at $400K per hour during holiday windows.

We implemented a modular .NET 8 platform with CQRS command handlers for write paths and read-optimized projections backed by PostgreSQL and Redis. Cross-context communication uses outbox-pattern events published to Kafka, with idempotent consumers and dead-letter handling for poison messages. A centralized API gateway enforces OAuth 2.0, rate limiting, and schema-validated contracts generated from OpenAPI specs. Blue-green deployments on AKS with feature flags allowed progressive traffic shifting per brand without shared release trains.

The system follows a hexagonal architecture within each bounded context, with domain logic isolated from infrastructure adapters for messaging, persistence, and external ERP connectors. An event backbone on Kafka provides at-least-once delivery with partition keys scoped to order aggregate IDs for ordering guarantees. Read models are rebuilt from event streams using dedicated projection workers, decoupling query performance from write contention. Infrastructure is provisioned via Terraform modules per environment, with Azure Front Door handling geo-routing and WAF policies at the edge.