Backend Architecture

Series Hub | Next Chapter: Part 1: Decomposing Magento into 21 Services with DDD → Answer-first: Migrating from a monolithic Magento deployment to a Composable Commerce platform with 21 Go microservices eliminates the $200k/year license fee entirely, boosts flash-sale capacity by 10x, and removes the risk of single-vendor lock-in. Answer-first: Start with a Modular Monolith mindset, then progressively shift to Composable Commerce built on 21 Go microservices, Kratos v2, and Dapr PubSub. This is the definitive answer to replacing Magento Enterprise. It delivers extreme commerce capability (multi-warehouse, payment sagas, real-time search) at a license cost of $0, while also meeting the API-first requirements of Agentic Commerce in the 2026 AI ecosystem. ...

← Previous Chapter: Part 0: Avoiding the $200K/Year Magento Trap | Series Hub | Next Chapter: Part 2: Rush Monorepo for 21 Go & Next.js Apps → Answer-first: The number of microservices you need is decided by your team structure, your scaling profile, and the boundaries of your business invariants; applying DDD carves 240 Magento modules into 21 independent bounded contexts (such as separating Checkout from Order, and Pricing from Promotion). Answer-first: The number of services you need is determined by your team structure, your scaling profile, and the boundaries of your business invariants — not by cookie-cutter formulas. In the 2026 e-commerce environment, with the shift toward Agentic Commerce and Composable APIs, establishing clear boundaries becomes even more critical. The platform in this series uses 21 services to serve 10,000+ orders per day. ...

← Previous Chapter: Part 1: Decomposing Magento into 21 Services with DDD | Series Hub | Next Chapter: Part 3: Go + Kratos v2 Framework Deep Dive → Answer-first: Governing a polyglot monorepo (21 Go microservices and 2 Next.js frontends) with Microsoft Rush delivers strict dependency control, incremental builds, and automatic generation of TypeScript SDKs from proto files — all without version conflicts. When you own 21 Go microservices and 2 frontend applications, the first infrastructure question is not Kubernetes or CI/CD — it is how do you manage the source code itself? ...

← Previous Chapter: Part 2: Rush Monorepo for 21 Go & Next.js Apps | Series Hub | Next Chapter: Part 4: gRPC Internal + REST Gateway → Answer-first: The enterprise-grade Go microservice architecture on this platform is built on Kratos v2 with a strict 5-layer model, Google Wire dependency injection, parallel HTTP/REST and gRPC transports, and a shared library that standardizes logging and middleware. For engineers coming over from Magento PHP, the shift to Go microservices is not just a change of programming language — it is a fundamentally different way of organizing code. Magento has controllers, models, blocks, helpers, and plugins. Go with Kratos v3 (fully optimized for Go 1.25) has exactly 5 layers, each with a crisply defined responsibility. ...

← Previous Chapter: Part 3: Go + Kratos v2 Framework Deep Dive | Series Hub | Next Chapter: Part 5: Migrating the Magento EAV Schema → Answer-first: Every API in the Composable Commerce system starts from a Protocol Buffers (.proto) contract, using gRPC for high-speed internal communication between services and gRPC-Gateway to automatically expose JSON REST endpoints for Web and Mobile applications. Every public-facing API in the Composable Commerce platform starts from a .proto file. The code — including the gRPC handler functions written in Go, the TypeScript SDK, the HTTP routes, request validation, and the error codes — is all automatically generated from that contract. This article documents the conventions behind the scenes that keep the whole system running smoothly. ...

Answer-first: Production-grade geospatial routing architectures require decoupling graph-traversal engines (OSRM, GraphHopper) from spatial partitioning indexes (Uber H3, Google S2) via high-concurrency Go 1.25 API gateways. This 9-part masterclass details the complete engineering blueprint for building an in-memory routing cluster with sub-5ms point-to-point queries, 50,000 QPS distance matrices, Redis semantic caching, and zero-downtime map rollouts on Kubernetes, reducing cloud map spend by 99.7%. 1. Production Reality: The Economics and Latency Wall of Commercial Mapping APIs In on-demand delivery platforms, ride-hailing networks (Grab, Uber, GoTo), and rapid-fulfillment e-commerce fleets (ShopeeXpress, Amazon Logistics), software survival hinges on solving one continuous question: “What is the exact travel duration, road distance, and route geometry between thousands of moving vehicles and pending pickup orders?” ...