Backend Architecture

Series Hub | Next Chapter: Part 1: DDD & Bounded Contexts Decomposing Magento into 21 Services → Answer-first: Migrating from a monolithic Magento deployment to a Composable Commerce platform with 21 Go microservices eliminates $200k/year in licensing fees, boosts flash-sale concurrency capacity by 10x, and mitigates single-vendor lock-in. Starting with a Modular Monolith mindset and incrementally transitioning to Composable Commerce via 21 Go microservices, Kratos v2, and Dapr PubSub represents the definitive solution for replacing Adobe Commerce / Magento Enterprise. It delivers enterprise-grade retail capabilities (multi-warehouse routing, saga checkouts, real-time search) with $0 licensing overhead, fulfilling API-first requirements for Agentic Commerce in the 2026 AI ecosystem. ...

← Previous Chapter: Part 0: Executive Summary | Series Hub | Next Chapter: Part 2: Rush Monorepo Architecture → Answer-first: Decomposing Magento requires Domain-Driven Design (DDD) bounded contexts across 5 core domains: Catalog & Search, Order & Fulfillment, Customer & Identity, Marketing & Promotion, and Financial Accounting. Each microservice owns its private PostgreSQL database to eliminate coupling. Monolithic Magento tightly couples product catalogs, tax rules, user sessions, inventory locks, and payment processing within a single shared database. A schema change to customer addresses can inadvertently lock product catalog tables. ...

← Previous Chapter: Part 1: DDD & Bounded Contexts | Series Hub | Next Chapter: Part 3: Go + Kratos v2 Framework Deep Dive → Answer-first: Using Microsoft Rush with PNPM workspaces enables polyglot monorepo management across 21 Go microservices and 2 Next.js frontends. It automates Protobuf code generation via Buf, enforces dependency boundaries, and slashes CI build times by 70% with incremental build caching. Managing 21 independent Git repositories creates severe operational friction: version mismatch across shared Protobuf contracts, fragmented CI pipelines, and delayed end-to-end integration testing. ...

← Previous Chapter: Part 2: Rush Monorepo | Series Hub | Next Chapter: Part 4: gRPC Internal + REST Gateway → Answer-first: Go-Kratos v2 provides a battle-tested microservice foundation combining Clean Architecture layers (Server, Service, Biz, Data), Google Wire compile-time dependency injection, and dual gRPC/HTTP protocol handlers. When building 21 microservices, consistency across codebases is paramount. If each service adopts a different folder structure, error handling paradigm, or logging format, developer onboarding becomes a nightmare. ...

← Previous Chapter: Part 3: Go + Kratos v2 Framework Deep Dive | Series Hub | Next Chapter: Part 5: Migrating Magento EAV Schema to PostgreSQL → Answer-first: Every API in our Composable Commerce system starts with a Protocol Buffers (.proto) contract. Internal microservices communicate over binary gRPC for 7x faster serialization, while gRPC-Gateway automatically exposes standard REST/JSON endpoints with OpenAPI 3.1 specs for web and mobile clients. In modern 2026 cloud architectures, internal services communicate over gRPC (type-safe, binary format, ~7x faster than JSON over HTTP/1.1). External clients (web browsers, mobile apps) communicate over standard REST via a Gateway Service (using grpc-gateway or Connect by Buf running at the edge). ...

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?” ...