Outbox Pattern

When a customer places an order on the Composable Commerce Platform, seven events need to happen in sequence across four independent services: Order created → Payment authorized → Stock reserved → Fulfillment triggered → Notification sent → Loyalty points awarded → Shipping label generated. Any of these can fail. The network can fail. The database can fail. A third-party payment gateway can time out. Without a reliability mechanism, a 2% failure rate on any step means 2% of all orders are stuck in an inconsistent state, requiring manual intervention. ...

Answer-first: Three database strategies exist for Magento→Golang migration: (A) Shared DB — immediate compute win, dangerous as a final state; (B) CDC + Debezium — gradual DB separation without changing PHP code; (C) Full Event Bus — complete autonomy but requires Magento to publish every state change as an event. Option B is the recommended path for most teams. What You’ll Learn That AI Won’t Tell You Why Go running against Magento’s MySQL is faster at the compute layer but still bottlenecked at the EAV query layer — and what actually fixes it. The single deciding factor between CDC (Option B) and Event Bus (Option C): who owns the PHP Magento codebase. This post is part of the Composable Commerce Migration series — a step-by-step playbook for migrating Magento 2 to Go microservices. For the full migration execution guide, see Part 6: Phase 1 Strangler Fig. ...

Answer-first: The Saga Pattern coordinates distributed transactions across microservices by decomposing a large transaction into a sequence of local transactions. If any step fails, the system automatically executes compensating transactions in reverse order to undo completed steps. Each local transaction must be idempotent. Prerequisite: Part 8 of the System Design Masterclass. Read Part 7: Idempotent API Design first — compensating transactions in Saga must be idempotent. What You’ll Learn That AI Won’t Tell You Temporal Workflow Determinism: How Temporal’s event sourcing workflow engine replays Go code, and why random functions or time sleeps crash workers. Debezium EventRouter Tuning: The exact JSON configuration keys needed to customize Kafka routing keys and prevent partition ordering issues. Pivot State Analysis: Identifying the “point of no return” in a distributed saga where compensations are no longer allowed. What Are the Problems with 2PC in Microservices? Key Concept: Two-Phase Commit (2PC) is a blocking protocol with a coordinator single point of failure. If the coordinator crashes between the Prepare and Commit phases, all participants are blocked indefinitely with locks held — a catastrophic failure mode in microservices. These are the same core banking distributed transaction challenges seen in legacy systems. ...

Prerequisite: Before reading this chapter, please ensure you have read the previous article in this series: Chapter 3: Distributed Rate Limiting with Redis & GCRA Algorithm. When your Golang application migrates from a Monolith to event-driven Microservices, you will immediately face an architectural nightmare: the Dual-Write Problem. 1. What is the Dual-Write Problem? Dual-Write occurs when an app attempts to write to a Database and publish to a Message Broker (Kafka) simultaneously. Without a distributed transaction, network failures will cause the two systems to fall out of sync. ...