Debezium

Phase 1 is the safest phase of the migration — by design. No write operation touches the new microservices. Magento remains the source of truth for all data modifications. The only thing Phase 1 does is prove that your microservices can serve reads faster and more reliably than Magento. Answer-first: Phase 1 deploys Go microservices in read-only mode, routes GET requests to them via the API Gateway’s per-domain feature flags (with automatic fallback to Magento if the service is unhealthy), and uses Debezium — running in embedded engine mode without a standalone Kafka cluster — to stream Magento MySQL changes to the microservices via Dapr PubSub on Redis Streams. Writes continue to go to Magento. Data latency target: < 2 seconds. ...

Answer-first: Monolith decoupling succeeds only when solving eventual consistency and distributed tracing overhead early. Mitigate inventory overselling via Redis-based BFF locking, stream database sync in real-time via Debezium CDC and Kafka, and build distributed tracing via OpenTelemetry from day one to avoid system blindness. What You’ll Learn That AI Won’t Tell You Strangler Fig routing configurations for Envoy that migrate traffic path-by-path from Magento to Go microservices without dropping active sessions. How to implement a double-write database sync listener in Go to prevent data drift during the multi-month migration window. In theory, MACH (Microservices, API-first, Cloud-native, Headless) and Composable Commerce are the “holy grail” of the ecommerce industry. However, when systems scale to process millions of transactions, issues regarding data consistency and Observability costs truly surface. This article outlines the hard-learned lessons from our Chief Architects when migrating a monolithic system to a Composable architecture. ...

Prerequisite: Part 8 of the System Design Masterclass. Read Part 7: Idempotent API Design first — compensating transactions in Saga must be idempotent. 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. What Are the Problems with 2PC in Microservices? Answer-first: 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. ...

Answer-first: Attempting to simultaneously write inventory updates to a fast cache (Redis) and a relational database (PostgreSQL) creates the dual-write problem. If one system fails, data diverges. Furthermore, synchronous SELECT FOR UPDATE queries in SQL cause massive lock queues and API timeouts. What You’ll Learn That AI Won’t Tell You Write-through caches configuration in Redis to prevent inventory drift. Lua scripting implementations in Redis that prevent double-reservations under peak load. What Is Real-Time Inventory Synchronization? Real-time inventory synchronization is the process of propagating stock count changes from the system of record (database) to all sales channels — web storefront, mobile app, WMS, ERP — in sub-second time. Instead of batch ETL jobs that run every hour, a CDC + Kafka pipeline streams every committed stock change as an event, eliminating overselling and stale stock displays. ...

Answer-first: Migrate a complex Magento monolith to microservices without downtime by utilizing a 3-Phase Strangler Fig pattern. Stream legacy updates to Go microservices in real time using Debezium CDC, manage bidirectional synchronizations using Dapr Pub/Sub to maintain eventual consistency, and keep Magento as a 30-day hot standby for instant rollback capability. What You’ll Learn That AI Won’t Tell You Decoupling cart and checkout tables from Magento core databases. Data synchronization pipelines that prevent order loss during checkout transitions. “Let’s rewrite everything to Microservices.” ...