CDC

In Part 1: The Paradigm Shift - Agentic Architecture & Golang Orchestration Power, we established the Orchestration Engine using Golang and Eino. However, no matter how smart a brain is, it becomes useless if fed with misleading, unstructured, or fragmented information. In the e-commerce domain, product catalog data changes continuously every second: prices fluctuate, inventory is updated, new products are added. Meanwhile, chunking product data to feed into a Vector Database (Qdrant) is entirely different from chunking a PDF document or a news article. ...

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. ...

1. “Yesterday’s Data” is a Disaster If a customer asks a banking Chatbot about savings interest rates, and the Chatbot answers based on a PDF policy file that was changed… 2 hours ago. What happens? In Enterprise environments like Finance, Healthcare, or E-commerce, Yesterday’s data is a legal liability. Legacy data pipelines (ETL Batch Jobs running at midnight) no longer meet the demands of 2026. If the Core Database changes, your Vector Database must be updated immediately. Data Freshness must be measured in seconds. ...