Custom-Trained RAG with Event Pipeline and Edge Serving

Scenario

A platform team uses EventBridge + DataWorks for continuous data ingestion feeding PAI-trained custom embedding and reranking models (Combo 4's domain-specific training), then deploys the hybrid BM25+vector retrieval pipeline via Terraform with Cloudflare edge inference (Combo 2's edge serving) for a globally-distributed production RAG system that auto-retrains on new ingested data.

How the products combine

1. airec · end-to-end-trained-rag-platform-with-event-drive-3fc547 — End-to-End Trained RAG Platform with Event-Driven Serving

See _combos/end-to-end-trained-rag-platform-with-event-drive-3fc547.

2. airec · event-driven-rag-platform-with-edge-serving-173e4f — Event-Driven RAG Platform with Edge Serving

See _combos/event-driven-rag-platform-with-edge-serving-173e4f.

3. airec · event-pipeline-to-production-rag-platform-d21287 — Event Pipeline to Production RAG Platform

See _combos/event-pipeline-to-production-rag-platform-d21287.

4. alinux · full-stack-custom-rag-train-to-production-e68446 — Full-Stack Custom RAG: Train to Production

See _combos/full-stack-custom-rag-train-to-production-e68446.

Typical questions

• custom embeddings with event-driven retraining and edge serving
• train domain models deploy globally via CDN and event pipeline
• EventBridge ingestion auto-retrain embeddings serve via Cloudflare
• hybrid BM25 vector search with custom PAI models at edge
• Terraform deploy custom RAG with auto-retraining and global CDN
• 从事件数据训练自定义模型并通过边缘节点全球服务
• EventBridge数据管道自动训练嵌入模型后CDN加速推理
• DataWorks加工数据训练混合检索模型边缘部署

Q: How does the platform deploy and maintain a custom-trained RAG system with event-driven retraining and global edge serving? A: The architecture uses Terraform to deploy a globally distributed hybrid BM25 and vector retrieval pipeline that runs inference on Cloudflare's edge network. Continuous data ingestion via EventBridge and DataWorks automatically retrains PAI-based custom embedding and reranking models on new data.