RAG Pipelines in Production
A production RAG pipeline chains ingestion, chunking, embedding, retrieval, reranking, and generation into one maintained system.
Prerequisites
Overview
Each stage of RAG — ingestion, chunking, embedding, retrieval, reranking, generation — is simple in isolation. A production pipeline is the operational work of running all of them reliably, keeping them in sync as source documents change, and monitoring quality end to end.
Where It Fits
Ingestion
Chunking
Embedding
Retrieval
Reranking
Generation
Key Points
- Pipeline ownership
- Each stage typically has its own failure modes and needs its own monitoring, not just an end-to-end "did the user get an answer" check.
- Sync with source data
- A production pipeline needs a strategy for detecting and re-processing changed or deleted source documents.
- End-to-end evaluation
- Retrieval quality and generation quality need to be measured separately — a good answer built on the wrong context is still a bug.
Interview Question
What’s the difference between a RAG demo and a production RAG pipeline?
A demo runs each stage once, on clean data. A production pipeline runs continuously against changing source documents, needs monitoring at each stage rather than just a final quality check, needs a strategy for re-processing updated content, and needs retrieval and generation quality evaluated separately so failures can be traced to the right stage.
Explain It in 30 Seconds
A production RAG pipeline chains ingestion, chunking, embedding, retrieval, reranking, and generation into one system that stays in sync with changing source data and is monitored at each stage, not just checked end to end.
Real-World Stack
Technologies commonly used to implement this in production.