How do you handle content updates and stale embeddings in production RAG?
mediumAnswer
- (1) Track document versions; re-embed changed docs and upsert.
- (2) Delete stale vectors — tombstone or hard delete.
- (3) Backfill jobs when embedding model changes (full re-embed of the corpus, staged rollout).
- (4) Version namespaces: keep old + new embeddings in parallel, canary rollout with a small % of traffic on the new model.
- (5) Idempotent IDs (stable across re-embeddings) simplify updates.
- Avoid full-corpus re-embeds for minor changes.
Check yourself — multiple choice
- Never update
- Version + upsert changed docs, delete stale, backfill on model changes with canary, stable idempotent IDs
- Random reindex
- Only append
RAG updates: version + upsert + tombstone + canary backfills on model changes.
#vector-db#production
Practise LLMs & GenAI
214 interview questions in this topic.