Day 5 — Production RAG Systems

Everything so far has assumed a clean development environment: small document sets, no concurrent users, and you watching the logs. Production changes everything. Thousands of documents need indexing without blocking your API. Documents change and the index must reflect those changes without a full rebuild. Caching saves money but introduces staleness. Monitoring tells you when retrieval quality degrades before your users do. And the costs that were negligible in dev become real line items you need to optimize.

Lessons

1. Indexing at Scale — batch embedding, background workers, incremental indexing, and rate limit handling
2. Handling Updates — upserting changed documents, soft deletion, version tracking, and cache invalidation
3. Caching — embedding cache, result cache, TTL strategies, and Redis integration
4. Monitoring & Observability — structured logging, latency tracking, quality metrics, and alerting
5. Cost Optimization — embedding dimension tradeoffs, model selection, caching ROI, and token budgets

Next: Capstone: Company Docs Q&A