Chapter 1 — Designing AI Systems: RAG & Vector Databases
Purpose
[stub: designing-ai-systems-rag-vector-db]
Metadata
| Author | Amit Singh |
| Scope | system-design |
Local graph
Related notes
Chapter 2 — AI Infrastructure
GPU scheduling, inference serving, and model-serving architecture as the infrastructure layer underneath every AI product design.
Chapter 3 — AI Observability
Extending metrics, logs, and traces to LLM-specific signals — token cost, latency per generation step, and quality/hallucination drift.
Chapter 4 — Alerting Systems
Multi-window burn-rate alerts, recording rules, routing, and deduplication as the difference between an actionable page and noise.
Chapter 3 — Monitoring at Scale
Prometheus, Mimir, Cortex, and Thanos as the horizontally-scaled answer to a single Prometheus instance running out of room.