forecasting

AI runs on time-stamped data; this hands-on guide shows why time-series databases beat CSVs/OLTP for ML features and monitoring, and walks you through Linux/Bash setup of TimescaleDB and ClickHouse, ingesting telemetry, building 1‑minute aggregates, setting retention/TTL, and exporting ML-ready features, with queries for p95 latency/error-rate monitoring and a practical LLM service example, plus next-step automation tips.