Comment by killme2008

This thread overlaps a lot with "Observability 2.0 and the Database for It" (https://news.ycombinator.com/item?id=43789625). The core claim there is: treat logs/spans as structured "wide events", and build a storage/query layer that can handle high-cardinality events so many metrics become derived views rather than pre-modeled upfront. It also argues the hard part isn't "dump it in S3", it’s indexing/queryability + cost control at scale.

In an agentic AI world this pressure gets worse: telemetry becomes more JSON-ish, more high-cardinality (tool names, model/version, prompt/template IDs, step graphs), and more bursty, so pre-modeling every metric up front breaks down faster.