Boris Tane's argument that traditional logging is broken for distributed systems and that "wide events" — one comprehensive, high-cardinality structured event per request per service — are the fix. Log what happened to the request, not what your code is doing.
Logging was designed for monoliths. Once a single request fans out across 15+ services, conventional logs turn into noise — 17 lines for one successful request, 130,000+ lines per second at scale — because they optimize for writing, not querying. OpenTelemetry doesn't fix this; it's a delivery mechanism, not a mental model.
Instead of logging what your code is doing, log what happened to this request.
The proposed fix is wide events (canonical log lines): emit one comprehensive, high-cardinality event per request per service, carrying everything you'd want at query time:
Tail sampling keeps cost sane by retaining events by priority: 100% of errors, 100% of slow requests (p99+), all VIP/enterprise users, and a 1–5% random sample of healthy requests.
The payoff: debugging shifts from archaeological text-searching to analytics-style queries over structured business events.
Boris is building nominal.dev, an observability platform based on this idea.
My usual move: send this article to an LLM agent and have it build me an Effect layer for logging and observability from it — since most of my code is Effect anyway. I specify the sampling strategy up front: on small projects I sample at 100% (no sampling — I want all the data), and as the project grows I start dialing in tail sampling along the lines Boris describes.