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This is a web feed, also known as an Atom feed. Subscribe by copying the URL from the address bar into your newsreader. Visit About Feeds to learn more and get started. It's free.Visit websiteRecent postsUpdated on $DATEdateObservabilityThink and Act as One - ObservabilityCEO & Founder of Greptime. Writing about systems, distributed computing, AI & Programming.Zola2026-07-09T00:00:00+00:00https://blog.fnil.net/tags/observability/atom.xmlWhen Agents Go to Production: What Actually Breaks2026-07-09T00:00:00+00:002026-07-09T00:00:00+00:00Dennis Zhuanghttps://blog.fnil.net/when-agents-go-to-production/When agents go to production, they break the four assumptions today's infrastructure was built on: deterministic, human-driven, request-response, stateless. A first-principles walk through what actually breaks.I Burned 23 Billion Tokens to "Rewrite" Langfuse2026-06-26T00:00:00+00:002026-06-26T00:00:00+00:00Dennis Zhuanghttps://blog.fnil.net/openfuse-23-billion-tokens/A migration retro: forking Langfuse to swap its analytics store from ClickHouse to GreptimeDB, run mostly by two AI agents. Most of the work was paying down the debt of one decision — make a single database both the source of truth and the analytics layer.The Three Pillars of Observability: The Unification That Never Quite Arrived (Part 2 of 2)2026-06-16T00:00:00+00:002026-06-16T00:00:00+00:00Dennis Zhuanghttps://blog.fnil.net/observability-unification-history/Part 1 was about how the three pillars split apart. This part is about how many smart people, starting in 2018, tried to put them back together — what they actually built, and why none of it quite reached the finish line.The Three Pillars of Observability: A History No One Planned (Part 1 of 2)2026-06-10T00:00:00+00:002026-06-10T00:00:00+00:00Dennis Zhuanghttps://blog.fnil.net/observability-three-pillars-history/Today we treat metrics, logging, and tracing as the natural structure of observability. But it wasn't designed; it grew. Part 1, on how it split apart (2010–2017).When Systems Turn Uncertain: How Datadog Sees Observability in the AI Era2026-05-31T00:00:00+00:002026-05-31T00:00:00+00:00Dennis Zhuanghttps://blog.fnil.net/datadog-ai-observability/Datadog's Investor Day deck quietly redefines observability: the object of observation turns probabilistic, AI agents become operators, and the reader of the data shifts from human to model.TMA1 v2: Making the Agent Loop actually loop2026-05-23T00:00:00+00:002026-05-23T00:00:00+00:00Dennis Zhuanghttps://blog.fnil.net/tma1-v2-agent-loop/TMA1 v2 adds an MCP server, enhanced hooks that auto-inject build/session/anomaly context, and cross-agent context sharing between Claude Code and Codex.Observing my coding agents without leaving localhost2026-03-18T00:00:00+00:002026-03-18T00:00:00+00:00Dennis Zhuanghttps://blog.fnil.net/local-observability-tool-for-coding-agents/TMA1: a local observability tool for AI coding agents with full session trace, tool decision breakdown, latency tracking, and SQL-queryable storage.