https://blog.fnil.net • 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 website Recent posts Updated on $DATE date Think and Act as One Think and Act as One CEO & Founder of Greptime. Writing about systems, distributed computing, AI & Programming. Zola2026-09-02T00:00:00+00:00https://blog.fnil.net/atom.xml LLMs Already Understand Observability. What Is Left for the Database? 2026-09-02T00:00:00+00:00 2026-09-02T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/what-is-left-for-the-database/ The last post in this series. The time for unified observability has come, so what should a database actually do about it? My answer is probably smaller than you expect, and "doing less" is what I arrived at after thinking it through. Twenty Years of S3: How It Became the Default Persistence Layer for Modern Data Infrastructure 2026-08-20T00:00:00+00:00 2026-08-20T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/s3-at-twenty/ S3 launched twenty years ago as a simple object store with eventual consistency. Strong consistency, conditional writes, and Express One Zone turned it into the durable source of truth for warehouses, streaming systems, databases, and now Git hosting. Bigtable at Twenty: What Stayed and What Got Rebuilt 2026-07-31T00:00:00+00:00 2026-07-31T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/bigtable-at-twenty/ SIGMOD Companion '26 has a 13-page paper by 50+ Google authors revisiting Bigtable two decades on. 10 EB, 7 billion QPS, and an architecture that barely moved. This is my reading of why. Why Now: The Eight-Year Wait for Unified Observability 2026-07-16T00:00:00+00:00 2026-07-16T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/observability-unification-why-now/ An idea someone had fully worked out back in 2018, yet it took eight years before it could actually be built. This piece is about one thing: why now. When Agents Go to Production: What Actually Breaks 2026-07-09T00:00:00+00:00 2026-07-09T00:00:00+00:00 Dennis Zhuang https://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" Langfuse 2026-06-26T00:00:00+00:00 2026-06-26T00:00:00+00:00 Dennis Zhuang https://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 2026-06-16T00:00:00+00:00 2026-06-16T00:00:00+00:00 Dennis Zhuang https://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 2026-06-10T00:00:00+00:00 2026-06-10T00:00:00+00:00 Dennis Zhuang https://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 Era 2026-05-31T00:00:00+00:00 2026-05-31T00:00:00+00:00 Dennis Zhuang https://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 loop 2026-05-23T00:00:00+00:00 2026-05-23T00:00:00+00:00 Dennis Zhuang https://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 localhost 2026-03-18T00:00:00+00:00 2026-03-18T00:00:00+00:00 Dennis Zhuang https://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. Six Ways to Make Your Infrastructure Agent-Friendly 2026-03-05T00:00:00+00:00 2026-03-05T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/agent-friendly-infrastructure/ Have we been building infrastructure for humans this whole time, without ever treating agents as users? Six principles for agent-friendly infrastructure, rooted in Unix philosophy. Is Database MCP Just Unnecessary Overhead? 2026-01-20T00:00:00+00:00 2026-01-20T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/database-mcp-unnecessary/ My colleague called Database MCP 'pulling your pants down to fart.' After thinking about it, I mostly agree—but we built one anyway. My AI Coding Experience: Three Principles 2025-12-17T00:00:00+00:00 2025-12-17T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/vibe-coding-experience/ AI Coding doesn't fundamentally make you a better programmer. It's an amplifier—amplifying your strengths and your weaknesses. Using AI ≠ AI Native: What It Really Means to Transform How Teams Work 2025-12-11T00:00:00+00:00 2025-12-11T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/ai-native-team/ The difference between using AI as a tool you pick up occasionally versus treating AI as infrastructure you don't know how to work without. Rethinking Software Design Principles in the Age of Vibe Coding 2025-11-28T00:00:00+00:00 2025-11-28T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/vibe-coding-principles/ When AI can rewrite an entire module in seconds, do the design principles built for 'humans maintaining code' still apply? The AI Productivity Divide: From 10x to 100x Engineers 2025-11-27T00:00:00+00:00 2025-11-27T00:00:00+00:00 Dennis Zhuang https://blog.fnil.net/100x-engineer/ AI's real value isn't in producing the final output—it's in creating Builders. Whether you can create Builders is what separates the 2x from the 100x.