Posts

TLA+ Modeling of AWS outage DNS race condition

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On Oct 19–20, 2025, AWS’s N. Virginia region suffered a major DynamoDB outage triggered by a DNS automation defect that broke endpoint resolution. The issue cascaded into a region-wide failure lasting nearly a full day and disrupted many companies’ services. As with most large-scale outages, the “DNS automation defect” was only the trigger; deeper systemic fragilities ( see my post on the Metastable Failures in the Wild paper ) amplified the impact. This post focuses narrowly on the race condition at the core of the bug, which is best understood through TLA+ modeling. My TLA+ model builds on Waqas Younas’s Promela/Spin version . To get started quickly, I asked ChatGPT to translate his Promela model into TLA+, which turned out to be a helpful way to understand the system’s behavior, much more effective than reading the postmortem or prose descriptions of the race. The translation wasn’t perfect, but fixing it wasn’t hard. The translated model treated the enactor’s logic as a single atom...

Barbarians at the Gate: How AI is Upending Systems Research

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This recent paper from the Berkeley Sky Computing Lab has been making waves in systems community. Of course, Aleksey and I did our live blind read of it, which you can watch below. My annotated copy of the paper is also available here. This is a fascinating and timely paper. It raises deep questions about how LLMs will shape the research process, and how that could look like. Below, I start with a short technical review, then move to the broader discussion topics. Technical review The paper introduces AI-Driven Research for Systems (ADRS) framework. By leveraging the OpenEvolve framework ,  ADRS integrates LLMs directly into the systems research workflow to automate much of the solution-tweaking and evaluation process. As shown in Figure 3, ADRS operates as a closed feedback loop in which the LLM ensemble iteratively proposes, tests, and refines solutions to a given systems problem. This automation targets the two most labor-intensive stages of the research cycle, solution tweaking...

Academic chat: On PhD

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This week, Aleksey and I met not to dissect a research paper, but to chat about "the process of PhD". I had recently wrote a post titled "The Invisible Curriculum of Research" , where I framed research as an iceberg, with the small visible parts (papers, conferences) resting on the hidden 5 Cs: Curiosity/Taste: what problems are worth solving. Clarity: how to ask precise and abstracting questions. Craft: writing, experimentation, presentation. Community: collaboration and contribution. Courage: resilience through setbacks. Above is the video of our chat, with a lot of personal anecdotes and a few rants. But if you want to cut to the chase, the highlight reel is below. What a PhD Really Produces The real product of a PhD is not the thesis, but you, the researcher! The thesis is just the residue of this long internal transformation. Like martial arts, the training breaks you and rebuilds you into someone who sees and thinks differently. This transformation cannot be ...

Tiga: Accelerating Geo-Distributed Transactions with Synchronized Clocks

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This paper (to appear at SOSP'25) is one of the latest efforts exploring the dream of a one-round commit for geo-replicated databases. TAPIR tried to fuse concurrency control and consensus into one layer. Tempo and Detock went further using dependency graphs.  Aleksey and I did our usual thing. We recorded our first blind read of the paper. I also annotated a copy while reading, which you can access here . We liked the paper overall. This is a thoughtful piece of engineering, not a conceptual breakthrough. It uses  future timestamps to align replicas  in a slightly new way, and the results are solid. But the presentation needs refinement and stronger formalization. (See our livereading video about how these problems manifested themselves.)  Another study to add to my survey , showing how, with modern clocks, time itself is becoming a coordination primitive. The Big Idea Tiga claims to do strictly serializable one-shot (multi-shot ok with reconnaissance queries t...

The Invisible Curriculum of Research

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Courses, textbooks, and papers provide the formal curriculum of research. But there is also an invisible curriculum. Unwritten rules and skills separate the best researchers from the rest. I did get an early education on this thanks to my advisor, Anish . He kept mentioning "taste", calling some of my observations and algorithms "cute", and encouring me to be more curious and creative and to develop my "taste".  Slowly, I realized that what really shapes a research career isn't written in any textbook or taught in any course. You learn it by osmosis from mentors, and through missteps: working on the wrong problem, asking shallow questions, botching a project, giving up too soon. But if you can absorb these lessons faster, you will find research more fulfilling. The visible curriculum teaches you how to build a car. The invisible curriculum teaches you where to go, who to ride with, and how to keep going when the road turns uphill. After 25 years of exp...

Four Ivies. Two days.

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This is my long-overdue trip report from last summer: July 10–11, 2024. We toured Ivy League campuses to help our rising senior son weigh his options, with our two daughters (our kids are four years apart each) tagging along for an early preview. Day one was Yale and Brown, followed by a night in New Jersey. Day two took us to Princeton and UPenn, then the long drive back to Buffalo. Of course we drove , that's how we roll . Prelude Lining up campus tours is its own sport. They are booked months in advance. Pro-tip: when your kid is born, call the colleges to reserve their campus visit. We lucked into two open slots, then hacked together a Python script to snipe cancellations and grabbed the other two. Not proud of this, but that's what it takes if you don't book months in advance. The U.S. college admissions process is Byzantine. It is a weird mix of ritual and performance. There are entire books about how to write the college essay . I have plenty to say about the so-cal...

Supporting our AI overlords: Redesigning data systems to be Agent-first

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This Berkeley systems group paper opens with the thesis that LLM agents will soon dominate data system workloads. These agents, acting on behalf of users, do not query like human analysts or even like the applications written by them. Instead, the LLM agents bombard databases with a storm of exploratory requests: schema inspections, partial aggregates, speculative joins, rollback-heavy what-if updates. The authors calls this behavior agentic speculation . Agentic speculation is positioned as both the problem and the opportunity. The problem is that traditional DBMSs are built for exact intermittent workloads and cannot handle the high-throughput redundant and inefficient querying of LLM agents. The opportunity also lies here. Agentic speculation has recognizable properties and features that invite new designs. Databases should adapt by offering approximate answers, sharing computation across repeated subplans, caching grounding information in an agentic memory store, and even steering...

Disaggregation: A New Architecture for Cloud Databases

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This short VLDB'25 paper  surveys disaggregation for cloud databases. It has several insightful points, and I found it worth summarizing.  The key advantage of the cloud over on-prem is elastic scalability: users can scale resources up and down and pay only for what they use. Traditional database architectures, like shared-nothing, do not fully exploit this. Thus, cloud-native databases increasingly adopt disaggregated designs. Disaggregation is primarily motivated by the asymmetry between compute and storage: Compute is far more expensive than storage in the cloud. Compute demand fluctuates quickly; storage grows slowly. Compute can be stateless and easier to scale, while storage is inherently stateful. Decoupling them lets compute scale elastically while storage remains relatively stable and cheap. Review of Disaggregation in the Clouds Early cloud-native systems like Snowflake and Amazon Aurora separate compute and storage into independent clusters. Modern systems push dis...

Our Myrtle Beach vacation

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This year was a bastard. Not from work. God, no, I find work relaxing. Reading papers, inventing algorithms, ripping apart distributed systems with TLA+ models -- that's how I have fun. I can do that all day with a grin on my face. But the minute I need to do adulting (like simply calling the cable company and ask why keep increasing our bill when I'm not looking), I will stress and procrastinate. And this year, I had a lot of adulting to do to put our house on market, and plan a move to California, all the while juggling to help three kids with school and EC activities. No wonder I've been grinding my teeth at night like a mule chewing rocks... Anywho, we botched our great escape to California. House didn't sell quickly, as we hoped it would, and we are stuck in Buffalo for another year. Summer disappeared in a cloud of errands and disappointment, and suddenly it was late August with our kids twitching with pre-school nerves. There was still some time left to salvage t...

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