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Building Software Systems At Google and Lessons Learned

Stanford4 HN recommenders · 2012–2022
257K views · lecture · evergreen · Uploaded 2011-06-02

Jeff Dean of Google describes his experiences building Google's systems and how its infrastructure evolved over time. The Stanford talk covers search, scaling tipping points and lessons from building large-scale software.

HN recommends it as a classic look at systems engineering at Google, whose fundamentals have held up well despite its 2010 date.

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5 comments from Hacker News

@kqr22012 · in “Latency Numbers Every Programmer Should Know”

Also recommend Jeff Dean's tech talk Building Software Systems At Google and Lessons Learned which references those latency numbers. Slides: [LINK] Video: [VIDEO] Also, a previous thread on latency numbers: [LINK]

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@boulos2016 · in “Ask HN: What's your favorite tech talk?”

In addition to Linus's git talk, I really enjoyed Jeff Dean's EE380 retrospective on Building Systems at Google ( [VIDEO] ). Many people have mentioned Jeff's basic premise elsewhere ("Design a system for 10x your current need, but not 100x, rewrite it before then") but this talk gave several useful examples where tipping points occurred (at least with Search).

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@ignoramous2019 · in “AWS Nitro System”

Google is famous for publishing a lot of material every year. A couple of related publications you might be interested in: 1. The Datacenter as a computer: [LINK] 2. The SRE book: [LINK] A couple of dated presentations: 1. Jeff Dean on building software systems at Google (2010) at Stanford: [VIDEO] 2. Notes by James Hamilton on a talk by Jeff Dean on Google Datacenters in 2008: [LINK] -- Microsoft Research pretty much work on bleeding edge tech, as well and publish about some of their research pretty regularly. Here's a staring point to help anyone interested find relevant publications: [LINK]

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@ma2rten2020 · in “Web Performance Profiling: Google.com”

There is a lecture from Jeff Dean about it: [VIDEO] It's from 2010, but the fundamentals probably haven't changed.

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@mrazomor2022 · in “We're improving search results when you use quotes”

Probably this one: [LINK] Or this one: [VIDEO] (terrible audio) Both are very old, but extremely well aged. IMO, the secret behind Google Search is not the smartness of the algorithms, but how much of it is baked in those O(100ms) which takes Google machines to answer your query. That's why the links above are the true reason Google Search performs well. Natural Language Processing and Information Retrieval state of the art is far beyond what Google/Bing/Yahoo/Yandex/Baidu employ. But, it's far too expensive to serve it at QPS & latency required for decent UX.

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