scaling

Peter Rizun and Andrew Stone present results of tests running 1 GB blocks on a Bitcoin test network at Scaling Bitcoin Stanford. The talk argues for big-block scaling and discusses its consequences.

Stanford Blitzscaling class session where Reid Hoffman interviews Eric Schmidt about structuring teams and scaling Google. Topics include Alphabet, hiring, and how Chrome and Android operated inside the company.

Rick Reed of WhatsApp explains at Erlang Factory 2014 how the service scaled to billions of messages with a very small engineering team. He covers the FreeBSD and Erlang stack, Mnesia usage, server counts and bottleneck work.

A Linear engineer talks about scaling the company's sync engine, which keeps client data local and synchronized. It follows an earlier talk on the same system.

An Alan Kay talk on programming and scaling, covering theoretical limits of code size, engineering versus tinkering, and biological cells as inspiration for object-oriented design.

Matt Ranney of Uber talks at GOTO Chicago 2016 about what Uber learned from growing past 1,000 production microservices. He covers regrets, sprawl and organizational effects.

Richard Feldman's Elm Europe 2017 talk on how to structure and scale large Elm applications, including when to nest messages.

A 4K AI-upscaled, subtitled fan edit of David Lynch's 1984 Dune by Spicediver that restores deleted and lost footage to form an alternative cut.

Allan Jude of Klara presents work on making ZFS scale on fast NVMe storage, covering fixes to the TaskQueue interface and removal of bottlenecks. The talk was given at EuroBSDcon 2022 and describes raising write throughput from about 3 to over 7 GB/sec.

Dropbox engineer Kevin Modzelewski gives a Stanford colloquium on Dropbox's history and the technical problems it faced scaling, including detailed database schema decisions.

Physicist Geoffrey West speaks at an FQXi conference on time about complexity and scaling laws. He covers how metabolism, growth and lifespan scale across organisms and how the same mathematics applies to cities and companies.

A Welch Labs explainer on neural scaling laws and the compute-efficient frontier, asking why model loss seems to hit a line it cannot cross. It draws an analogy to an ideal gas law for AI.

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.

Rick Reed of WhatsApp speaks at MeetBSD about running a messaging service on FreeBSD and Erlang at huge scale. He covers the stack, tuning and the challenges of millions of connections per host.

Matt Godbolt tells the story of Compiler Explorer, from a hacky basement server to a cloud-scaled service handling tens of thousands of daily requests. He also shows its features and how it is built.

A PyCon 2012 talk by early YouTube engineer Mike Solomon on how YouTube scaled its architecture, which is mostly Python.

Bryan Cantrill's Scale By The Bay 2019 talk on software after Moore's Law. He covers the end of easy scaling and the move toward specialized, emerging architectures.

Sophie Wilson, designer of the ARM instruction set, discusses the future of microprocessors, including the economics of scaling below 28nm and why much of a chip must stay powered off.

Part one of Capt. Grace Hopper's 1982 NSA lecture on the future of data, hardware, software and people. It includes her humor, her nanosecond demonstration and views on scaling and resisting old ways of doing things.

A clip from Lex Fridman's podcast in which chip architect Jim Keller argues that Moore's Law is not dead and that transistor scaling still has lots of room. He also discusses how to break down hard problems.

Rob Miles discusses GPT-3 on Computerphile, covering how scaling parameters kept improving results over GPT-2 and how the model nearly learned arithmetic without anyone knowing exactly how.

An AWS re:Invent 2018 session in which Holly Mesrobian and Marc Brooker explain how AWS Lambda is built, including its sandboxing, isolation and scaling architecture. It covers what happens under the hood when serverless code runs.

A Google Tech Talk by Raymond Blum on how Google backs up massive amounts of data such as Gmail and Picasa. It covers scaling challenges, failure types, and approaches that did not work, including tape.

Jim Keller gives a UC Berkeley EECS colloquium arguing that Moore's Law is not dead. He surveys upcoming technologies and the multiple innovation curves that can keep transistor density and performance scaling.

Andrej Karpathy gives a one-hour general-audience introduction to large language models, covering what they are, how they are trained, comparisons to operating systems, and security challenges such as jailbreaks.

Cal Henderson's DjangoCon 2008 keynote, "Why I Hate Django", is a funny critique of Django from a Flickr architect. It touches on scaling topics such as database replication.

Lex Fridman interviews Instagram co-founder and former CEO Kevin Systrom about building the product, its early days and its pivot story.

Footage shot in New York City in 1911 by a Swedish film company, upscaled to 4K and 60 fps with neural networks and optionally colorized. The creator notes the colors are artificial and added only for ambiance.

A two-minute supercut of film and TV characters ordering a computer to 'enhance' a blurry image into a perfectly sharp one. It is a remaster of an earlier 2009 version.

A two-minute compilation of TV and film scenes where investigators say 'enhance' and a blurry image becomes sharp. It mocks the trope.

Anthony Marcar describes lessons from three years of using Clojure at WalmartLabs, including scaling a team and a large multi-project codebase in an enterprise setting.

Sasa Juric explains what makes Erlang and Elixir suited to server-side systems, focusing on the BEAM concurrency model rather than syntax or ecosystem. He demonstrates processes, supervision, and fault tolerance.

Will Wilson of FoundationDB explains how the team tested their distributed database using deterministic simulation. By running the whole system in a simulator with injected faults and reproducible seeds, they could find rare concurrency and network bugs.

Richard Cook's short Velocity 2013 talk on resilience in complex adaptive systems, arguing systems operate near the edge of failure and that the surprise is how rarely they fail. He presents a model of how pressures push systems toward failure boundaries.

Bryan Cantrill's GOTO Chicago 2017 talk on debugging production systems under pressure, centered on the incident where an operator's mistyped command rebooted an entire Joyent datacenter. It covers human factors, automation and architecture.

Rick Houlihan's AWS re:Invent 2018 deep dive on advanced DynamoDB design patterns. It covers index overloading, GSI sharding, composite keys, graph processing and transactions.

Martin Kleppmann argues that databases are global shared mutable state and proposes treating them as an ever-growing log of immutable facts. Derived data such as caches, indexes and views is then built by stream processors like Apache Samza. The talk draws on Kafka and LinkedIn's experience with commit logs.

Rich Hickey's 2013 talk applies language-design thinking to whole systems, covering names, queues, data, failure, and the interfaces between programs. It ends with a call to action for building systems holistically.

Rob Pike's Google I/O 2012 talk shows how goroutines and channels solve tricky concurrency problems with simple Go code. It features a playful goroutine demo with gophers passing messages and a search engine example.

Howard Abrams demonstrates, in an EmacsConf 2015 talk, how he uses org-mode's Babel and Tramp to configure and operate remote servers from a single document. Code blocks, their results and the explanatory text all live together.