Stuff The Internet Says On Scalability For August 4th, 2017

Hey, it's HighScalability time:

Hands down the best ever 25,000 year old selfie from Pech Merle cave in southern France. (The Ice Age)

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• 35%: US traffic is now IPV6; 10^161: decision points in no-limit Texas hold’em; 4.5 billion: Facebook translations per day; 90%: savings by moving to Lambda; 330TB: IBM's tiny tape cartridge, enough to store 330 million books; $108.9 billion: game revenues in 2017; 85%: of all research papers are on Sci-Hub; 1270x: iPhone 5 vs Apollo guidance computer; 16 zettabytes: 2017 growth in digital universe; 


• Quotable Quotes:
  • Andrew Roberts: [On Napoleon] No aspect of his command was too small to escape notice.
  • Jason Calacanis: The world has trillions of dollars sitting in bonds, cash, stocks, and real estate, which is all really “dead money.” It sits there and grows slowly and safely, taking no risk and not changing the world at all. Wouldn’t it be more interesting if we put that money to work on crazy experiments like the next Tesla, Google, Uber, Cafe X, or SpaceX?
  • @icecrime: The plural of “it’s not a bug, it’s a feature” is “it’s not a bug tracker, it’s a backlog”.
  • Jeff Darcy: When greater redundancy drives greater dependency, it’s time to take a good hard look at whether the net result is still a good one.
  • uhnuhnuhn: "They ran their business into the ground, but they did it with such great tech!"
  • Anglés-Alcázar: It’s very interesting to think of our galaxy not as some isolated entity, but to think of the galaxy as being surrounded by gas which may come from many different sources. We are connected to other galaxies via these galactic winds.
  • @ojiidotch: Main app now running Python 3.6 (was 2.7 until yesterday). CPU usage 40% down, avg latency 30% down, p95 60% down.
  • Nemanja Mijailovic: It’s really difficult to catch all bugs without fuzzing, no matter how hard you try to test your software. 
  • SandwichTeeth: a lot of companies have security teams solely to meet audit requirements. If you find yourself on a team like that, you'll be spending a lot of time just gathering evidence for audits, remediating findings and writing policy. I really loved security intellectually, but in practice, the blue-team side of things wasn't my cup of tea.
  • jph: security is needed to gradually escalate a user's own identity verification -- think of things like two-factor auth and multi-factor auth, that can phase in (or ramp up) when a user's actions enter a gray area of risk. Some examples: when a user signs in from a new location, or a user does an especially large money transfer, or a user resumes an account that's been dormant for years, etc.
  • @hichaelmart: So while Google is doubling down on gRPC it seems that Amazon is going all in with CBOR. DDB DAX uses some sort of CBOR-over-sockets AFAICT
  • Wysopal: I’d like to see someone fixing this broken market [insecure software and hardware market]. Profiting off of that fix seems like the best approach for a capitalism-based economy.
  • Matthias Käppler: Microservices are often intermediate nodes in a graph of services, acting as façades where an incoming request translates to N outgoing requests upstream, the responses to which are then combined into a single response back downstream to the client.
  • Jack Fennimore: EA Play 2017 was watchable the same way Olive Garden is edible.
  • erikb: [On SoundCloud] TL;DR Top Management started too late to think about making actual money. They also hired an asshole for their US offices. When they got an opportunity to be bought by Twitter they asked for way too much money. And the CEO is basically on a constant holidays trip since 2014, while not failing to rub it in everybody's face via Instagram photos.
  • Jennifer Mendez: If you don’t have the games people want to play, you can wave goodbye to return on investment on a powerful console. Does hardware matter? Of course it does! But it doesn’t matter if you don’t have anything to play on it.
  • Alex Miller: The utility of a blockchain breaks down in a private or consortium setting and should, in my opinion, be replaced by a more performant engine like Apache Kafka.
  • Krish: most of the multi-cloud usecases I am seeing are about using different cloud for different workloads. It could change and I would expect them to embrace the eventual consistency model initially
  • Ian Cutress: Then there is the Ryzen 3 1300X. Compared to the Core i3-7300/7320 and the Core i5-7400, it clearly wins on performance per dollar all around. Compared to the Core i3-7100 though, it offers almost 5% more performance for around $10-15 more, which is just under 10% of the cost.
  • throw2016: Just from an year ago the cpu market has changed completely. The sheer amount of choice at all levels is staggering. For the mid level user the 1600 especially is a formidable offering, and the 1700 with 8 cores just ups the ante.
  • danmaz74: the main reason Rails is declining in relevance isn't microservices or the productivity (!) of Java, but the fact that more and more development effort for web applications is moving into JS front-end coding.
  • Rohit Karlupia: we can deal with [S3] eventual consistency in file listing operations by repeating the listing operation, detecting ghost and conceived files and modifying our work queues to take our new knowledge about the listing status into account.
  • tboyd47: It's the end of an era. From 2005 to 2007, the "Web 2.0" craze, the release of Ruby on Rails, and the rise of Agile methods all happened at once. These ideas all fed into and supported each other, resulting in a cohesive movement with a lot of momentum. The long-term fact turned out to be that this movement didn't benefit large corporations that have always been and usually still are the main source of employment for software developers. So we have returned to our pre-Rails, pre-agile world of high specialization and high bureaucratic control, even if Rails and "Agile" still exist with some popularity.
  • @reneritchie: Only beginning to see the advantages of Apple making everything from atom to bit. Everything will be computational.
  • Vasiliy Zukanov: switching to Kotlin will NOT have any appreciable positive gains on the cost, the effort or the schedule of software projects
  • visarga: Over the years I have seen astronomy become more like biology - diverse both in the kinds of objects it describes and their behavior.
  • Jaana B. Dogan: I think the industry needs a breakdown between product and infra engineering and start talking how we staff infra teams and support product development teams with SRE. The “DevOps” conversation is often not complete without this breakdown and assuming everyone is self serving their infra and ops all the times.
  • David Rosenthal~ Does anybody believe we'll be using Bitcoin or Ethereum 80 years from now?
  • Richard Jones: There is a physical lower limit on how much energy it takes to carry out a computation – the Landauer limit. The plot above shows that our current technology for computing consumes energy at a rate which is many orders of magnitude greater than this theoretical limit (and for that matter, it is much more energy intensive than biological computing). There is huge room for improvement – the only question is whether we can deploy R&D resources to pursue this goal on the scale that’s gone into computing as we know it today.

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The Next Scalability Hurdle: Massively Multiplayer Mobile AR

Many moons ago, in Building Super Scalable Systems: Blade Runner Meets Autonomic Computing In The Ambient Cloud, I said we still had scaling challenges ahead, that we've not yet begun to scale, that we still don't know how to scale at a planetary level.

That was 7 years ago. Now Facebook has 2 billion monthly users. There's no reason to think they can't scale an unimpressive 3.5x to handle the rest of the planet. WhatsApp is at one billion daily users. YouTube is at 1.5 billion monthly users.

So it appears we do know how to service a whole planet full of people (and bots). At least a select few companies with vast resources know how. We are still no closer to your average developer being able to field a planet scale service. The winner take all nature of the Internet seems to fend off decentralization like it's a plague. Maybe efforts like Filecoin will change the tide. 

There's another area we have scaling challenges: Massively Multiplayer Mobile AR (Augmented Reality). While AR has threatened to be the future for quite some time, it now looks like the future may be just around the virtual corner.

Apple Introducing ARKit, a hit with developers, means that future will be sooner rather than later. One billion iPhone users make it so. Remember when the iPhone was introduced, how the increased data usage melted AT&Ts' network? This will be worse. 

Pokémon Go had a little event recently that shows what incredible stress such systems will put on our infrastructure. No need to repeat the story, iMore has it all: Pokémon Go Fest: What happened and why, Pokémon Go Fest's big flop shows Niantic needs to think bigger, Pokémon Go Fest Chicago: The fun, the failure, and the legendary, UPDATED: Are AT&T's iPhone Problems Due to Network Configuration Errors?

It's true, Pokémon Go has been well known for its scaling problems, but this was a planned event, shouldn't it have been handled better? No doubt. Still, a concentration of 20,000 players in a single shard, in such a small "kill zone" like a park, is a challenge. Should they have brought in Cell on Wheels, use high density WiFi, maybe put up microwave links to increase the backhaul? Yep, that seems reasonable. EM spectrum is a terrible thing to waste.

But what happens when Pokémon Go Fest is just what we call Tuesday? When everyone is using mobile AR? Every product in every store, every building, every sign, everything will have some sort of data driven overlay. There will be no chance to build special infrastructure. Infrastructure must be improved to handle the new loads. Hopefully 5G will come to the rescue.

Spectrum isn't the only problem. Compute resources are also a problem. Pokémon Go isn't a particularly data intensive game. It doesn't require a lot interaction between users or constant communication with backend servers. What happens we we have multiple games like that all operating at once?

Pokémon Go seems like a poster child for edge computing. The entire shard could have been handled by a portable onsite datacenter with its own local communication infrastructure. An onsite datacenter combines low latency compute with enough scale to handle the load. My guess is the thundering herd problem that blocked players connecting to the game would have disappeared. Players would have connected quickly to the local game servers and started playing the game with little muss or fuss. Same with game state.

Perhaps in the future we'll have datacenter handoff protocols just like we have cell network handoff protocols today. And if we really do it right, the big scheduler in the sky that will coordinate all these moving parts, might consider distributed compute resources like smartphones as part of the compute fabric.

We have not yet begun to scale Massively Multiplayer Mobile AR. 

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Stuff The Internet Says On Scalability For July 28th, 2017s

Hey, it's HighScalability time:

Jackson Pollock painting? Cortical column? Nope, it's a 2 trillion particle cosmological simulation using 4000+ GPUs. (paper, Joachim Stadel, UZH)

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• 1.8x: faster code on iPad MacBook Pro; 1 billion: WhatsApp daily active users; 100 milliamps: heart stopping current; $25m: surprisingly low take from ransomware; 2,700x: improvement in throughput with TCP BBR; 620: Uber locations; $35.5 billion: Facebook's cash hoard; 2 billion: Facebook monthly active users; #1: Apple is the world's most profitable [legal] company; 500,000x: return on destroying an arms depot with a drone; 


• Quotable Quotes:
  • Alasdair Allan: Jeff Bezos’ statement that “there’s not that much interesting about CubeSats” may well turn out to be the twenty first century’s “nobody needs more than 640kb.”
  • @hardmaru: Decoding the Enigma with RNNs. They trained a LSTM with 3000 hidden units to decode ciphertext with 96%+ accuracy. 
  • @tj_waldorf: Morningstar achieved 97% cost reduction by moving to AWS. #AWSSummit Chicago
  • Ed Sperling: Moore’s Law is alive and well, but it is no longer the only approach. And depending on the market or slice of a market, it may no longer be the best approach.
  • @asymco: With the end of Shuffle and Nano iPods Apple now sells only Unix-enabled products. Amazing how far that Bell Labs invention has come.
  • @peteskomoroch: 2017: RAM is the new Hadoop
  • Carlo Pescio: What if focusing on the problem domain, while still understanding the machine that will execute your code, could improve maintainability and collaterally speed up execution by a factor of over 100x compared to popular hipster code?
  • @stevesi: Something ppl forget: moving products to cloud, margins go down due to costs to operate scale services—costs move from Customer to vendor.
  • @brianalvey: The most popular software for writing fiction isn't Word. It's Excel.
  • @pczarkowski: How to make a monolithic app cloud native: 1) run it in a docker 2) change the url from .com to .io
  • @tj_waldorf: Morningstar achieved 97% cost reduction by moving to AWS. #AWSSummit Chicago
  • drinkzima: There is a huge general misunderstanding in the profitability of directing hotel bookings vs flight bookings or other types of travel consumables. Rate parity and high commission rates mean that directing hotel rooms is hugely profitable and Expedia (hotels.com, trivago, expedia) and Priceline (booking.com) operate as a duopoly in most markets. They are both marketing machines that turn brand + paid traffic into highly profitable room nights.
  • Animats: This is a classic problem with AI researchers. Somebody gets a good result, and then they start thinking strong human-level AI is right around the corner. AI went through this with search, planning, the General Problem Solver, perceptrons, the first generation of neural networks, and expert systems. Then came the "AI winter", late 1980s to early 2000s, when almost all the AI startups went bust. We're seeing some of it again in the machine learning / deep neural net era.
  • Charity Majors: So no, ops isn't going anywhere. It just doesn't look like it used to. Soon it might even look like a software engineer.
  • @mthenw: As long as I need to pay for idle it’s not “serverless”. Pricing is different because in Lambda you pay for invocation not for the runtime.
  • Kelly Shortridge: The goal is to make the attacker uncertain of your defensive environment and profile. So you really want to mess with their ability to profile where their target is
  • @CompSciFact: 'About 1,000 instructions is a reasonable upper limit for the complexity of problems now envisioned.' -- John von Neumann, 1946
  • hn_throwaway_99: Few barriers to entry, really?? Sorry, but this sounds a bit like an inexperienced developer saying "Hey, I could build most of Facebook's functionality in 2 weeks." Booking.com is THE largest spender of advertising on Google. They have giant teams that A/B test the living shite out of every pixel on their screens, and huge teams of data scientists squeezing out every last bit of optimization on their site. It's a huge barrier to entry. 
  • callahad: It's real [performance improvements]. We've [Firefox] landed enormous performance improvements this year, including migrating most Firefox users to a full multi-process architecture, as well as integrating parts of the Servo parallel browser engine project into Firefox. There are still many improvements yet-to-land, but in most cases we're on track for Firefox 57 in November.
  • Samer Buna: One important threat that GraphQL makes easier is resource exhaustion attacks (AKA Denial of Service attacks). A GraphQL server can be attacked with overly complex queries that will consume all the resources of the server.
  • wheaties: This is stupid. Really. Here we are in a world where the companies that own the assets (you know, the things that cost a lot of money) are worth less than the things that don't own anything. This doesn't seem "right" or "fair" in the sense that Priceline should be a middleman, unable to exercise any or all pricing power because it does not control the assets producing the revenue. I wonder how long this can last?
  • platz: Apparently deep-learning and algae are the same thing.
  • @CompSciFact: "If you don't run experiments before you start designing a new system, your entire system will be an experiment." -- Mike Williams
  • Scott Aaronson: our laws of physics are structured in such a way that even pure information often has “nowhere to hide”: if the bits are there at all in the abstract machinery of the world, then they’re forced to pipe up and have a measurable effect. 
  • The Internet said many more interesting things this week. To read them all please click through to the full article.


• Cool interview with Margaret Hamilton--NASA's First Software Engineer--on Makers. Programmers, you'll love this. One of the stories she tells is how her daughter was playing around and selected the prelaunch program during flight. That crashed the simulator. So like a good programmer she wanted to prevent this from happening. She tried to get a protection put in because an astronaut could actually do this during flight. Management would certainly allow this, right? She was denied. They said astronauts are trained never to make a mistake so it could never happen. Eventually she won the argument and was able to add code to protect against human error. So little has changed :-)

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7 Interesting Parallels Between the Invention of Tiny Satellites and Cloud Computing

CubeSats are revolutionizing space exploration because they are small, modular, and inexpensive to build and launch. On an episode of embedded.fm, Professor Jordi Puig-Suari gives a fascinating interview on the invention of the CubeSat. 195: A BUNCH OF SPUTNIKS.

What struck me in the interview is how the process of how the CubeSat was invented parallels how the cloud developed. They followed a very similar path driven by many of the same forces and ideas. 

Just what is a CubeSat? It's a "type of miniaturized satellite for space research that is made up of multiples of 10×10×10 cm cubic units. CubeSats have a mass of no more than 1.33 kilograms per unit, and often use commercial off-the-shelf (COTS) components for their electronics and structure."

Parallel #1:  University as Startup Incubator

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Stuff The Internet Says On Scalability For July 21st, 2017

Hey, it's HighScalability time:

Afraid of AI? Fire ants have sticky pads so they can form rafts, build towers, cross streams, & order takeout. We can CRISPR these guys to fight Skynet. (video, video, paper)

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• 222x: Bitcoin less efficient than a physical system of metal coins and paper/fabric/plastic; #1: Python use amongst Spectrum readers; 3x: time spent in apps that don't make us happy; 1 million: DigitalOcean users; 11.6 million: barrels of oil a day saved via tech and BigData; 200,000: cores on Cray super computer;$200B: games software/hardware revenue by 2021; $3K: for 50 Teraflops AMD Vega Deep Learning Box; 24.4 Gigawatts: China New Solar In First Half Of 2017; 


• Quotable Quotes:
  • sidlls: I think instead there is a category error being made: that CS is an appropriate degree (on its own) to become a software engineer. It's like suggesting a BS in Physics qualifies somebody to work as an engineer building a satellite.
  • Elon Musk: AI is a fundamental existential risk for human civilization, and I don’t think people fully appreciate that
  • Mike Elgan: Thanks to machine learning, it's now possible to create a million different sensors in software using only one actual sensor -- the camera.
  • Amin Vahdat (Google): The Internet is no longer about just finding a path, any path, between a pair of servers, but actually taking advantage of the rich connectivity to deliver the highest levels of availability, the best performance, the lowest latency. Knowing this, how you would design protocols is now qualitatively shifted away from pairwise decisions to more global views.
  • naasking: You overestimate AI. Incompleteness is everywhere in CS. Overcoming these limitations is not trivial at all.
  • 451: Research believes serverless is poised to undergo a round of price cutting this year.
  • Nicholas Bloom: We found massive, massive improvement in performance—a 13% improvement in performance from people working at home
  • @CoolSWEng: "A Java new operation almost guarantees a cache miss. Get rid of them and you'll get C-like performance." - @cliff_click #jcrete
  • DarkNetMarkets: We're literally funding our own investigation. 
  • Tristan Harris: By shaping the menus we pick from, technology hijacks the way we perceive our choices and replaces them with new ones. But the closer we pay attention to the options we’re given, the more we’ll notice when they don’t actually align with our true needs.
  • xvaier: If I have one thing to tell anyone who is looking for business ideas to try out their new programming skills on, I strongly suggest taking the time to learn as much as possible about the people to whom you want to provide a solution, then recruiting one of them to help you build it, lest you become another project that solves a non-issue beautifully.
  • @sebgoa: Folks, there were schedulers before kubernetes. Let's get back down to earth quickly
  • Mark Shead: A finite state machine is a mathematical abstraction used to design algorithms. In simple terms, a state machine will read a series of inputs. When it reads an input it will switch to a different state. Each state specifies which state to switch for a given input. This sounds complicated but it is really quite simple.
  • xantrel: I started a small business that started to grow, I thought I had to migrate to AWS and increase my cost by 5xs eventually, but so far Digital Ocean with their hosted products and block storage has handled the load amazingly well.
  • danluu: when I’m asked to look at a cache related performance bug, it’s usually due to the kind of thing we just talked about: conflict misses that prevent us from using our full cache effectively6. This isn’t the only way for that to happen – bank conflicts and and false dependencies are also common problems
  • Charles Hoskinson: People say ICOs (Initial Coin Offering) are great for Ethereum because, look at the price, but it’s a ticking time-bomb. There’s an over-tokenization of things as companies are issuing tokens when the same tasks can be achieved with existing blockchains. People are blinded by fast and easy money.
  • Charles Schwab: There don't seem to be any classic bubbles near bursting at the moment—at least not among the ones most commonly referenced as potential candidates.
  • Sertac Karaman: We are finding that this new approach to programming robots, which involves thinking about hardware and algorithms jointly, is key to scaling them down.
  • Michael Elling: When do people wake up and say that we’ve moved full circle back to something that looks like the hierarchy of the old PSTN? Just like the circularity of processing, no?
  • Benedict Evans: Content and access to content was a strategic lever for technology. I’m not sure how much this is true anymore.  Music and books don’t matter much to tech anymore, and TV probably won’t matter much either. 
  • SeaChangeViaExascaleOnDown: Currently systems are still based around mostly separately packaged processor elements(CPUs, GPUs, and other) processors but there will be an evolution towards putting all these separate processors on MCMs or Silicon Interposers, with silicon interposers able to have the maximum amount of parallel traces(And added active circuitry) over any other technology.
  • BoiledCabbage: Call me naive, but am I the only one who looks at mining as one of the worst inventions for consuming energy possible?
  • Amin Vahdat (Google):  Putting it differently, a lot of software has been written to assume slow networks. That means if you make the network a lot faster, in many cases the software can’t take advantage of it because the software becomes the bottleneck.


• Dropbox has 1.3 million lines of Go code, 500 million users, 500 petabytes of user data, 200,000 business customers, and a multi-exabyte Go storage system. Go Reliability and Durability at Dropbox. They use it for: RAT: rate limiting and throttling; HAT: memcached replacement; AFS: file system to replace global Zookeeper; Edgestore: distributed database; Bolt: for messaging; DBmanager: for automation and monitoring of Dropbox’s 6,000+ databases; “Jetstream”, “Telescope”, block routing, and many more. The good: Go is productive, easy to write and consume services, good standard library, good debugging tools. The less good: dealing with race conditions.


• Professor Jordi Puig-Suari talks about the invention of CubeSat on embedded.fm. 195: A BUNCH OF SPUTNIKS. Fascinating story of how thinking different created a new satellite industry. The project wasn't on anyone's technology roadmap, nobody knew they needed it, it just happened. A bunch of really bright students, in a highly constrained environment, didn't have enough resources to do anything interesting, so they couldn't build spacecraft conventionally. Not knowing what you're doing is an advantage in highly innovative environments. The students took more risk and eliminated redundancies. One battery. One radio. Taking a risk that things can go wrong. They looked for the highest performance components they could find, these were commercial off the shelf components that when launched into space actually worked. The mainline space industry couldn't take these sort of risks. Industry started paying attention because the higher performing, lower cost components, even with the higher risk, changed the value proposition completely. You can make it up with numbers. You can launch 50 satellites for the cost of one traditional satellite. Sound familiar? Cloud computing is based on this same insight. Modern datacenters have been created on commodity parts and how low cost miniaturized parts driven by smartphones have created whole new industries. CubeSats' had a standard size, so launch vehicles could standardize also, it didn't matter where the satellites came from, they could be launched. Sound familiar? This is the modularization of the satellite launching, the same force that drives all mass commercialization. Now the same ideas are being applied to bigger and bigger spacecraft. It's now a vibrant industry. Learning happens more quickly because they get to fly more. Sound familiar? Agile, iterative software development is the dominant methodology today. 

Don't miss all that the Internet has to say on Scalability, click below and become eventually consistent with all scalability knowledge (which means this post has many more items to read so please keep on reading)...

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You'll Never Believe the Big Hairy Audacious Startup John Jacob Astor Created in 1808

Think your startup has a Big Hairy Audacious Goal? Along with President Thomas Jefferson, John Jacob Astor  conceived (in 1808), and implemented (in 1810) a plan to funnel the entire tradable wealth of the westernmost sector of the North American continent north of Mexico through his own hands. Early accounts described it as “the largest commercial enterprise the world has ever known.”

Think your startup raised a lot of money? Astor put up $400,000 ($7,614,486 in today's dollars) of his own money, with more committed after the first prototype succeeded.

Think competition is new? John Jacob Astor dealt with rivals in one of three ways: he tried to buy them out; if that didn’t work, he tried to partner with them; if he failed to join them, he tried to crush them.

Think your startup requires commitment? Joining Astor required pledging five years of one’s life to a start-up venture bound for the unknownn.

Think your startup works hard? Voyageur's paddled twelve to fifteen hours per day, with short breaks while afloat for a pipe of tobacco. During that single day each voyageur would make more than thirty thousand paddle strokes. On the upper Great Lakes, the canoes traversed hundreds of miles of empty, forested shorelines and vast stretches of clear water without ports or settlements or sails, except for the scattered Indian encampment.

Think your product is complex? Astor planned, manned and outfitted one overseas and two overland expeditions to build the equivalent of a Jamestown settlement on the Pacific Coast.

Think your startup parties hard? Every nook and corner in the whole island swarmed, at all hours of the day and night, with motley groups of uproarious tipplers and whisky-hunters. It resembled a great bedlam, the frantic inmates running to and fro in wild forgetfulness. Many were eager for company and with a yen to cut loose—drinking, dancing, singing, whoring, fighting, buying knickknacks and finery from the beach’s shacks and stalls. 

Think your startup was an adventure you can never forget? I have been twenty-four years a canoe man, and forty-one years in service; no portage was ever too long for me. Fifty songs could I sing. I have saved the lives of ten voyageurs. Have had twelve wives and six running dogs. I spent all my money in pleasure. Were I young again, I should spend my life the same way over. There is no life so happy as a voyageur’s life!

Think people at your startup dress weird? Above the waist, the voyageurs wore a loose-fitting and colorful plaid shirt, perhaps a blue or red, and over it, depending on the weather, a long, hooded, capelike coat called a capote. In cold winds they cinched this closed with a waist sash—the gaudier the better, often red. From the striking sash dangled a beaded pouch that contained their fire-making materials and tobacco for their “inevitable pipe.”...The true “Man of the North” wore a brightly colored feather in his cap to distinguish himself from the rabble.

Think your startup takes risks? Half of them died.

And like most startups, they accomplished a lot, but ultimately failed to earn a payout.

Thomas Jefferson said to John Jacob Astor: Your name will be handed down with that of Columbus & Raleigh, as the father of the establishment and the founder of such an empire. Unfortunately, not so much Tom. How many have heard of Astor today? Not many, unless you've traveled to Astoria, Oregon. Astoria in the right weather is a gorgeous place with a hot beer scene.

It's trite to say the reward is in the journey, but in this case the saying is true, the journey was larger than digital life.

For the complete story read: Astoria: John Jacob Astor and Thomas Jefferson's Lost Pacific Empire: A Story of Wealth, Ambition, and Survival.

Stuff The Internet Says On Scalability For July 14th, 2017

Hey, it's HighScalability time:

We've seen algorithms expressed in seeds. Here's an algorithm for taking birth control pills expressed as packaging. Awesome history on 99% Invisible.

If you like this sort of Stuff then please support me on Patreon.

• 2 trillion: web requests served daily by Akamai; 9 billion: farthest star ever seen in light-years; 10^31: bacteriophages on earth; 7: peers needed to repair ransomware damage; $30,000: threshold of when to leave AWS; $300K-$400K: beginning cost of running Azure Stack on HPE ProLiant; 3.5M: files in the Microsoft's git repository; 300M: Google's internal image data training set size; 7.2 Mbps: global average connection speed; 85 million: Amazon Prime members; 35%: Germany generated its electricity from renewables;


• Quotable Quotes:
  • Jessica Flack: I believe that science sits at the intersection of these three things — the data, the discussions and the math. It is that triangulation — that’s what science is. And true understanding, if there is such a thing, comes only when we can do the translation between these three ways of representing the world.
  • gonchs: “If your whole business relies on us [Medium], you might want to pick a different one”
  • @AaronBBrown777: Hey @kelseyhightower, if you're surfing GitHub today, you might find it interesting that all your web bits come thru Kubernetes as of today.
  • Psyblog: The researchers were surprised to find that a more rebellious childhood nature was associated with a higher adult income.
  • Antoine de Saint-Exupéry: If you want to build a ship, don't drum up people to collect wood and don't assign them tasks and work, but rather teach them to long for the endless immensity of the sea.
  • Marek Kirejczyk: In general I would say: if you need to debug — you’ve already lost your way.
  • jasondc: To put it another way, RethinkDB did extremely well on Hacker News. Twitter didn't, if you remember all the negative posts (and still went public). There is little relation between success on Hacker News and company success.
  • Rory Sutherland: What intrigues me about human decision making is that there seems to be a path-dependence involved - to which we are completely blind.
  • joeblau: That experience taught me that you really need to understand what you're trying to solve before picking a database. Mongo is great for some things and terrible for others. Knowing what I know now, I would have probably chosen Kafka.
  • 0xbear: cloud "cores" are actually hyperthreads. Cloud GPUs are single dies on multi-die card. If you use GPUs 24x7, just buy a few 1080 Ti cards and forego the cloud entirely. If you must use TF in cloud with CPU, compile it yourself with AVX2 and FMA support. Stock TF is compiled for the lowest common denominator
  • Dissolving the Fermi Paradox: Doing a distribution model shows that even existing literature allows for a substantial probability of very little life, and a more cautious prior gives a significant probability for rare life
  • Peter Stark: Crews with clique structures report significantly more depression, anxiety, anger, fatigue and confusion than crews with core-periphery structures.
  • Patrick Marshall: Gu said that the team expects to have a prototype [S2OS’s software-defined hypervisor is being designed to centrally manage networking, storage and computing resources] ready in about three years that will be available as open-source software.
  • cobookman: I've been amazed that more people don't make use of googles preemtibles. Not only are they great for background batch compute. You can also use them for cutting your stateless webserver compute costs down. I've seen some people use k8s with a cluster of preemtibles and non preemtibles. 
  • @jeffsussna: Complex systems can’t be fully modeled. Failure becomes the only way to fully discover requirements. Thus the need to embrace it.
  • Jennifer Doudna: a genome’s size is not an accurate predictor of an organism’s complexity; the human genome is roughly the same length as a mouse or frog genome, about ten times smaller than the salamander genome, and more than one hundred times smaller than some plant genomes.
  • Daniel C. Dennett: In Darwin’s Dangerous Idea (1995), I argued that natural selection is an algorithmic process, a collection of sorting algorithms that are themselves composed of generate-and-test algorithms that exploit randomness (pseudo-randomness, chaos) in the generation phase, and some sort of mindless quality-control testing phase, with the winners advancing in the tournament by having more offspring.
  • Almir Mustafic: My team learned the DynamoDB limitations before we went to production and we spent time calculating things to properly provision RCUs and WCUs. We are running fine in production now and I hear that there will be automatic DynamoDB scaling soon. In the meantime, we have a custom Python script that scales our DynamoDB.


• I've written a novella: The Strange Trial of Ciri: The First Sentient AI. It explores the idea of how a sentient AI might arise as ripped from the headlines deep learning techniques are applied to large social networks. I try to be realistic with the technology. There's some hand waving, but I stay true to the programmers perspective on things. One of the big philosophical questions is how do you even know when an AI is sentient? What does sentience mean? So there's a trial to settle the matter. Maybe. The big question: would an AI accept the verdict of a human trial? Or would it fight for its life? When an AI becomes sentient what would it want to do with its life? Those are the tensions in the story. I consider it hard scifi, but if you like LitRPG there's a dash of that thrown in as well. Anyway, I like the story. If you do too please consider giving it a review on Amazon. Thanks for your support!


• Serving 39 Million Requests for $370/Month, or: How We Reduced Our Hosting Costs by Two Orders of Magnitude. Step 1: Just Go Serverless: Simply moving to a serverless environment had the single greatest impact on reducing hosting costs. Our extremely expensive operating costs immediately shrunk by two orders of magnitude. Step 2: Lower Your Memory Allocation: Remember, each time you halve your function’s memory allocation, you’re roughly halving your Lambda costs. Step 3: Cache Your API Gateway Responses: We pay around $14 a month for a 0.5GB API Gateway cache with a 1 hour TTL. In the last month, 52% (20.3MM out of 39MM) of our API requests were served from the cache, meaning less than half (18.7MM requests) required invoking our Lambda function. That $14 saves us around $240 a month in Lambda costs.

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Sponsored Post: Apple, Domino Data Lab, Etleap, Aerospike, Loupe, Clubhouse, Stream, Scalyr, VividCortex, MemSQL, InMemory.Net, Zohocorp

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• Apple is looking for passionate VoIP engineer with a strong technical background to transform our Voice platform to SIP. It will be an amazing journey with highly skilled, fast paced, and exciting team members. Lead and implement the engineering of Voice technologies in Apple’s Contact Center environment. The Contact Center Voice team provides the real time communication platform for customers’ interaction with Apple’s support and retail organizations. You will lead the global Voice, SIP, and network cross-functional engineers to develop world class customer experience. More details are available here.


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• www.site24x7.com : Monitor End User Experience from a global monitoring network. 


• Working on a software product? Clubhouse is a project management tool that helps software teams plan, build, and deploy their products with ease. Try it free today or learn why thousands of teams use Clubhouse as a Trello alternative or JIRA alternative.


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Stuff The Internet Says On Scalability For July 7th, 2017

Hey, it's HighScalability time:

What's real these days? I was at Lascaux II, an exact replica of Lascaux. I was deeply, deeply moved. Was this an authentic experience? A question we'll ask often in VR I think.

If you like this sort of Stuff then please support me on Patreon.

• $400k: cost of yearly fake news campaign; $50,000: cost to discredit a journalist; 100 Gbps: SSDP DDoS amplification attack; $5.97BN: wild guess on cost of running Facebook on AWS; 2 billion: Facebook users; 80%: Spotify backend services in production run as containers; $60B: AR market by 2021; 10.4%: AMD market share taken from Intel; 5 days: MIT drone flight time; $1 trillion: Apple iOS revenues; 35%-144%: reduction in image sizes; 10 petabytes: Ancestry.com data stored; 1 trillion: photos taken on iPhone each year; $70B: Apple App Store payout to developers; 355: pages in Internet Trends 2017 report; 14: people needed to make 500,000 tons of steel; 25%: reduced server-rendering time with Node 8; 50-70%: of messages Gmail receives are spam; 8,000: bugs found in pacemaker code; 


• Quotable Quotes:
  • Vladimir Putin: We must take into account the plans and directions of development of the armed forces of other countries… Our responses must be based on intellectual superiority, they will be asymmetric, and less expensive.
  • @swardley: What most fail to realise is that the Chinese corporate corpus has devoured western business thinking and gone beyond it.
  • @discostu105: I am a 10X developer. Everything I do takes ten times as long as I thought.
  • DINKDINK: You grossly underestimate the hashing capacity of the bitcoin network. The hashing capacity, at time of posting, is approximately 5,000,000,000 Gigahashes/second[1]. Spot measurement of the hashing capacity of an EC2 instance is 0.4 Gigahashes/second[2]. You would need 12 BILLION EC2 instances to 51% attack the bitcoin network.[3] Using EC2 to attack the network is impractical and inefficient.
  • danielsamuels && 19eightyfour~ Machiavelli's Guide to PaaS: Keep your friends close, and your competitors hosted.
  • Paul Buchheit:  I wrote the the first version of Gmail in a day!
  • @herminghaus: If you don’t care about latency, ship a 20ft intermodal container full of 32GB micro-SD cards across the globe. It’s a terabyte per second.
  • @cstross: Okay, so now the Russian defense industry is advertising war-in-a-can (multimodal freight containerized missiles):
  • Dennett~ you don't need comprehension to achieve competence.
  • @michellebrush~ Schema are APIs. @gwenshap #qconnyc
  • Stacy Mitchell: Amazon sells more clothing, electronics, toys, and books than any other company. Last year, Amazon captured nearly $1 of every $2 Americans spent online. As recently as 2015, most people looking to buy something online started at a search engine. Today, a majority go straight to Amazon.
  • Xcelerate: I have noticed that Azure does have a few powerful features that AWS and GCP lack, most notably InfiniBand (fast interconnects), which I have needed on more than one occasion for HPC tasks. In fact, 4x16 core instances on Azure are currently faster at performing molecular dynamics simulations than 1x"64 core" instance on GCP. But the cost is extremely high, and I still haven't found a good cloud platform for short, high intensity HPC tasks.
  • jjeaff: I took about 5 sites from a $50 a month shared cPanel plan that included a few WordPress blogs and some custom sites and put them on a $3 a month scaleway instance and haven't had a bit of trouble.
  • @discordianfish: GCP's Pub/Sub is really priced by GB? And 10GB/free/month? What's the catch?
  • Amazon: This moves beyond the current paradigm of typing search keywords in a box and navigating a website. Instead, discovery should be like talking with a friend who knows you, knows what you like, works with you at every step, and anticipates your needs. This is a vision where intelligence is everywhere. Every interaction should reflect who you are and what you like, and help you find what other people like you have already discovered. 
  • @CloudifySource: Lambda is always 100% busy - @adrianco #awasummit #telaviv #serverless
  • @codinghorror: Funny how Android sites have internalized this "only multi core scores now matter" narrative with 1/2 the CPU speed of iOS hardware
  • @sheeshee: deleted all home directories because no separation of "dev" & "production". almost ran a billion euro site into the ground with a bad loop.
  • We have quotes the likes of which even God has never seen! Please click through to ride all of them.


• The Not Hotdog app on Silicon Valley may be a bit silly, but the story of how they built the real app is one of the best how-tos on building a machine learning app you'll ever read. How HBO’s Silicon Valley built “Not Hotdog” with mobile TensorFlow, Keras & React Native. The initial app was built in a weekend using Google Cloud Platform’s Vision API, and React Native. The final version took months of refinement.  Google Cloud’s Vision API was dropped because its accuracy in recognizing hotdogs was only so-so; it was slow because of the network hit; it cost too much. They ended up using Keras, a deep learning library that provides nicer, easier-to-use abstractions on top of TensorFlow. They used on SqueezeNet due to its explicit positioning as a solution for embedded deep learning. SqueezeNet used only 1.25 million parameters which made training much faster and reduced resource usage on the device. What would they change? timanglade: Honestly I think the biggest gains would be to go back to a beefier, pre-trained architecture like Inception, and see if I can quantize it to a size that’s manageable, especially if paired with CoreML on device. You’d get the accuracy that comes from big models, but in a package that runs well on mobile. And this is really cool: The last production trick we used was to leverage CodePush and Apple’s relatively permissive terms of service, to live-inject new versions of our neural networks after submission to the app store. 


• And the winner is: all of us. Serverless Hosting Comparison: Lambda: Unicorn: $20,830.83. Heavy: $120.16. Medium: $4.55. Light: $0.00; Azure Functions: Unicorn: $19,993.60. Heavy: $115.40. Moderate: $3.60. Light: $0.00; Cloud Functions: Unicorn: $23,321.20. Heavy: $138.95. Moderate: $9.76. Light: $0.00; OpenWhisk: Unicorn: $21,243.20. Heavy: $120.70. Medium: $3.83. Light: $0.00; Fission.io: depends on the cost of running your managed Kubernetes cloud. 


• Minds are algorithms made physical. Seeds May Use Tiny “Brains” to Decide When to Germinate: The seed has two hormones: abscisic acid (ABA), which sends the signal to stay dormant, and gibberellin (GA), which initiates germination. The push and pull between those two hormones helps the seed determine just the right time to start growing...According to Ghose, some 3,000 to 4,000 cells make up the Arabidopsis seeds...It turned out that the hormones clustered in two sections of cells near the tip of the seed—a region the researchers propose make up the “brain.” The two clumps of cells produce the hormones which they send as signals between each other. When ABA, produced by one clump, is the dominate hormone in this decision center, the seed stays dormant. But as GA increases, the “brain” begins telling the seed it’s time to sprout...This splitting of the command center helps the seed make more accurate decisions.

Don't miss all that the Internet has to say on Scalability, click below and become eventually consistent with all scalability knowledge (which means this post has many more items to read so please keep on reading)...

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