A Patreon Architecture Short

Patreon recently snagged $30 Million in funding. It seems the model of pledging $1 for individual feature releases or code changes won't support fast enough growth. CEO Jack Conte says: We need to bring in so many people so fast. We need to keep up with hiring and keep up with making all of the things.

Since HighScalability is giving Patreon a try I've naturally wondered how it's built. Modulo some serious security issues Patreon has always worked well. So I was interested to dig up this nugget in a thread on the funding round where the Director of Engineering at Patreon shares a little about how Patreon works:

  • Server is in Python using Flask and SQLAlchemy, 
  • Runs on AWS (EC2, RDS (MySQL), and some Redis, Celery, SQS, etc. to boot). 
  • A few microservices here and there in other languages too (e.g. real time chat server with Node & Firebase)
  • Web code is written in React (with some legacy code in Angular). We tend to use Redux for the non-component pieces, but are still trying out new React-compatible libraries here and there.
  • iOS and Android code are written in Objective-C and Java, respectively. 
  • We use Realm on both platforms for data storage
  • Most of the rest is pretty standard modern project stuff (CocoaPods for iOS, Gradle on Android, etc.)

For this time period it seems like a good set of technologies to use for the type of application Patreon is. It's interesting to see Angular as referred to as legacy code. React seems to be winning the framework wars.

The use of Realm is notable on the mobile platform as a common storage layer. Realm's simplicity is attractive.

The use of microservices may have helped Patreon dodge the Parse closing down bullet. Instead of trying to find one backend to rule them all they picked Firebase, a more targeted technology, to implement a specific feature. Service diversification is a great way to manage service failure risk.


Stuff The Internet Says On Scalability For January 29th, 2016

Hey, it's HighScalability time:

This is a trace of a Google search query. A single query might touch a couple thousand machines.


If you like this Stuff then please consider supporting me on Patreon.
  • 88: the too short life of Marvin Minsky; $18.4 billion: profit made by Apple in 3 months; 100M: hours of video watched on Facebook each day; 1.59 billion: Facebook users; $115B: size of game market by 2020; 12 years: Mars rover still going strong; 96.3m: barrels of oil produced per day; 570 Billion: object brighter than the Sun; 134 pounds: carried by drones;  $2.4 billion: AWS Q4 sales; 2.5 million: advertisers on the Facebook;

  • Quotable Quotes:
    • @ptaoussanis: Real-world scaling 101: be in the habit of routinely, objectively asking what parts of your system could stand to be simplified or removed
    • @Carnage4Life: Azure revenue up 140%. Search revenue from #BingAds up 21%. Microsoft is killing it in the cloud
    • @gabriel_boya: Scaling up a Cloud Service on @azure takes so many hours that your customers may be gone by the time your instances are allocated...
    • AJ007: Facebook is the only platform that lets advertisers target a mass audience with very fine demographic precision. Google you lose the demographics. Television, you lose the the precision.
    • Junaid Anwar: It is to be noted that clustering [node.js] yielded two times the performance as compared to the non-clustering case which shows that performance linearly increases with processing cores when clustering is used.
    • crash41301: Our company has been slowly shrinking the hundreds of services we have down to a handful of larger, automated tested services and the dev team (about 50) likes it much more.
    • @swardley: Compute is the activity, Architecture is the practice
    • van lessen: Self-Contained Systems (SCS) describe an architectural approach to build software systems, e.g. to split monoliths into multiple functionally separated, yet largely autonomous web applications. 
    • R. P. Feynman: What is the cause of management's fantastic faith in the machinery?
    • Steven Max Patterson: Facebook filters much from the raw newstream and gives me what it thinks I want with about 20% accuracy.
    • Brandon Butterworth~ a single mega data centre might simply represent a single, large potential point of failure
    • boggzPit: Damn it Facebook. Why did I ever believe you could handle being cool to developers?
    • Vadim Tkachenko: To recap an interesting point in that post: when using 48 cores with the server, the result was worse than with 12 cores. I wanted to understand the reason is was true, so I started digging. My primary suspicion was that Java (I never trust Java) was not good dealing with 100GB of memory.
    • Seth Lloyd: Our algorithm shows that you don't need a big quantum computer to kick some serious topological butt...You could find the topology of simple structures on a very simple quantum computer. 
    • Robert Scoble: When he was doing his thesis 20 years ago, it took him two years to analyze just 24 hours of data from farms (he pulls in data from satellites, Doppler radar and even drones). Today, his company does the same thing in seconds.
    • @jgrahamc: Devotees of microservices use 'monolith' as a derogatory term; wait 10 years and we'll be using 'spider's web' as a derogatory term.
    • @mweagle: I see your femtoservice, and pivot with a single source code point: “yoctoservice” :) #disrupt #unicorn #M&A
    • milesrout: The entire point of Docker is that you use it for everything. It's a universal application image format. That is the point. It's contained, secure, and childproof. That is the point. It's not just about scalability. If I could use a desktop operating system where all programs ran as docker containers, I'd do that too. That's what they're for.
    • Bill Wash: I will never pass up an opportunity to help out a colleague, and I’ll remember the days before I knew everything.
    • @CarlHasselskog:  my startup handles ~10 million uploaded files/day with two employees in total (entire company). That's largely thanks to you guys.
    • AJ Kohn: December saw more negative numbers with a 6.96% decrease, year over year, in desktop search volume. Every month in 2015 had lower desktop query volume than the same month in 2014. Every. Month.
    • Jerry Chen: Every startup has a different size unit of value. Bigger is not better, smaller is not better.
    • sacundim: No, the goal of normalization is to eliminate logical inconsistencies—data sets that entail two or more different answers to the same question. 
    • Jake Archibald: Streams can be used to do fun things like turn clouds to butts, transcode MPEG to GIF, but most importantly, they can be combined with service workers to become the fastest way to serve content.
    • Solomon Hykes: Computers do run only one unikernel at a time. It’s just that sometimes they are virtual computers. Remember that virtualization is increasingly hardware-assisted, and the software parts are mature. So for many use cases it’s reasonable to separate concerns and just assume that VMs are just a special type of computer.

  • Relying on a tool backed by a big company is no protection. Facebook is closing down Parse. This is a stunner because Parse was a popular and well made service, used by millions of now adrift mobile apps. What happened? This might be it: "Facebook also would have had to invest untold millions of dollars in capital and, more importantly, engineering talent, to get the Parse business fully off the ground to have a better chance at making a dent in competitors like Amazon, Microsoft and Google." How about Firebase? The Firebase founder responds: "We're not going anywhere. What makes us different? Firebase is very complementary to Google's other product offerings. Cloud for one, as well as Angular, Polymer, GCM, etc." The moral of the store is told by bsaul: "parse wasn't a core service for facebook, nor a relevant source of a revenue AND their API wasn't standard. Those points combined made it very risky for people to use it." 

  • The Internet will soon be eating a lot of Brotli, Google's new lossless compression algorithm that is making the Internet 17-25% faster. Support will be in Chrome and other browsers, but server side support may take longer. Why does it only work with https? Richard Coles: one reason why this is limited to https is to stop it being mangled by proxies, which has been a practical problem in the past with encodings.

  • Young Skynet is continuing its dastardly plan of self-creation by seeding deep learning both far and wide. Microsoft Open Sources Deep Learning, AI Toolkit On GitHub. Twitter released Distributed learning in TorchTeach Yourself Deep Learning with TensorFlow and Udacity.

  • While the Super Bowl will make a mess of local traffic, it's great for cell phone service. Verizon spent $70 million to triple Bay Area LTE capacity ahead of the Super Bowl. They have more than tripled its 4G LTE network capacity; Build 16 new area cell sites; Install 75 small cells; Boost capacity by adding 37 XLTE to existing sites; Complete preparations to deploy 14 mobile cell sites in high traffic locations.

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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Tinder: How does one of the largest recommendation engines decide who you'll see next?

We've heard a lot about the Netflix recommendation algorithm for movies, how Amazon matches you with stuff, and Google's infamous PageRank for search. How about Tinder? It turns out Tinder has a surprisingly thoughtful recommendation system for matching people.

This is from an extensive profile, Mr. (Swipe) Right?, on Tinder founder Sean Rad:

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Design of a Modern Cache

This is a guest post by Benjamin Manes, who did engineery things for Google and is now doing engineery things for a new load documentation startup, LoadDocs.

Caching is a common approach for improving performance, yet most implementations use strictly classical techniques. In this article we will explore the modern methods used by Caffeine, an open-source Java caching library, that yield high hit rates and excellent concurrency. These ideas can be translated to your favorite language and hopefully some readers will be inspired to do just that.

Eviction Policy

A cache’s eviction policy tries to predict which entries are most likely to be used again in the near future, thereby maximizing the hit ratio. The Least Recently Used (LRU) policy is perhaps the most popular due to its simplicity, good runtime performance, and a decent hit rate in common workloads. Its ability to predict the future is limited to the history of the entries residing in the cache, preferring to give the last access the highest priority by guessing that it is the most likely to be reused again soon...

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Stuff The Internet Says On Scalability For January 22nd, 2016

Hey, it's HighScalability time:

The Imaginary Kingdom of Aurullia. A completely computer generated fractal. Stunning and unnerving.


If you like this Stuff then please consider supporting me on Patreon.
  • 42,000: drones from China securing the South China Sea; 1 billion: WhatsApp active users; 2⁻¹²²: odds of a two GUIDs with 122 random bits colliding; 25,000 to 70,000: memory chip errors per billion hours per megabit; 81,500: calories in a human body; 62: people as wealthy as half of world's population; 1.66 million: App Economy jobs in the US; 521 years: half-life of DNA; 0.000012%: air passenger fatalities; $1B: Microsoft free cloud resources for nonprofits; 4000-7000+: BBC stats collected per second; $1 billion: Google's cost to taste Apple's pie;

  • Quotable Quotes:
    • @mcclure111: 1995: Every object in your home has a clock & it is blinking 12:00 / 2025: Every object in your home has a IP address & the password is Admin
    • @notch: Coming soon to npm: tirefire.js, an asynchronous framework for implementing helper classes for reinventing the wheel. Based on promises.
    • @ayetempleton: Fun fact: You are MORE likely to win a million or more dollars in the #powerball lottery than to lose an #AWS #S3 object in a given year.
    • @viktorklang: IMO biggest lie in performance work: constant factors don't matter in Big-Oh.
    • Flavien Boucher: We all came to the conclusion that Docker is adding a complexity layer compare to a virtual machine approach, and this complexity will be for the deployment, development and build.
    • @Frances_Coppola: Uber is a cab cartel. And AirBNB is wealthy - though its suppliers aren't. They are simply firms with apps.
    • Susan Sontag: The method especially appeals to people handicapped by a ruthless work ethic – Germans, Japanese and Americans. Using a camera appeases the anxiety which the work driven feel about not working when they are on vacation and supposed to be having fun. They have something to do that is like a friendly imitation of work: they can take pictures.
    • @SachaNauta: "It's never been easier to be a billionaire and never been harder to be a millionaire" @profgalloway #DLD16
    • @Techmeme: Google Play saw 100% more downloads than iOS App Store, but Apple generated 75% more revenue 
    • Ryan Shea: we’ve concluded that 8MB blocks are simply too large to be considered safe for the network at this point in time, considering the current global bandwidth levels.
    • @RichRogersHDS: "In the old world you spent 30% of your time building a great service & 70% shouting about it. In the new world, that inverts." - Jeff Bezos
    • @thetinot: When you have an SDN, yes, networking throughput does grow on trees. Why @googlecloud is faster than #AWS and #Azure 
    • @GOettingerEU: Digital tech has contributed to around 1/3 of EU GDP growth in over the past decade and I believe this number will continue to grow #wef16
    • @COLRICHARDKEMP: More women fly F16s in Israel than drive cars in Saudi Arabia. KA. 
    • @JoshZumbrun: The total collapse in shopping mall construction
    • @jeffjarvis: 44 million people saw NY Fashion Show content on Instagram last year says Instagram's Marne Levine. Attn: Conde & Hearst!  #DLD16
    • @HackerNewsOnion: Developer Accused Of Unreadable Code Refuses To Comment
    • Lloyds online banking: in a 60-second period: 12,900 people visit its website, 400 bills are paid, 1,500 customers log onto the mobile app, 350 transfers are made and 3,000+ logins
    • @bdha: 2013: DevOps 2014: Docker 2015: Containers 2016: Unikernels 2017: Threads 2018: Syscalls 2019: Inodes
    • hacknat: Two things need to happen to make unikernels attractive. A new Hypervisor needs to get made, one that is just as extensible as an OS around the isolated primitives. It should also have something extra too (like the ability to fine tune resource management better than an OS can). Secondly a user friendly mechanism like Docker needs to happen.

  • It's a winner take all world, but not everywhere. Brian Brushwood on Cordkillers with an insightful breakdown of how the new diversified market for TV content has actually become far less of a winner take all system. We have more good content than ever. Gone are the days of Mash when everyone watched the same show at the same time. Is it bad that actors are making less? No. We are seeing the destruction of the tournament, as explained in the book Freakonomics, is the idea that those at the very top make all the money, those at the bottom of the pyramid make next to nothing. And the winners only have to win by a nose to reap all the rewards, the don't even need to win on merit. This is an inefficient system. Now we are reaching an artistically efficient system. If you have a story to tell and no budget you can tell it on YouTube. This is the democratization of talent. It's inconvenient for those who used to be at the top. What we have now is more working actors producing more content than ever.  And since a lot of this content does not have to pander to advertisers to get made the content is more diverse and more interesting than ever as well.

  • The RAMCloud Storage System: RAMCloud combines low-latency, large scale, and durability. Using state of the art networking with kernel bypass, RAMCloud expects small reads to complete in less that 10µs on a cluster of 10,000 nodes. This is 50 – 1,000 times faster that storage systems commonly in use.

  • All Change Please. Adrian Colyer makes the case that we are transitioning to a new part of the technology cycle that promises great change. Networking: 40Gbps and 100Gbps ethernet. Memory: battery backed RAM; 3D XPoint, MRAM, MeRAM, etc. Storage: NVRAM and fast PCIe. Processing: GPUs; integrated on processor FPGAs; hardware transactional memory. This is the question: What happens when you combine fast RDMA networks with ample persistent memory, hardware transactions, enhanced cache management support and super-fast storage arrays? It’s a whole new set of design trade-offs that will impact the OS, file systems, data stores, stream processing, graph processing, deep learning and more. And this is before we’ve even introduced integration with on-board FPGAs, and advances in GPUs…

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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Why does Unikernel Systems Joining Docker Make A Lot of Sense?

Unikernel Systems Joins Docker. Now this is an interesting match. The themes are security and low overhead, though they do seem to solve the same sort of problem.

So, what's going on?

In FLOSS WEEKLY 302 Open Mirage, starting at about 10 minutes in, there are a series of possible clues. Dr. Anil Madhavapeddy, former CTO of Unikernel Systems, explains their motivation behind the creation of unikernels. And it's a huge and exciting vision...

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Building An Infinitely Scaleable Online Recording Campaign For David Guetta

This is a guest repost of an interview posted by Ryan S. Brown that originally appeared on It continues our exploration of building systems on top of Lambda.

Paging David Guetta fans: this week we have an interview with the team that built the site behind his latest ad campaign. On the site, fans can record themselves singing along to his single, “This One’s For You” and build an album cover to go with it.

Under the hood, the site is built on Lambda, API Gateway, and CloudFront. Social campaigns tend to be pretty spiky – when there’s a lot of press a stampede of users can bring infrastructure to a crawl if you’re not ready for it. The team at chose Lambda because there are no long-lived servers, and they could offload all the work of scaling their app up and down with demand to Amazon.

James Hall from is going to tell us how they built an internationalized app that can handle any level of demand from nothing in just six weeks.

The Interview

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Sponsored Post: Netflix, Macmillan, Aerospike, TrueSight Pulse, LaunchDarkly, Robinhood,, Redis Labs, InMemory.Net, VividCortex, MemSQL, Scalyr, AiScaler, AppDynamics, ManageEngine, Site24x7

Who's Hiring?

  • Manager - Site Reliability Engineering: Lead and grow the the front door SRE team in charge of keeping Netflix up and running. You are an expert of operational best practices and can work with stakeholders to positively move the needle on availability. Find details on the position here:

  • Macmillan Learning, a premier e-learning institute, is looking for VP of DevOps to manage the DevOps teams based in New York and Austin. This is a very exciting team as the company is committed to fully transitioning to the Cloud, using a DevOps approach, with focus on CI/CD, and using technologies like Chef/Puppet/Docker, etc. Please apply here.

  • DevOps Engineer at Robinhood. We are looking for an Operations Engineer to take responsibility for our development and production environments deployed across multiple AWS regions. Top candidates will have several years experience as a Systems Administrator, Ops Engineer, or SRE at a massive scale. Please apply here.

  • Senior Service Reliability Engineer (SRE): Drive improvements to help reduce both time-to-detect and time-to-resolve while concurrently improving availability through service team engagement.  Ability to analyze and triage production issues on a web-scale system a plus. Find details on the position here:

  • Manager - Performance Engineering: Lead the world-class performance team in charge of both optimizing the Netflix cloud stack and developing the performance observability capabilities which 3rd party vendors fail to provide.  Expert on both systems and web-scale application stack performance optimization. Find details on the position here

  • Senior Devops Engineer - is looking for a senior devops engineer to help us in making the internet more transparent around downtime. Your mission: help us create a fast, scalable infrastructure that can be deployed to quickly and reliably.

  • Software Engineer (DevOps). You are one of those rare engineers who loves to tinker with distributed systems at high scale. You know how to build these from scratch, and how to take a system that has reached a scalability limit and break through that barrier to new heights. You are a hands on doer, a code doctor, who loves to get something done the right way. You love designing clean APIs, data models, code structures and system architectures, but retain the humility to learn from others who see things differently. Apply to AppDynamics

  • Software Engineer (C++). You will be responsible for building everything from proof-of-concepts and usability prototypes to deployment- quality code. You should have at least 1+ years of experience developing C++ libraries and APIs, and be comfortable with daily code submissions, delivering projects in short time frames, multi-tasking, handling interrupts, and collaborating with team members. Apply to AppDynamics

Fun and Informative Events

  • Aerospike, the high-performance NoSQL database, hosts a 1-hour live webinar on January 28 at 1PM PST / 4 PM EST on the topic of "From Development to Deployment" with Docker and Aerospike. This session will cover what Docker is and why it's important to Developers, Admins and DevOps when using Aerospike; it features an interactive demo showcasing the core Docker components and explaining how Aerospike makes developing & deploying multi-container applications simpler. Please click here to register.

  • Your event could be here. How cool is that?

Cool Products and Services

  • Dev teams are using LaunchDarkly’s Feature Flags as a Service to get unprecedented control over feature launches. LaunchDarkly allows you to cleanly separate code deployment from rollout. We make it super easy to enable functionality for whoever you want, whenever you want. See how it works.

  • TrueSight Pulse is SaaS IT performance monitoring with one-second resolution, visualization and alerting. Monitor on-prem, cloud, VMs and containers with custom dashboards and alert on any metric. Start your free trial with no code or credit card.

  • Turn chaotic logs and metrics into actionable data. Scalyr is a tool your entire team will love. Get visibility into your production issues without juggling multiple tools and tabs. Loved and used by teams at Codecademy, ReturnPath, and InsideSales. Learn more today or see why Scalyr is a great alternative to Splunk.

  • InMemory.Net provides a Dot Net native in memory database for analysing large amounts of data. It runs natively on .Net, and provides a native .Net, COM & ODBC apis for integration. It also has an easy to use language for importing data, and supports standard SQL for querying data. http://InMemory.Net

  • VividCortex measures your database servers’ work (queries), not just global counters. If you’re not monitoring query performance at a deep level, you’re missing opportunities to boost availability, turbocharge performance, ship better code faster, and ultimately delight more customers. VividCortex is a next-generation SaaS platform that helps you find and eliminate database performance problems at scale.

  • MemSQL provides a distributed in-memory database for high value data. It's designed to handle extreme data ingest and store the data for real-time, streaming and historical analysis using SQL. MemSQL also cost effectively supports both application and ad-hoc queries concurrently across all data. Start a free 30 day trial here:

  • aiScaler, aiProtect, aiMobile Application Delivery Controller with integrated Dynamic Site Acceleration, Denial of Service Protection and Mobile Content Management. Also available on Amazon Web Services. Free instant trial, 2 hours of FREE deployment support, no sign-up required.

  • ManageEngine Applications Manager : Monitor physical, virtual and Cloud Applications.

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

If any of these items interest you there's a full description of each sponsor below...

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Use Google For Throughput, Amazon And Azure For Low Latency

Which cloud should you use? It may depend on what you need to do with it. What Zach Bjornson needs to do is process large amounts scientific data as fast as possible, which means reading data into memory as fast as possible. So, he made benchmark using Google's new multi-cloud PerfKitBenchmarker, to figure out which cloud was best for the job.

The results are in a very detailed article: AWS S3 vs Google Cloud vs Azure: Cloud Storage Performance. Feel free to datamine the results for more insights, but overall his conclusions are:

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Stuff The Internet Says On Scalability For January 15th, 2016

Hey, it's HighScalability time:

Space walk from 2001: A Space Odyssey? Nope. A base jump from the CN Tower in Toronto.


If you like this Stuff then please consider supporting me on Patreon.
  • 13.5TB: open data from Yahoo for machine learning; 1+ exabytes: data stored in the cloud; 13: reasons autonomous cars should have steering wheels; 3,000: kilowatt-hours of energy generated by the solar bike path; 10TB: helium-filled hard disk; $224 Billion: 2016 gadget spending in US; 85: free ebooks; 17%: Azure price drop on some VMs; 20.5: tons of explosives detonated on Mythbusters; 20 Billion: Apple’s App Store Sales; 70%: Global Internet traffic goes through Northern Virginia; 12: photos showing the beauty of symmetry; 

  • Quotable Quote:
    • @WhatTheFFacts: Scaling Earth's 'life' to 46 years, the industrial revolution began 1 minute ago -- In that time we've destroyed half the world's forests.
    • David Brin: The apotheosis of Darth Vader was truly disgusting. Saving one demigod—a good demigod, his son—wiped away all his guilt from slaughtering billions of normal people.
    • Brian Brazil: In today’s world, having a 1:1 coupling between machines and services is becoming less common. We no longer have the webserver machine, we have one machine which hosts one part of the webserver service. 
    • @iamxavier: "Snapchat is said to have 7 billion mobile video views vs Facebook’s 8 bil.The kicker: Fb has 15x Snapchat’s users."
    • Charlie Stross: Do you want to know the real reason George R. R. Martin's next book is late? it's because keeping track of that much complexity and so many characters and situations is hard work, and he's not getting any younger. 
    • @raju: Unicorn-Size Losses: @Uber lost $671.4 million in 2014 & $987.2 million in the first half of 2015
    • @ValaAfshar: 3.8 trillion photos were taken in all of human history until mid-2011. 1 trillion photos were taken in 2015 alone
    • @ascendantlogic: 2010: Rewrite all the ruby apps with javascript 2012: Rewrite all the javascript apps with Go 2014: Rewrite all the Go apps with Rust
    • @kylebrussell: “Virtual reality was tried in the 90s!” Yeah, with screens that had 7.9% of the Oculus Rift CV1 resolution
    • @kevinmarks: #socosy2016 @BobMankoff: people don't like novelty - they like a little novelty in a cocoon of familiarity, that they could have thought of
    • @toddhoffious: The problem nature has solved is efficient variable length headers. Silicon doesn't like them for networks, or messaging protocols. DNA FTW.
    • @jaykreps: I'm loving the price war between cloud providers, cheap compute enables pretty much everything else in technology. 
    • The Confidence Game: Transition is the confidence game’s great ally, because transition breeds uncertainty. There’s nothing a con artist likes better than exploiting the sense of unease we feel when it appears that the world as we know it is about to change.
    • @somic: will 2016 be the year of customer-defined allocation strategies for aws spot fleet? (for example, through a call to aws lambda)
    • beachstartup: i run an infrastructure startup. the rule of thumb is once you hit $20-99k/month, you can cut your AWS bill in half somewhere else. sites in this phase generally only use about 20% of the features of aws.
    • @fart: the most important part of DevOps to me is “kissing the data elf”
    • @destroytoday: In comparison, @ProductHunt drove 1/4 the traffic of Hacker News, but brought in 700+ new users compared to only 20 from HN.
    • @aphyr~ Man, if people knew even a *tenth* of the f*cked up shit tech company execs have tried to pull... Folks are *awfully* polite on twitter.
    • @eric_analytics: It took Uber five years to get to a billion rides, and its Chinese rival just did it in one
    • lowpro: Being a 19 year old college student with many friends in high school, I can say snapchat is the most popular social network, followed by Instagram then Twitter, and lastly Facebook. If something is happening, people will snap and tweet about it, Instagram and Facebook are reserved for bigger events that are worth mentioning, snapchat and Twitter are for more day to day activities and therefore get used much more often.
    • Thaddeus Metz: The good, the true, and the beautiful give meaning to life when we transcend our animal nature by using our rational nature to realize states of affairs that would be appreciated from a universal perspective.
    • Reed Hastings: We realized we learned best by getting in the market and then learning, even if we’re less than perfect. Brazil is the best example. We started [there] four years ago. At first it was very slow growth, but because we were in the market talking to our members who had issues with the service, we could get those things fixed, and we learned faster.

  • Why has Bitcoin failed? From Mike Hearn: it has failed because the community has failed. What was meant to be a new, decentralised form of money that lacked “systemically important institutions” and “too big to fail” has become something even worse: a system completely controlled by just a handful of people. Worse still, the network is on the brink of technical collapse. The mechanisms that should have prevented this outcome have broken down, and as a result there’s no longer much reason to think Bitcoin can actually be better than the existing financial system.

  • Lessons learned on the path to production. From Docker CEO: 1) IaaS is too low; 2) PaaS is too high: Devs do not adopt locked down platforms; 3) End to end matters: Devs care about deployment, ops cares about app lifecycle and origin; 4) Build management, orchestration, & more in a way that enables portability; 5) Build for resilience, not zero defects; 6) If you do 5 right, agility + control

  • Is this the Tesla of database systems? No Compromises: Distributed Transactions with Consistency, Availability, and Performance: FaRMville transactions are processed by FaRM – the Fast Remote Memory system that we first looked at last year. A 90 machine FaRM cluster achieved 4.5 million TPC-C ‘new order’ transactions per second with a 99th percentile latency of 1.9ms. If you’re prepared to run at ‘only’ 4M tps, you can cut that latency in half. Oh, and it can recover from failure in about 60ms. 

  • Uber tells the story behind the design and implementation of their scalable datastore using MySQL. Uber took that path of many others in writing an entire layer on top of MySQL to create the database that best fits their use case. Uber wanted: to be able to linearly add capacity by adding more servers; write availability; a way of notifying downstream dependencies; secondary indexes; operation trust in the system, as it contains mission-critical trip data. They looked at Cassandra, Riak, and MongoDB, etc. Features alone did not decide their choice. What did?: "the decision ultimately came down to operational trust in the system we’d use."  If you are Uber this is a good reason that may not seem as important to those without accountability. Uber's design is inspired by Friendfeed, and the focus on the operational side inspired by Pinterest.

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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