How Uber Scales Their Real-time Market Platform

Reportedly Uber has grown an astonishing 38 times bigger in just four years. Now, for what I think is the first time, Matt Ranney, Chief Systems Architect at Uber, in a very interesting and detailed talk--Scaling Uber's Real-time Market Platform---tells us a lot about how Uber’s software works.

If you are interested in Surge pricing, that’s not covered in the talk. We do learn about Uber’s dispatch system, how they implement geospatial indexing, how they scale their system, how they implement high availability, and how they handle failure, including the surprising way they handle datacenter failures using driver phones as an external distributed storage system for recovery.

The overall impression of the talk is one of very rapid growth. Many of the architectural choices they’ve made are a consequence of growing so fast and trying to empower recently assembled teams to move as quickly as possible. A lot of technology has been used on the backend because their major goal has been for teams to get the engineering velocity as high as possible.

After a understandably chaotic (and very successful) start it seems Uber has learned a lot about their business and what they really need to succeed. Their early dispatch system was a typical just make it work type affair that assumed at a deep level it was moving only people. Now that Uber’s mission has grown to handle boxes and groceries as well as people, their dispatch system has been abstracted and put on very solid and smart architectural foundation.

Though Matt thinks their architecture might be a little crazy, the idea of using a consistent hash ring with a gossip protocol seems spot on for their use case.

It’s hard not to be captivated for Matt’s genuine enthusiasm for what he’s working on. When talking about DISCO, their dispatch system, he says in an excited tone that it’s like the traveling salesman problem from school. It’s a cool Computer Science thing. Even though the solution isn’t optimal, it’s the traveling salesman at an interesting scale, in real-time, in the real-world, built out of fault tolerant scalable components. How cool is that?

So let’s see how Uber works on the inside. Here’s my gloss on Matt’s talk:


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Stuff The Internet Says On Scalability For September 11th, 2015

Hey, it's HighScalability time:

Need a challenge? Solve the code on this 17.5 feet tall 11,000 year old wooden statue!

  • $100 million: amount Popcorn could have made from criminal business offers; 3.2-gigapixel: World’s Most Powerful Digital Camera; $17.3 trillion: US GDP in 2014;  700 million: Facebook time series database data points added per minute; 300PB: Facebook data stored in Hive; 5,000: Airbnb EC2 instances.

  • Quotable Quotes:
    • @jimmydivvy: NASA: Decade long flight across the solar system. Arrives within 72 seconds of predicted. No errors. Me: undefined is not a function
    • Packet Pushers~ Everyone has IOPS now. We are heading towards invisible consumption being the big deal going forward. 
    • Randy Medlin: Gonna drop $1000+ on a giant iPad, $100 on a stylus, then whine endlessly about $4.99 drawing apps.
    • Anonymous: Circuit Breaker + Real-time Monitoring + Recovery = Resiliency
    • Astrid Atkinson: I used to get paged awake at two in the morning. You go from zero to Google is down. That’s a lot to wake up to.
    • Todd Waters~ In 1979, 200MB weighed 30 lbs and took up the space of a washing machine
    • Todd Waters~ CERN spends more compute power throwing away data than storing and analyzing it
    • Rob Story:  We've clearly reached the point where SSD/RAM bandwidth have completely outpaced CPU compute.
    • Shedding light on the era of 'dark silicon': We will soon live in an era where perhaps more than 80 per cent of computer processors' transistors must be powered off  and 'remain dark' at any time to prevent the chip from overheating.
    • @diogomonica: In a container world, when someone asks about A vs B, the answer is always, A on top of B. #softwarecircus
    • Mike Curtis (Airbnb)~ 70 percent of the people who put space up for rent on Airbnb in New York City say they do so because if they didn’t, they would lose their apartments or homes
    • Mike Curtis (Airbnb)~ it would probably be on the order of 20 percent to 30 percent more expensive to operate its own datacenters than rent capacity on AWS 
    • @cloud_opinion: If John McAfee gets elected as President once, it will be impossible to uninstall him.
    • @bradurani: The greatest trick the ORM ever pulled was convincing the world the DB doesn't exist... and it's a disaster for a generation of devs
    • @coderoshi: The idea that management is the higher rung of a programmer's career ladder is like thinking that every actor wants to become a director.
    • @HiddenBrain: MT @CBinsights: A million guys walk into a Silicon Valley bar. No one buys anything. Bar is declared a massive success.
    • @Carnage4Life: Every time a developer says "temporary workaround" I remember this list. 

  • Some impressive gains by migrating from Python to Go. From Python to Go: migrating our entire API: reducing the mean response time of an API call from 100ms to 10ms...We reduced the number of EC2 instances required by 85%...we can now ship a self-hosted version of Repustate that is identical to the one we host for customers.

  • Rob Story has an awesome summary of the goings on at the Very Large DataBases Conference. His main gloss is at VLDB 2015: Concurrency, DataFlow, E-Store, but he also has a day by day summaries up on github. An amazing job and lots of concentrated insight.

  • Really wonderful article. A Life in Games: The Playful Genius of John Conway. Packed with slices of life that make me feel like I would like a little more John Conway in my life.

  • Need high availability? Here's how eBay uses Netflix Hystrix to implement the Circuit Breaker pattern. An example is given for their Secure Token service. Hystrix: a latency and fault tolerance library designed to isolate points of access to remote systems, services and 3rd party libraries, stop cascading failure and enable resilience in complex distributed systems where failure is inevitable.

  • Rob Pike and Naitik Shah are speaking at the Fall Gopherfest - Silicon Valley on November 18th. It's free and you might find it useful. 

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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Trade Stimulators and the Very Old Idea of Increasing User Engagement 

Very early in my web career I was introduced to the almost mystical holy grail of web (and now app) properties: increasing user engagement.

The reason is simple. The more time people spend with your property the more stuff you can sell them. The more stuff you can sell the more value you have. Your time is money. So we design for addiction.

Famously Facebook, through the ties that bind, is the engagement leader with U.S. adults spending a stunning average of 42.1 minutes per day on Facebook. Cha-ching.

Immense resources are spent trying to make websites and apps sticky. Psychological tricks and gamification strategies are deployed with abandon to get you not to leave a website or to keep playing an app.

It turns out this is a very old idea. Casinos are designed to keep you gambling, for example. And though I’d never really thought about it before, I shouldn’t have been surprised to learn retail stores of yore used devices called trade stimulators to keep customers hanging around and spending money.

Never heard of trade stimulators? I hadn’t either until, while watching American Pickers, one of my favorite shows, they talked about this whole category of things people collect that I had no idea even existed!

Here’s an explanation of trade stimulators on the For Amusement Only EM and Bingo Pinball podcast. They are small gambling devices used in stores and bars. Usually it was a mini slot machine or game of chance, like a horse racing game or a dice game. It would vend you a small trinket like a particular color gum ball that could be turned into the shop keeper for a free drink or other prize. The idea is you put money in and you keep spending money at the establishment. 

Here’s a beautiful Sun Mfg 2 Wheel Bicycle Trade Stimulator from the late 1800s. The wheels spin and when the wheels stop spinning you add up the numbers by the indicators to learn what prize you've won. It could be a cigar or a drink, for example.


Sun Mfg 2 Wheel Bicycle Trade Stimulator.jpg


Here’s a Stephens Magic Beer Barrel Trade Stimulator from around 1934. Your prize is a beer. Even if you didn’t win a beer you would get a pretzel, which would of course make you thirsty so you want more beer!

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Want IoT? Here's How a Major US Utility Collects Power Data from Over 5.5 Million Meters

I serendipitously found this fascinating reply by Richard Farley, your friendly neighborhood meter reader, in a local email list giving a rare first-hand account of how the Advanced Metering Infrastructure works in California. This is real Internet of Things territory. So if it doesn't have a typical post structure that is why. He generously allowed it to be reposted with a few redactions. When you see “A Major US Utility”, please replace it with the most likely California power company.

Old mechanical meters had bearings that over time wore out and caused friction that threw off readings. That friction would cause the analog gauge to spin slower than it should, resulting in lower readings than actual usage -- hence "free power". It's like a clock falling behind over time as the gears wear down.

For A Major US Utility "estimated billing" happens when your meter, for whatever reason, was not able to be read. The algorithms approved by the CPUC and are almost always favorable to the consumer. A Major US Utility hates to have to do estimated billing because they almost always have to underestimate based on the algorithms and CPUC rules. Not 100% sure about this, but if they underestimate, they have to eat the cost. In the rare case they overestimate (i.e., you were on vacation during the missed period), you will get "trued up" in the next billing cycle.

A Major US Utility does not see your actual use in "real time". For those interested in the nuts and bolts, here's how A Major US Utility’s AMI system works (AMI is short for Advanced Metering Infrastructure):

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Stuff The Internet Says On Scalability For September 4th, 2015

Hey, it's HighScalability time:

An astonishing 300 billion stars in our galaxy have planets. Take a look in the Eyes on Exoplanets app.
  • 1 billion: people who used Facebook in a single day; 2.8 million: sq. ft. in new Apple campus (with drone pics);  1.1 trillion: Apache Kafka messages per day; 2,000 years: age of termite mounds in Central Africa; 30: # of times better the human brain is better than the best supercomputers; 4 billion: requests it took to trigger an underflow bug.

  • Quotable Quotes:
    • Sara Seager: If an Earth 2.0 exists, we have the capability to find and identify it by the 2020s.
    • Android Dick: But you’re my friend, and I’ll remember my friends, and I’ll be good to you. So don’t worry, even if I evolve into Terminator, I’ll still be nice to you. I’ll keep you warm and safe in my people zoo, where I can watch you for ol’ times sake.
    • @viktorklang: "If the conversation is typically “scale out” versus “scale up” if we’re coordination-free, we get to choose “scale out” while “scaling up.”
    • Amir Najmi: At Google, data scientists are just too much in demand. Thus, anytime we can replace data scientist thinking with machine thinking, we consider it a win.
    • @solarce: "don’t be be content that the software seems to basically work — you must beat the hell out of it" -- @bcantrill
    • John Ralston Saul: I have enormous confidence in the individual as citizen. I don't think there is any proof in our 2,500 years of history that the elites do a good job without the close involvement of the citizenry.
    • Joshua Strebel: on average Aurora RDS is 3x faster than MySql RDS when used with WordPress.
    • Martin Thompson: I'd argue that "state of the art" in scalable design is to have no contention. It does not matter if you manage contention with locks or CAS techniques. Once you have contention then Universal Scalability Law kicks in as you have to face the contention and coherence penalty that contented access to shared state/resources brings. Multiple writers to shared state is a major limitation to the scalability of any design. Persistent data structures make this problem worse and not better due to path-copy semantics that is amplified by the richness of the domain model.

  • Mike Hearn in a great interview on a16z, Hard Forks, Hard Choices for Bitcoin, had much to say on the future scalability of Bitcoin. One of the key ideas is that many of the things that people love about Bitcoin are based on Bitcoin's decentralized nature. Characteristics like it is permissionless, that it's the new gold, that it doesn't have a centralized policy committee, that it's a global network, and that it's a platform you can innovate on top of. One of the challenges with the keeping the current block size is that decentralization is already under stress. A certain amount of centralization has crept with ever bigger and bigger miners. With the collaboration of three or four companies they could start to apply some policy influence to Bitcoin and that would erode all the interesting properties that people love about Bitcoin. The challenge is to scale Bitcoin in balance with decentralization. Scaling and security as encapsulated by decentralization are tradeoffs. You can scale massively and lose decentralization and which point Bitcoin becomes Paypal. Yet if you keep the block size the same you make it so Bitcoin can't be used by a world wide audience. 

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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How Agari Uses Airbnb's Airflow as a Smarter Cron

This is a guest repost by Siddharth Anand, Data Architect at Agari, on Airbnb's open source project Airflow, a workflow scheduler for data pipelines. Some think Airflow has a superior approach.

Workflow schedulers are systems that are responsbile for the periodic execution of workflows in a reliable and scalable manner. Workflow schedulers are pervasive - for instance, any company that has a data warehouse, a specialized database typically used for reporting, uses a workflow scheduler to coordinate nightly data loads into the data warehouse. Of more interest to companies like Agari is the use of workflow schedulers to reliably execute complex and business-critical "big" data science workloads! Agari, an email security company that tackles the problem of phishing, is increasingly leveraging data science, machine learning, and big data practices typically seen in data-driven companies like LinkedIn, Google, and Facebook in order to meet the demands of burgeoning data and dynamicism around modeling.

In a previous post, I described how we leverage AWS to build a scalable data pipeline at Agari. In this post, I discuss our need for a workflow scheduler in order to improve the reliablity of our data pipelines, providing the previous post's pipeline as a working example.

Scheduling Workflows @ Agari - A Smarter Cron

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Building Globally Distributed, Mission Critical Applications: Lessons From the Trenches Part 2

This is Part 2 of a guest post by Kris Beevers, founder and CEO, NSONE, a purveyor of a next-gen intelligent DNS and traffic management platform. Here's Part 1.

Integration and functional testing is crucial

Unit testing is hammered home in every modern software development class.  It’s good practice. Whether you’re doing test-driven development or just banging out code, without unit tests you can’t be sure a piece of code will do what it’s supposed to unless you test it carefully, and ensure those tests keep passing as your code evolves.

In a distributed application, your systems will break even if you have the world’s best unit testing coverage. Unit testing is not enough.

You need to test the interactions between your subsystems. What if a particular piece of configuration data changes – how does that impact Subsystem A’s communication with Subsystem B? What if you changed a message format – do all the subsystems generating and handling those messages continue to talk with each other? Does a particular kind of request that depends on results from four different backend subsystems still result in a correct response after your latest code changes?

Unit tests don’t answer these questions, but integration tests do. Invest time and energy in your integration testing suite, and put a process in place for integration testing at all stages of your development and deployment process. Ideally, run integration tests on your production systems, all the time.

There is no such thing as a service interrupting maintenance

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Who's Hiring?

  • Microsoft’s Visual Studio Online team is building the next generation of software development tools in the cloud out in Durham, North Carolina. Come help us build innovative workflows around Git and continuous deployment, help solve the Git scale problem or help us build a best-in-class web experience. Learn more and apply.

  • VoltDB's in-memory SQL database combines streaming analytics with transaction processing in a single, horizontal scale-out platform. Customers use VoltDB to build applications that process streaming data the instant it arrives to make immediate, per-event, context-aware decisions. If you want to join our ground-breaking engineering team and make a real impact, apply here.  

  • At Scalyr, we're analyzing multi-gigabyte server logs in a fraction of a second. That requires serious innovation in every part of the technology stack, from frontend to backend. Help us push the envelope on low-latency browser applications, high-speed data processing, and reliable distributed systems. Help extract meaningful data from live servers and present it to users in meaningful ways. At Scalyr, you’ll learn new things, and invent a few of your own. Learn more and apply.

  • UI EngineerAppDynamics, founded in 2008 and lead by proven innovators, is looking for a passionate UI Engineer to design, architect, and develop our their user interface using the latest web and mobile technologies. Make the impossible possible and the hard easy. Apply here.

  • Software Engineer - Infrastructure & Big DataAppDynamics, leader in next generation solutions for managing modern, distributed, and extremely complex applications residing in both the cloud and the data center, is looking for a Software Engineers (All-Levels) to design and develop scalable software written in Java and MySQL for backend component of software that manages application architectures. Apply here.

Fun and Informative Events

  • Surge 2015. Want to mingle with some of the leading practitioners in the scalability, performance, and web operations space? Looking for a conference that isn't just about pitching you highly polished success stories, but that actually puts an emphasis on learning from real world experiences, including failures? Surge is the conference for you.

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

Cool Products and Services

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  • MongoDB Management Made Easy. Gain confidence in your backup strategy. MongoDB Cloud Manager makes protecting your mission critical data easy, without the need for custom backup scripts and storage. Start your 30 day free trial today.

  • In a recent benchmark for NoSQL databases on the AWS cloud, Redis Labs Enterprise Cluster's performance had obliterated Couchbase, Cassandra and Aerospike in this real life, write-intensive use case. Full backstage pass and and all the juicy details are available in this downloadable report.

  • Real-time correlation across your logs, metrics and events. just released its operations data hub into beta and we are already streaming in billions of log, metric and event data points each day. Using our streaming analytics platform, you can get real-time monitoring of your application performance, deep troubleshooting, and even product analytics. We allow you to easily aggregate logs and metrics by micro-service, calculate percentiles and moving window averages, forecast anomalies, and create interactive views for your whole organization. Try it for free, at any scale.

  • In a recent benchmark conducted on Google Compute Engine, Couchbase Server 3.0 outperformed Cassandra by 6x in resource efficiency and price/performance. The benchmark sustained over 1 million writes per second using only one-sixth as many nodes and one-third as many cores as Cassandra, resulting in 83% lower cost than Cassandra. Download Now.

  • Datadog is a monitoring service for scaling cloud infrastructures that bridges together data from servers, databases, apps and other tools. Datadog provides Dev and Ops teams with insights from their cloud environments that keep applications running smoothly. Datadog is available for a 14 day free trial at

  • Turn chaotic logs and metrics into actionable data. Scalyr replaces all your tools for monitoring and analyzing logs and system metrics. Imagine being able to pinpoint and resolve operations issues without juggling multiple tools and tabs. Get visibility into your production systems: log aggregation, server metrics, monitoring, intelligent alerting, dashboards, and more. Trusted by companies like Codecademy and InsideSales. Learn more and get started with an easy 2-minute setup. Or see how Scalyr is different if you're looking for a Splunk alternative or Sumo Logic alternative.

  • SignalFx: just launched an advanced monitoring platform for modern applications that's already processing 10s of billions of data points per day. SignalFx lets you create custom analytics pipelines on metrics data collected from thousands or more sources to create meaningful aggregations--such as percentiles, moving averages and growth rates--within seconds of receiving data. Start a free 30-day trial!

  • 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 goes beyond monitoring and measures the system's work on your MySQL and PostgreSQL servers, providing unparalleled insight and query-level analysis. This unique approach ultimately enables your team to work more effectively, ship more often, and delight more customers.

  • 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. Please click to read more...

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Building Globally Distributed, Mission Critical Applications: Lessons From the Trenches Part 1

This is Part 1 of a guest post by Kris Beevers, founder and CEO, NSONE, a purveyor of a next-gen intelligent DNS and traffic management platform. Here's Part 2.

Every tech company thinks about it: the unavoidable – in fact, enviable – challenge of scaling its applications and systems as the business grows. How can you think about scaling from the beginning, and put your company on good footing, without optimizing prematurely? What are some of the key challenges worth thinking about now, before they bite you later on? When you’re building mission critical technology, these are fundamental questions. And when you’re building a distributed infrastructure, whether for reliability or performance or both, they’re hard questions to answer.

Putting the right architecture and processes in place will enable your systems and company to withstand the common hiccups distributed, high traffic applications face. This enables you to stay ahead of scaling constraints, manage inevitable network and system failures, stay calm and debug production issues in real-time, and grow your company and product successfully.

Who is this guy?

I’ve been building globally distributed, large scale applications for a long time.  Way back in the first dot-com boom, I bailed on college classes for a year and built backend infrastructure for a file-sharing startup which grew to millions of users – until the RIAA’s lawyers caught wind and sent us packing back to our dorm rooms. The business went bust, but I was hooked on scale.

More recently, at Voxel, an internet infrastructure provider that was acquired by Internap in 2011, I built global internet infrastructure used by many large web companies – we built globally distributed public cloud, bare metal as-a-service, content delivery networks, and much more. We learned a lot of scaling lessons, and we learned them the hard way.

Now, at NSONE, we’ve built a next-gen intelligent DNS and traffic management platform, which today services some of the largest properties on the Internet, including many companies who are themselves mission critical service providers.  This is truly globally distributed, mission critical infrastructure, and the lessons we learned at Voxel have served us well – and been reinforced time and again – as we’ve built and scaled the NSONE platform.

It’s time to share some of what we’ve learned, and with luck, maybe you can apply some of these lessons in your own applications – instead of learning them the hard way!

Architecture first

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Stuff The Internet Says On Scalability For August 28th, 2015x

Hey, it's HighScalability time:

The oldest known fossil of a flowering plant. 130 million years old. What digital will last so long?
  • 32.6: Ashley Madison password cracks per hour; 1 million: cores in the Human Brain Project's silicon brain; 54,000: tennis balls used at Wimbledon; 4 kB: size of first web page; 1.2 million: million messages per second Apache Samza performance on a single node; 27%: higher conversion for sites loading one second faster; 

  • Quotable Quotes:
    • @adrianco: Apple first read about Mesos on  and for a year have run Siri on the worlds biggest cluster 
    • @Besvinick: Interesting recurring sentiment from recent grads: We lived most of our college lives on Snapchat—now we don't have any "tangible" memories.
    • Robin Hobb: For most moments of our lives, we have forgotten almost all of the world around us, except for what currently claims our interest.
    • @Carnage4Life: I'd like to thank all the Amazon employees who cried at their desks to make this possible πŸ™πŸ‘ 🚚🍷🍸🍹🍺 
    • Jim Handy: The single most interesting thing I learned at the 2015 Flash Memory Summit was that 3D NAND doesn’t have a natural limit, after which some other memory type will need to be adopted.
    • @mccv: them: is that written down? me: we communicate in the viking tradition. Let me tell you the saga of that system.
    • The Handmade Manifesto: that amazing speed we'd been granted was wasted, by us, in a death by a thousand abstraction layers
    • Peter Thiel: For us to really have a greater productivity gains as a society, we have to do things more in the world of atoms and not just the world of bits.
    • @lxpollitt: Verizon announced today as paying customer of @Mesosphere DCOS. Cool on stage demo with 22k cores: 50k containers in 100s - @flo #MesosCon
    • Matthew Brunwasser: Technology has transformed this 21st-century version of a refugee crisis, not least by making it easier for millions more people to move.
    • @rsingel: Stephen Hawking says to never give up hope if caught in a black hole. He has never evidently used a mobile browser.
    • @lxpollitt: Siri has been running on Mesos for exactly one year today. “Mesos scales” - Apple #MesosCon
    • @Jimminy: "The cheapest, fastest, and most reliable components are those that aren’t there. — Gordon Bell
    • @mathiasverraes: There are only two hard problems in distributed systems:  2. Exactly-once delivery 1. Guaranteed order of messages 2. Exactly-once delivery
    • Horace Dediu: If I were Tim Cook I would not have the goal of tripling revenue over the next decade...The objective of the company is not to triple revenues, the objective of the company is to make great products...That's the goal. End of story. You don't talk about money. You talk about product. Money comes from product not the other way around...The purpose of the firm is to delight the customer. 
    • @t_blom: “The hardest thing about MVP — you decide what’s Minimum, the customer decides what's Viable”β€Š—β€Š@davidjbland 
    • @adrianco: #mesoscon @pbailis reading list. 
    • @kelseyhightower: Based on my twitter stream, it seems the theme coming out of #mesoscon is the major benefits of increasing resource utilization at scale.
    • lorenzhs: We need new algorithms that - require communication volume and latency significantly sublinear in the local input size (ideally polylogarithmic) - don't depend on randomly distributed input data (most older work does)
    • @clstokes: #MesosCon @pbailis on coordination-free systems - "Scalable systems can just shut up and comfortably share silence."
    • frankmcsherry: if you want to do any big data computation, please sort your records. Stop talking sass about how Hadoop sorts things it doesn't need to, read some papers, run some tests, and then sort your damned data. Or at least run faster than me when I sort your data for you.
    • @RFFlores: There's always lock-in. You have to choose where. My latest blog is about this.
    • Jared Diamond: People in the first world are terrified by the wrong things. The real danger isn’t terrorism, serial killers or sharks, which kill a very, very small percentage of people annually. The real risks are those things that we do daily that carry a low risk but that eventually catch up with you – driving, taking stairs, using step ladders.

  • Something tells me we can expect this list to get much larger as the future fumbles forward. T-Rex large. The 20 Most Infamous Cyberattacks of the 21st Century (Part I).

  • Getting to Datacenter Zero. Catchy buzzword from @swardley around Netflix sloughing off the last of its non AWS datacenter operations. Netflix shuts down its last data centre, but it still runs a big IT operation. Finally, all of Netflix IT will run in the public cloud. We'll likely hit Datacenter Zero long before we hit Inbox Zero.

  • She's so humble! Q: Alexa, what do you think of M, Facebook's new Human-Powered assistant? A: I don't have preferences or desires. 

  • Have you ever wanted to know how WiFi in a plane works? Have you ever wondered why it's so expensive? Have you ever wondered why it's just a tad slow? Then Why Gogo's Infuriatingly Expensive, Slow Internet Still Owns the Skies is your story. In my mind I thought the system would use a satellite. It doesn't! There's a vast air-to-ground system. The plane talks to 225 towers spread across the US. Newer systems do use a satellite. It's expensive because with a first mover advantage Gogo was able to lock in long term contracts and achieve a near monopoly. There are competitors, but switching costs are high. And with only 40,000 planes in the world making more money requires raising prices on relatively price insensitive business users. There's a sophisticated dynamic pricing scheme aimed at keeping traffic within capacity limits while maximizing profits. It's slow because the signal is shared by everyone on the plane and the hardware on 2/3rds of the planes tops out at 3Mbps. Yet it's still hard to deny: “Everything’s Amazing and Nobody’s Happy.” 

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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