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Sunday
Sep182016

Stuff The Internet Says On Scalability For September 23rd, 2016

Hey, it's HighScalability time:

 

Will Minority Report for developers really help us program better? (Primitive)

 

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  • October 2017: ICANN changes the DNSSEC root keys; $2.91M: cost of running Let's Encrypt; 20%: Amazon convenience tax; 100%: increase in spam; 6.2 km: Quantum teleportation across a metropolitan fibre network; March 18, 1982: birth of containers; 6 months: how long a lightening bolt can power a 60 watt bulb; trillions: EV cache hits per day @ Netflix; 5x: Spark is faster than MapReduce; billions: HTTP, Git and SSH connections served per day at GitHub; 28: # of websites in North Korea; 

  • Quotable Quotes:
    • @vgcerf: It is time to admit after 18 years that the multistakeholder model of Internet operation works. #yestoIANA
    • @EricLathrop: Netflix found a 5x performance variation between AWS instances at the same price! They benchmark to avoid overpaying. @indirect #Strangeloop
    • @swardley: Perfectly reasonable @NigelBarron. Larry's statements are ludicrous, play is to milk existing customers whilst hoping to find a new future.
    • @BethanyMacri: Etsy is very anti-SOA. Monolith forever!
    • janfoeh: I've said it before here and I'll say it again: the JS ecosystem is moving in the wrong direction. Sometimes I feel that with Javascript, we developers have taken something that wasn't ours, and we're in the process of destroying the best thing there ever was about it. So here we are, the single <script> tag having been replaced with compilers, transpilers, five mutually incompatible build systems, three different module systems in God knows how many implementations, frameworks changing their API every ten minutes and five thousand lines of NPM module code to be installed for even the simplest of tasks.
    • marknadal: This is the way humans have been thinking for thousands of years. And guess what, I sat down with a large airline and had to warn them "we're not Strongly Consistent" and they laughed at me saying "you realize we've been booking seat reservations before there was internet, before you were born, and before there was cheap telephony. Seat reservation has never been strongly consistent - we used to have hundreds of travel agents booking seats and it would take 2 weeks before we would hear about it."
    • Jason Feifer: All I have to do is go to another website and see the price is different, and I don't. It's crazy. Like, why am I not doing that? We're the problem.
    • @cmeik: "The clock-free design paradigm I promote must eventually prevail. It fits Physics."
    • @gabrielgironda: mclaren and apple are a great fit. all the stability of apple's software combined with the reliability of british automobiles
    • Bryan Cantrill: The virtual machine is vestigial abstraction. We can not get to #serverless without getting rid of of the VM.
    • @dchetwynd: The number of US households that only use cellular data has doubled from 10% to 20% between 2013 and 2016 #strangeloop
    • There are even more awesome Quotable Quotes in the full article.

  • Interesting results from a major architecture change at Netflix. Zuul 2 : The Netflix Journey to Asynchronous, Non-Blocking Systems. Netflix had a blocking servlet connectionless based architecture and they moved to a nonblocking asynchronous connection architecture. In general, from a latency, CPU, throughput, and capacity perspective the async version didn't perform much better than the old sync version. Netflix found "the less work a system actually does, the more efficiency we gain from async", which makes sense in terms of scheduling and IO. There was a big win however in the ability to scalably maintain over 83 million persistent connections, one for every client, back into their cloud infrastructure. The cost of a connection becomes a file descriptor instead of a thread, which is a lot cheaper. By using a persistent connect Netlfix can reduce overall device requests, improve device performance, understand and debug the customer experience better, enable more real-time user experience innovations, and reduce overall cloud costs by replacing “chatty” device protocols today (which account for a significant portion of API traffic) with push notifications. Operations did take a hit. Sync systems are much easier to understand and debug. Also, making the migration was not easy. Changing sync code to async is not for the faint-hearted. 

  • This is hilarious. Read the whole thread. You won't be disappointed. @stef: You are in a startup. All around is a burning runway. There are exits to the North and East. You have a bootstrap. There is a VC here.

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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Friday
Sep162016

Stuff The Internet Says On Scalability For September 16th, 2016 

Hey, it's HighScalability time:

 

The struggle for life that kills. Stunning video of bacteria mutating to defeat antibiotics. 

 

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

  • 60%: time spent cleaning dirty dirty BigData; 10 million: that's a lot of Raspberry Pi; 365: days living in a Mars simulation; 100M: monthly League of Legends players; 1.75 billion: copyright takedowns by Google; 3.5 petabytes: data Evernote has to move to Google cloud; 11%: YoY growth in time spent on mobile apps; 4 hours: time between Lambda coldstarts; 

  • Quotable Quotes:
    • Camille Fournier: humans struggle to tangibly understand domains that are theoretically separate when they are presented as colocated by the source code.
    • @songcarver: The better example: iPhone 7 is showing 115% of 2016 Macbook single core performance, 88% of multi-core.
    • ex3ndr: We (actor.im) also moved from google cloud to our servers + k8s. Shared persistent storage is a huge pain. We eventually stopped to try to do this, will try again when PetSets will be in Beta and will be able to update it's images.
    • @mcclure111: "Well maybe you should get your spaceship working before you try to implant nanites in your brain, DUDE"
    • IOpipe: Organizations I’ve spoken to have expressed an average of 10x cost savings over microservices-based infrastructure for the code they’ve moved to AWS Lambda.
    • avitzurel: Kube is winning for the same reason React/Redux (and now Mobx) is winning and why Rails was winning at the time. Community.
    • @etherealmind: Evernote is moving to public cloud. A strong sign that its in financial trouble, or lacking product direction.
    • @codinghorror: In 8 years of colocating servers I have seen multiple spinning rust disks fail, and one PSU, but zero SSDs failed from 2013-on.
    • Caltech: Now, with the new simulation—which used a network of thousands of computers running in parallel for 700,000 central processing unit (CPU) hours—Caltech astronomers have created a galaxy that looks like the one we live in today, with the correct, smaller number of dwarf galaxies.
    • Andy Grove: Rust is gearing up to be particularly suitable for building scalable asynchronous io and getting Rust onto servers is a great way to drive adoption of the language. 
    • James Hamilton: We have long believed that 80% of operations issues originate in design and development… When systems fail, there is a natural tendency to look first to operations since that is where the problem actually took place. Most operations issues, however, either have their genesis in design and development or are best solved there.
    • Google: even the possibility of a future quantum computer is something that we should be thinking about today.
    • Alan Kay: This doesn’t mean that “objects are now hidden”, but that they should be part of the “modeling and designing of ideas and processes” that is the center of what programming needs to be.
    • Packet Pushers: In the future the world be made of clouds and users. The user will be sitting in Starbucks and accessing the cloud and your network will be totally irrelevant.
    • StorageMojo: Our current system for the diffusion of knowledge is breaking down. How are we going to fix it?
    • Ron Miller: Flywheel Effect is the idea that once you have your core tech pieces in place, they have an energy of their own that drives other positive changes and innovations.
    • stonogo: Intel needs everything to be NUMA-aware. They're betting a lot of money on Xeon Phi, and once the self-booting KNL machines are out nobody will want to deal with the pcie cards any more.
    • @Fruzenshtein: It's strange to listen a talk about microservices when you have already heard about serverless architecture💩
    • MORGAN HOUSEL: There’s often a big gap between changing the world and convincing people that you changed the world.
    • @JoeEmison: Another under-reported aspect of moving from VMware to AWS: almost everyone is getting a massive performance improvement.
    • Dan Rayburn: Twitter’s NFL stream, taking place Thursday Sept 15th, will be delivered by Akamai and Level 3 and I do not expect it to have a large simultaneous audience. My estimate is under 2M simultaneous streams.
    • @johngirvin: Running serverless infrastructure this morning. In that the servers are all down.
    • Vlad Ilyushchenko: QuestdbWorker is pure worker implementation as far as worker consumers don't necessarily process same number of queue items. It is slower due to constant interaction with memory barriers and is at heavy disadvantage in this particular benchmark because it can't benefit from batching. Despite that workers can be useful when queue item processing cost is non-uniform.
    • ArkyBeagle: The path to concurrency is paved with a mix of finite state machines and event-driven programs. IMO, neither FP nor OO have all that much to say about that.
    • matt_oriordan: Having static servers handling load is only part of the problem in our experience. The true complexity and scalability of a system comes when you consider how it copes under load with unexpected failures (network, hardware), but more importantly expected maintenance such as regular deploys, scaling up and scaling down events
    • matthieum: I think my biggest complaint about the try-with-resources pattern is that... it just doesn't work. RAII just works, without effort on the client part, no matter how she uses the class.
    • Brandon Beck: I remember we had something like 20 folding chairs and, without knowing if anyone would watch, decided to stream the games. We ended up getting over 100,000 concurrent viewers, which just blew our minds. It was there we realized this was something League players loved and started to really take it seriously.
    • jandrewrogers: The weakness of GPU databases is that while they have fantastic internal bandwidth, their network to the rest of the hardware in a server system is over PCIe, which generally isn't going to be as good as what a CPU has and databases tend to be bandwidth bound. This is a real bottleneck and trying to work around it makes the entire software stack clunky.
    • @pmarca: 1 Software eats the world, 2 Every company becomes a software company, and 3 Software people run every company:
    • @benalexau: Benchmarked @mjpt777's Aeron w/ SBE and @grpcio for bulk xfers between JVMs. While different sweet spots, Aeron ~200 times higher throughput
    • Freeman Dyson: So, anyway, that’s sort of my view about the brain. That we won’t really understand the brain until we can make models of it which are analog rather than digital, which nobody seems to be trying very much.

  • Drivers and users turn out to be relatively price insensitive to Uber fares. As Uber approaches a monopoly position there's a lot of consumer surplus that can be turned into profits (if the war chest lasts). Why Uber Is an Economist’s Dream: if you extrapolate to the whole U.S., we found that the overall consumer surplus added up to almost $7 billion. So people spent about $4 billion on Ubers, but they actually would have been willing to spend about $11 billion.

  • Making money in Apple's app store ain't what it used to be, at least for developers. Here's a thoughtful discussion on the transition from a charge-up-front model to advertising suppported apps by long time app developers David Smith and Marco Arment: Overcast trying ads, dark theme now free and Under the Radar #45. You may lament advertising as the go to model allowing developers to make a decent living, but it turns out advertising within apps nicely aligns developer incentives with user goals in a way that doesn't happen for content. For content the drive to increase page views encourages a race to the bottom. Click-bait dominates as CPMs tumble. For apps the incentive is to provide a good user experience for every interaction. You want to encourage the user to use your app because that's when you get paid. Individually the payoff isn't so great that it warps the incentives to "encourage" a user to use your app, but over a whole installed base the more users use your app the more you get paid, so as a developer you have an incentive to keep developing features and making nice little improvements to the app. In the charge-up-front model the developer is disincentivized from making changes because there's always a well-founded fear any changes won't be rewarded by increased sales. If efforts aren't rewarded there's no point in efforting...and make no mistake, programming does take a lot of effort. And if a user really doesn't want ads they can pay to have them removed, there are no app ad blockers. Everyone wins. This has been your moment of Zen.

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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Tuesday
Sep132016

If Traffic is an Iterated Prisoner's Dilemma Game Can Smart Cars Evolve Co-operative Behavior?

 

Can small tribes of cooperating smart cars improve overall traffic even if they are not in the majority? Sure, if every car was a self-driving car maybe traffic jams could dissolve like blood clots on anticoagulants, but what about that messy in-between period? It will be some time before smart cars rule the road. Until then can smart cars make traffic better?

Adoption is hard. This is a general problem in tech. You want people to join your social network yet people won't join until enough people have already joined. What you really want is that virtuous circle to develop, where as more people adopt a technology it causes even more people to adopt it. So startups spend their VC money fast and furiously in hopes of acquiring new customers betting the lifetime value of a customer will be worth the investment. VC money is the dead corpse that feeds the rest of the ecosystem.

Traffic is already an example of a vicious cycle. Horrendous traffic jams are now the norm and "good" traffic windows are just tall tales texted to children. And it keeps on getting worse and not in a worse is better sort of way. Yet the incentives are still not enough for people to self-organize and batch themselves into cars. Cars are more of a synchronous streaming model. Traffic problems will need to be solved at a different level of abstraction. Human drivers are just so hopelessly human.

In some ways traffic is like an iterated game of Prisoner's Dilemma. So in an Evolution of Cooperation sense can overall flows improve if groups of self-driving cars cooperate together within a stream of muggle cars? If smart cars on the road choose to gang up together will that improve commute times in such a way that it will encourage more and more cars to join the gang, becoming part of the solution instead of the problem?

But we have the social network problem. Cars currently are individual, kept in silos organized by manufacturer. Tesla, Uber, Google, etc. don't cooperate at a global traffic planning level. Even cars within a manufacturer don't yet have the ability to slave themselves together in a self-driving conga line of traffic goodness.

Historically we know after individual point solutions are created the next step is to add a scheduling layer. After running a program on an entire CPU we create an OS (Linux, Windows, etc) to run multiple programs on the same CPU. After the container we create an OS (Swarm, Kubernetes, Mesos, etc) to run multiple programs on the same boxes.

We'll need a TrafficOS so all the cars that want to can cooperate together, you know like XMPP before the walls went up. Plus we'll need ecosystem incentives to help drive adoption. 

So many questions. Will drivers volunteer to be part of a smart car peloton even if it means their commute suffers in the short term? What's the tipping point? Will free riders ruin the whole thing? Like the fast lane, should incentives be created to encourage cooperating tribes of smart cars? Should traffic lights favor smart car trains? Should traffic laws allow bullet trains of smart cars to speed down the highway? Should insurance premiums be reduced for time spent protected in smart car convoys? Maybe smart car software should be seeded with altruism "genes" so they cooperate naturally? How can defectors be punished? Maybe we need a reputation system scoring for traffic reciprocity?

Unlike the weather traffic is something we can do something about. Let's just try to do a better job than we did with social networks and IM systems. Traffic is actually important.

Related Articles

Tuesday
Sep132016

Sponsored Post: ScaleArc, Spotify, Aerospike, Scalyr, Gusto, VividCortex, MemSQL, InMemory.Net, Zohocorp

Who's Hiring?

  • Spotify is looking for individuals passionate in infrastructure to join our Site Reliability Engineering organization. Spotify SREs design, code, and operate tools and systems to reduce the amount of time and effort necessary for our engineers to scale the world’s best music streaming product to 40 million users. We are strong believers in engineering teams taking operational responsibility for their products and work hard to support them in this. We work closely with engineers to advocate sensible, scalable, systems design and share responsibility with them in diagnosing, resolving, and preventing production issues. We are looking for an SRE Engineering Manager in NYC and SREs in Boston and NYC.

  • IT Security Engineering. At Gusto we are on a mission to create a world where work empowers a better life. As Gusto's IT Security Engineer you'll shape the future of IT security and compliance. We're looking for a strong IT technical lead to manage security audits and write and implement controls. You'll also focus on our employee, network, and endpoint posture. As Gusto's first IT Security Engineer, you will be able to build the security organization with direct impact to protecting PII and ePHI. Read more and apply here.

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Tuesday
Sep132016

The Dollar Shave Club Architecture Unilever Bought for $1 Billion

This is a guest post by Jason Bosco, the Dollar Shave Club’s Director of Engineering, Core Platform & Infrastructure, on the infrastructure of its ecommerce technology.

With more than 3 million members, Dollar Shave Club will do over $200 million in revenue this year. Although most are familiar with the company’s marketing, this immense growth in just a few years since launch is largely due to its team of 45 engineers.

Dollar Shave Club engineering by the numbers:

Core Stats

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Thursday
Sep082016

Stuff The Internet Says On Scalability For September 9th, 2016 

Hey, it's HighScalability time:

 

An alternate universe where Zeppelins rule the sky. 1929. (@AeroDork)

 

If you like this sort of Stuff then please support me on Patreon.
  • 15%: Facebook's reduction in latency using HTTP2's server push; 1.9x: nanotube transistors outperform silicon; 200: projectors used to film a "hologram"; 50%: of people fall for phishing attacks (it's OK to click); 5x: increased engagement using Google's Progressive Web Apps; 115,000+: Cassandra nodes at Apple; $500 million: Pokémon Go; $150M: Delta's cost for datacenter outage; 

  • Quotable Quotes: 
    • Dan Lyons: I wanted to write a book about what it’s like to be 50 and trying to reinvent yourself – that struggle. There are all these books and inspirational speakers talking about being a lifelong learner and it’s so great to reinvent yourself, the brand of you. And I wanted to say, you know, it’s not like that. It’s actually really painful.
    • Engineers & Coffee~ In modern application development everything is a stream now versus historically everything was a transaction. Make a request and the you're done. It's easier to write analytics on top of streams versus using Hive. It's cool that Kinesis is all real-time and has the power of SQL.
    • David Smith: The [iOS] market has been pulling me along towards advertising based apps, and I’ve found that the less I fight back with anachronistic ideas about how software “should” be sold, the more sustainable a business I have.
    • @tef_ebooks: (how do you keep a lisp user in suspense
    • @bodil: Use tests to verify your assumptions. Use a type checker to verify your implementations. Always.
    • tostitos1979: Here is a factoid for the youngins ... the Internet/Arpanet was created BEFORE the first microprocessor! In fact, Intel was originally founded to make RAM ICs. They only later created the first microprocessor (the 4004)!
    • gsubes:  Our tests showed than even with larger messages (100k price ticks per request) pipes were still a magnitude slower [than Memory Mapping].
    • Quincy Larson: Did you know the average developer only get two hours of uninterrupted work done a day? They spend the other 6 hours in varying states of distraction.
    • StorageMojo: Achieving lower-than-DRAM pricing requires volume, and that’s where NRAM has a competitive advantage over, say, 3D XPoint. Processing can be done on today’s flash, DRAM or logic lines. NRAM processing only needs spin coating and patterning – as well as carbon nanotubes – which modern fabs all support.
    • Xiao Mina: We’ve seen this story before: as cost of production and distribution go down, the range of creativity goes up.
    • @clarkkaren: Give humans a system and they'll game it. The End.
    • Jim Starkey: AmorphousDB is my modest effort to question everything database.
      The best way to think about Amorphous is to envision a relational database and mentally erase the boxes around the tables so all records free float in the same space – including data and metadata.
    • @jdub: On Reddit: “What is the use of Elastic IPs, if I can use ELB or an Auto Scaling Group instead?” STUDENT, YOU HAVE ACHIEVED ZEN OF CLOUD.
    • @BenedictEvans: A key premise for the next decade: it's easier for software to enter other industries than for other industries to hire software people
    • @jasongorman: To clarify, "dependency injection" literally just means passing an object's collaborators as constructor/method params. That's all it is.
    • jackpeterfletch: Grand solution to world hunger, available on Kindle!
    • @swardley: Optimise flow.  Often when you examine flows then you’ll find bottlenecks, inefficiencies and profitless flows.  There will be things that you’re doing that you just don’t need to. Be very careful here to consider not only efficiency but effectiveness. 
    • @PatrickMcFadin: #uber is fully replicated and active-active to make sure you never get stranded. #cassandrasummit
    • @FSVO: A monk named Chaitin found an algorithm for expressing the complexity of sutras. His master commented, “This monk could be shorter.”
    • Dotzler: We [Firefox] can learn from the competition [Chrome]. The way they implemented multi-process is RAM-intensive, it can get out of hand. We are learning from them and building an architecture that doesn’t eat all your RAM. 
    • @hichaelmart: Although CPU bound calculations [on OpenWhisk] seem about 4x slower than Lambda, so not too bad. Lambda still the winner so far though.
    • Shel Kaphan: Okay, I’m going to be building this website to run a bookstore [Amazon] and I haven’t done that before but it doesn’t sound so hard. When I’m done with that I’m not sure what I’ll do.
    • sixhobbits: "Our logger failed silently" "Shouldn't that have been recorded somewhere?" "I guess it's turtles all the way down"
    • @xmal: Trying to explain that CRDT causal contexts are a natural evolution of TCP sequence numbering and vector clocks in reliable causal broadcast
    • Joi Ito: Just like it is impossible to make another Silicon Valley somewhere else, although everyone tries—after spending four days in Shenzhen, I’m convinced that it’s impossible to reproduce this ecosystem anywhere else.
    • @adriancolyer: "My claim is that it is possible to write grand programs, noble programs, truly magnificent ones..." Knuth 1974
    • @Excellion: According to legend, if you say Blockchain three times fast, your databases will magically become immutable & your company a fintech leader.
    • bec0: The world has changed. Dennard scaling has mostly been replaced. The economic Moore's Law has morphed. It had too...we have all gotten used to its benefits.
    • @cloud_opinion: 5 stages of Cloud Grief: It's not secure / It's someone's computer / We do private cloud / Hybrid cloud  / Lambda is full of servers anyway
    • @DDD_Borat: "Why you not like framework annotations in your code?" - "Would you put bumper sticker on a Ferrari?" Rofl
    • @robert_winslow: Slow software is your fault. These are the real speed limits: billions of CPU instructions, GBs of RAM access, 100k+ SSD I/Os... per second.
    • Walter Bentley: I am proud to say, OpenStack held up to the torment. Did not experience not one single API request failure throughout my numerous load tests — yet another proof point that OpenStack is ready for enterprise/production use.
    • @xaprb: Let's fork it, say the people who have never put their heart and 5 years of their life into a product only to watch someone else fork it.
    • @adrianco: People asking Docker to slow down is like OpenStack folks asking AWS to standardize and slow down.
    • @amcafee: "In 1974, it was illegal for an airline to charge < $1,442 for a flight between New York City and Los Angeles."
    • Fairly Nerdy: For most real world scenarios, where you are betting against the house which has a house edge, f* becomes negative, which means that you shouldn’t be playing that game.  Truthfully it means that you should take the other side of the wager, become the house, and make them bet against you!
    • Judd Kaiser: Experience shows that good scalability can be achieved on 10 GigE networking provided that you stay above about 50,000 cells per core. That means, for example, that a 20 M cell problem shows good scaling up to about 400 cores; beyond that, interprocess communication latency begins to dominate and scaling degrades.

  • Maybe the real reason Uber wants driverless cars is hiring, er...onboarding drivers from across the globe is a really tough problem to solve. Each location has their own processes and that kills scalability. Screening processes and regulations vary, some countries have a very long list of required documents, and onboarding flows vary. Here's the story: How Uber Engineering Massively Scaled Global Driver Onboarding. So you can't use the same app everywhere. The solution was, as it often is, is to go meta and dynamic: the onboarding state machine (OSM)  easily configure a set of steps for each onboarding process in each country, state, city, or any level of granularity we need, coupled with an event system that allows us to easily switch users from one step to another depending on their actions or input. The onboarding API can then easily query the OSM to know at which step in the process a user is.  Clients are now stateless,  responsible only for their UI, 100% of the business logic in the shared back end. They went from Flask to Tornado and a lighter version of their initial JSON schema architecture, where only data is passed to the client, not UI definitions.

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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Wednesday
Sep072016

Code Generation: The Inner Sanctum of Database Performance

This is guest post by Drew Paroski, architect and engineering manager at MemSQL. Previously he worked at Facebook and developed HHVM, the popular real-time PHP compiler used across the company’s web scale application.

Achieving maximum software efficiency through native code generation can bring superior scaling and performance to any database. And making code generation a first-class citizen of the database, from the beginning, enables a rich set of speed improvements that provide benefits throughout the software architecture and end-user experience.

If you decide to build a code generation system you need to clearly understand the costs and benefits, which we detail in this article. If you are willing to go all the way in the name of performance, we also detail an approach to save you time leveraging existing compiler tools and frameworks such as LLVM in a proven and robust way.

Code Generation Basics

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Friday
Sep022016

Stuff The Internet Says On Scalability For September 2nd, 2016 

Hey, it's HighScalability time:

 

Spectacular iconic drawing of Aurora Borealis as observed in 1872. (Drawings vs. NASA Images)
  • 4,000 GB: projected bandwidth used per autonomous vehicle per day; 100K: photos of US national parks; 14 terabytes: code on Github in 1 billion files held in 400K repositories; 25: age of Linux; $5 billion: cost of labor for building Linux; $3800: total maintenance + repairs after 100K miles and 5 years of Tesla ownership; 2%: reduction in Arizona's economy by deporting all illegal immigrants; 15.49TB: available research data; 6%: book readers who are "digital only";

  • Quotable Quotes
    • @jennyschuessler: "Destroy the printing press, I beg you, or these evil men will triumph": Venice, 1473
    • @Carnage4Life: Biggest surprise in this "Uber for laundry" app shutting down is that there are still 3 funded startups in the space
    • @tlipcon: "backpressure" is right up there with "naming things" on the top 10 list of hardest parts of programming
    • cmcluck: Please consider K8s [kubernetes] a legitimate attempt to find a better way to build both internal Google systems and the next wave of cloud products in the open with the community. We are aware that we don't know everything and learned a lot by working with people like Clayton Coleman from Red Hat (and hundreds of other engineers) by building something in the open. I think k8s is far better than any system we could have built by ourselves. And in the end we only wrote a little over 50% of the system. Google has contributed, but I just don't see it as a Google system at this point.
    • looncraz: AMD is not seeking the low end, they are trying to redefine AMD as the top-tier CPU company they once were. They are aiming for the top and the bulk of the market.
    • lobster_johnson: Swarm is simple to the point of naivety.
    • @BenedictEvans: That is, vehicle crashes, >90% caused by human error & 30-40% by alcohol, cost $240bn & kill 30k each year just in the USA. Software please
    • @joshsimmons: "Documentation is like serializing your mental state." - @ericholscher, just one of many choice moments in here.
    • @ArseneEdgar: "better receive old data fast rather than new data slow"
    • @aphyr: hey if you're looking for a real cool trip through distributed database research, https://github.com/cockroachdb/cockroach/blob/develop/docs/design.md … is worth several reads
    • @pwnallthethings: It's a fact 0day policy-wonks consistently get wrong. 0day are merely lego bricks. Exploits are 0day chains. Mitigations make chains longer.
    • andrewguenther: Speaking of [Docker] 1.12, my heart sank when I saw the announcement. Native swarm adds a huge level of complexity to an already unstable piece of software. Dockercon this year was just a spectacle to shove these new tools down everyone's throats and really made it feel like they saw the container parts of Docker as "complete." 
    • @johnrobb: Foxconn just replaced 60,000 workers with robots at its Kushan facility in China.  600 companies follow suit.
    • @epaley: Well publicized - Uber has raised ~$15B. Yet the press is shocked @Uber is investing billions. Huh? What was the money for? Uber kittens?
    • Ivan Pepelnjak: One of the obsessions of our industry is to try to find a one-size-fits-everything solutions. It's like trying to design something that could be a mountain bike today and an M1 Abrams tomorrow. Reality doesn't work that way
    • There were so many good quotes this week that they wouldn't all fit here. Please see the full post to read all the wonderfulness.

  • This should concern every iPhone user. Total ownage.
    • Steve Gibson, Security Now 575, with a great explanation of Apple's previously unknown professional grade zero-day iPhone exploits, Pegasus & Trident, that use a chain of flaws to remotely jail break an iPhone. It's completely stealthy, surviving both reboots and upgrades. The exploits have been around for years and were only identified by accident. It's a beautiful hack.
    • Your phone is totally open and it happens just like in the movies: A user infected with this spyware is under complete surveillance by the attacker because, in addition to the apps listed above, it also spies on: Phone calls, Call logs,  SMS messages the victim sends or receives, Audio and video communications that (in the words a founder of NSO Group) turns the phone into a 'walkie­talkie'
    • Bugs happen in complicated software. Absolutely. But these exploits were for sale...for years. The companies that sell these exploits do not have to disclose them. Apple should be going to the open market and buying these exploits so they can learn about them and fix them. Apple should be outbidding everyone in their bug bounty system so they can find hacks and fix them.
    • Paying for exploits is not an ethical issue, it's smart business in a realpolitik world. If you can figure out the Double Irish With a Dutch Sandwich you can figure out how to go to the open market and find out all the ways you are being hacked. Apple needs to think about security strategically, not only as a tactical technical issue

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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Wednesday
Aug312016

My Test Tube Filled with DNA is Better than Your Mesos Cluster

 

We’ve seen computation using slime mold, soap film, water droplets, there’s even a 10,000 Domino Computer. Now DNA can do math In a test tube. Using addition, subtraction, multiplication, and division.

It’s not fast. Calculations can take hours. The upside: they are tiny and can work in wet environments. Think of running calculations in your bloodstream or in cells, like a programmable firewall, to monitor and alert on targeted health metrics and then trigger a localized response. Or if you are writing  science fiction perhaps the ocean could become one giant computer?

The applications already sound like science fiction:

Prior devices for control of chemical reaction networks and DNA doctor applications have been limited to finite-state control, and analog DNA circuits will allow much more sophisticated analog signal processing and control. DNA robotics have allowed devices to operate autonomously (e.g., to walk on a nanostructure) but also have been limited to finite-state control.
Analog DNA circuits can allow molecular robots to include real-time analog control circuits to provide much more sophisticated control than offered by purely digital control. Many artificial intelligence systems (e.g., neural networks and probabilistic inference) that dynamically learn from environments require analog computation, and analog DNA circuits can be used for back-propagation computation of neural networks and Bayesian probabilistic inference systems.

How does it work?

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Tuesday
Aug302016

The cat-and-mouse story of implementing anti-spam for Mail.Ru Group’s email service and what Tarantool has to do with this

Hey guys!

In this article, I’d like to tell you a story of implementing the anti-spam system for Mail.Ru Group’s email service and share our experience of using the Tarantool database within this project: what tasks Tarantool serves, what limitations and integration issues we faced, what pitfalls we fell into and how we finally arrived to a revelation.

Let me start with a short backtrace. We started introducing anti-spam for the email service roughly ten years ago. Our first filtering solution was Kaspersky Anti-Spam together with RBL (Real-time blackhole list — a realtime list of IP addresses that have something to do with spam mailouts). This allowed us to decrease the flow of spam messages, but due to the system’s inertia, we couldn’t suppress spam mailouts quickly enough (i.e. in the real time). The other requirement that wasn’t met was speed: users should have received verified email messages with a minimal delay, but the integrated solution was not fast enough to catch up with the spammers. Spam senders are very fast at changing their behavior model and the outlook of their spam content when they find out that spam messages are not delivered. So, we couldn’t put up with the system’s inertia and started developing our own spam filter...

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