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Thursday
Apr102014

Paper: Scalable Atomic Visibility with RAMP Transactions - Scale Linearly to 100 Servers

We are not yet at the End of History for database theory as Peter Bailis and the Database Group at UC Berkeley continue to prove with a great companion blog post to their new paper: Scalable Atomic Visibility with RAMP Transactions. I like the approach of pairing a blog post with a paper. A paper almost by definition is formal, but a blog post can help put a paper in context and give it some heart.

From the abstract:

Databases can provide scalability by partitioning data across several servers. However, multi-partition, multi-operation transactional access is often expensive, employing coordination-intensive locking, validation, or scheduling mechanisms. Accordingly, many real-world systems avoid mechanisms that provide useful semantics for multi-partition operations. This leads to incorrect behavior for a large class of applications including secondary indexing, foreign key enforcement, and materialized view maintenance. In this work, we identify a new isolation model—Read Atomic (RA) isolation—that matches the requirements of these use cases by ensuring atomic visibility: either all or none of each transaction’s updates are observed by other transactions. We present algorithms for Read Atomic Multi-Partition (RAMP) transactions that enforce atomic visibility while offering excellent scalability, guaranteed commit despite partial failures (via synchronization independence), and minimized communication between servers (via partition independence). These RAMP transactions correctly mediate atomic visibility of updates and provide readers with snapshot access to database state by using limited multi-versioning and by allowing clients to independently resolve non-atomic reads. We demonstrate that, in contrast with existing algorithms, RAMP transactions incur limited overhead—even under high contention—and scale linearly to 100 servers.

What is RAMP?

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Tuesday
Apr082014

Microservices - Not a free lunch!

This is a guest post by Benjamin Wootton, CTO of Contino, a London based consultancy specialising in applying DevOps and Continuous Delivery to software delivery projects. 

Microservices are a style of software architecture that involves delivering systems as a set of very small, granular, independent collaborating services.

Though they aren't a particularly new idea, Microservices seem to have exploded in popularity this year, with articles, conference tracks, and Twitter streams waxing lyrical about the benefits of building software systems in this style.

This popularity is partly off the back of trends such as Cloud, DevOps and Continuous Delivery coming together as enablers for this kind of approach, and partly off the back of great work at companies such as Netflix who have very visibly applied the pattern to great effect.

Let me say up front that I am a fan of the approach. Microservices architectures have lots of very real and significant benefits:

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Monday
Apr072014

Google Finds: Centralized Control, Distributed Data Architectures Work Better than Fully Decentralized Architectures

For years a war has been fought in the software architecture trenches between the ideal of decentralized services and the power and practicality of centralized services. Centralized architectures, at least at the management and control plane level, are winning. And Google not only agrees, they are enthusiastic adopters of this model, even in places you don't think it should work.

Here's an excerpt from Google Lifts Veil On “Andromeda” Virtual Networking, an excellent article by Timothy Morgan, that includes a money quote from Amin Vahdat, distinguished engineer and technical lead for networking at Google:

Like many of the massive services that Google has created, the Andromeda network has centralized control. By the way, so did the Google File System and the MapReduce scheduler that gave rise to Hadoop when it was mimicked, so did the BigTable NoSQL data store that has spawned a number of quasi-clones, and even the B4 WAN and the Spanner distributed file system that have yet to be cloned.

 

"What we have seen is that a logically centralized, hierarchical control plane with a peer-to-peer data plane beats full decentralization,” explained Vahdat in his keynote. “All of these flew in the face of conventional wisdom,” he continued, referring to all of those projects above, and added that everyone was shocked back in 2002 that Google would, for instance, build a large-scale storage system like GFS with centralized control. “We are actually pretty confident in the design pattern at this point. We can build a fundamentally more efficient system by prudently leveraging centralization rather than trying to manage things in a peer-to-peer, decentralized manner.

The context of the article is Google's impressive home brew SDN (software defined network) system that uses a centralized control architecture instead of the Internet's decentralized Autonomous System model, which thinks of the Internet as individual islands that connect using routing protocols.

SDN completely changes that model as explained by Greg Ferro:

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Friday
Apr042014

Stuff The Internet Says On Scalability For April 4th, 2014

Hey, it's HighScalability time:


The world ends not with a bang, but with 1 exaFLOP of bitcoin whimpers.
  • Quotable Quotes:
    • @EtienneRoy: Algorithm:  you must encode and leverage your ignorance, not only your knowledge #hadoopsummit - enthralling
    • Chris Brenny: A material is nothing without a process. While the constituent formulation imbues the final product with fundamental properties, the bridge between material and function has a dramatic effect on its perception and use.
    • @gallifreyan: Using AWS c1, m1, m2? @adrianco says don't. c3, m3, r3 are now better and cheaper. #cloudconnect #ccevent
    • @christianhern: Mobile banking in the UK: 1,800 transactions per MINUTE. A "seismic shift" that banks were unprepared for

  • While we are waiting for that epic article deeply comparing Google's Cloud with AWS, we have Adrian Cockcroft's highly hopped slide comparing the two. Google: no enterprise customers, no reservation options, need more regions and zones, need lower inter-zone latency, no SSD options. AWS: no per minute billing, need simpler discount options, need more regions and zones, no real PaaS strategy, not instance migration.
  • Technology has change us from a demo or die culture to a deploy or die culture. We see this in software, but it's happening in hardware too says, Joi Ito (MIT Media Lab), in this interview.
  • The Curmudgeon of Truth declares I reckon your message broker might be a bad idea: Engineering in practice is not a series of easy choices, but a series of tradeoffs. Brokers aren’t bad, but the tradeoffs you’re making might not be in your favour." < Good discussion on Hacker News.
  • High phive this. Your application may already achieved a degree of consciousness. An information integration theory of consciousness: consciousness corresponds to the capacity of a system to integrate information.
  • People really really like to talk. Line, a messaging app that's big in Japansurpasses 400 Million Registered Users, 10 billion chat messages per day, 1.8 billion stickers per day, and over 12 million calls per day.

Don't miss all that the Internet has to say on Scalability, click below and become eventually consistent with all scalability knowledge...

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Thursday
Apr032014

Leslie Lamport to Programmers: You're Doing it Wrong

Famous computer scientist Leslie Lamport is definitely not a worse is better kind of guy. In Computation and State Machines he wants to make the case that to get better programs we need to teach programmers to think better. And programmers will think better when they learn to think in terms of concepts firmly grounded in the language of mathematics.

I was disappointed that there was so much English in the paper. Surely it would have been more convincing if it was written as a mathematical proof. Or would it?

This whole topic has been argued extensively throughout thousands of years of philosophy. Mathematics has always been a strange attractor for those trying to escape a flawed human rationality. In the end as alluring as the utopia of mathematics is, it lacks a coherent theory of meaning and programming is not about rearranging ungrounded symbols, it's about manipulating and shaping meaning.

For programmers I think Ludwig Wittgenstein has the right sense of things. Meaning is derived by use within a community. Programs built and maintained by programmers is at bottom a community of effort.

Abstract:

For quite a while, I’ve been disturbed by the emphasis on language in computer science. One result of that emphasis is programmers who are C++ experts but can’t write programs that do what they’re supposed to. The typical computer science response is that programmers need to use the right programming/specification/development language instead of/in addition to C++. The typical industrial response is to provide the programmer with better debugging tools, on the theory that we can obtain good programs by putting a monkey at a keyboard and automatically finding the errors in its code.

I believe that the best way to get better programs is to teach programmers how to think better. Thinking is not the ability to manipulate language; it’s the ability to manipulate concepts. Computer science should be about concepts, not languages. But how does one teach concepts without getting distracted by the language in which those concepts are expressed? My answer is to use the same language as every other branch of science and engineering—namely, mathematics. But how should that be done in practice? This note represents a small step towards an answer. It doesn’t discuss how to teach computer science; it simply addresses the preliminary question of what is computation. 

Related Articles

Tuesday
Apr012014

The Mullet Cloud Selection Pattern

In a recent thread on Hacker News one of the commenters mentioned that they use Digital Ocean for personal stuff, but use AWS for business.

This DO for personal and AWS for business split has become popular enough that we can now give it a name: the Mullet Cloud Selection Pattern - business on the front and party on the back.

Providers like DO are cheap and the lightweight composable container model has an aesthetic appeal to developers. Even though it seems like much of the VM infrastructure has to be reinvented for containers, the industry often follows the lead of developer preference.

The mullet is dead. Long live the mullet! Developers are ever restless, always eager to move onto something new. 

Tuesday
Apr012014

Sponsored Post: Layer, The Factory, Airseed, Uber, ScaleOut Software, Couchbase, Tokutek, Booking, MongoDB, BlueStripe, AiScaler, Aerospike, LogicMonitor, AppDynamics, ManageEngine, Site24x7  

Who's Hiring?

  • We’re looking for talented and driven engineers who are passionate about scalability and reliability to help us build Layer, the open communications layer for the Internet. Layer enables app developers to easily build secure, scalable messaging, voice and video features into any app. For more information and our full list of openings, please visit: https://layer.com/jobs

  • The Factory is seeking a collaborative, talented and entrepreneurial Sr. Front End Engineer. Backed by the co-founder of Skype+Rdio and led by Rdio's founding team, we're changing the way products are built and companies get launched (think incubator/accelerator without the nagging outside influence or funding/timing constraints). Our goal is to build a platform to better launch startups and opensource what we do along the way.  http://www.thefactory.com/pdfs/sr_frontend.pdf

  • Airseed -- a Google Ventures backed, developer platform that powers single sign-on authentication, rich consumer data, and analytics -- is hiring lead backend and fullstack engineers (employees #4, 5, 6). More info here: https://www.airseed.com/jobs

  • Join the team that scales Uber supply globally! Our supply engineering team is responsible for prototyping, building, and maintaining the partner-facing platform. We're looking for experienced back-end developers who care about developing highly scalable services. Apply at https://www.uber.com/jobs/4810.

  • We need awesome people @ Booking.com - We want YOU! Come design next
    generation interfaces, solve critical scalability problems, and hack on one of the largest Perl codebases. Apply: http://www.booking.com/jobs.en-us.html

  • 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

  • The Biggest MongoDB Event Ever Is On. Will You Be There? Join us in New York City June 23-25 for MongoDB World! The conference lineup includes Amazon CTO Werner Vogels and Cloudera Co-Founder Mike Olson for keynote addresses.  You’ll walk away with everything you need to know to build and manage modern applications. Register before April 4 to take advantage of super early bird pricing.
  • April 3 Webinar: The BlueKai Playbook for Scaling to 10 Trillion Transactions a Month. As the industry’s largest online data exchange, BlueKai knows a thing or two about pushing the limits of scale. Find out how they are processing up to 10 trillion transactions per month from Vice President of Data Delivery, Ted Wallace. Register today.

Cool Products and Services

  • As one of the fastest growing VoIP services in the world Viber has replaced MongoDB with Couchbase Server, supporting 100,000+ operations per second in the short term and 1,000,000+ operations per second in the long term for their third generation architecture.  See the full story on the Viber switch.

  • Do Continuous MapReduce on Live Data? ScaleOut Software's hServer was built to let you hold your daily business data in-memory, update it as it changes, and concurrently run continuous MapReduce tasks on it to analyze it in real-time. We call this "stateful" analysis. To learn more check out hServer.

  • LogicMonitor is the cloud-based IT performance monitoring solution that enables companies to easily and cost-effectively monitor their entire IT infrastructure stack – storage, servers, networks, applications, virtualization, and websites – from the cloud. No firewall changes needed - start monitoring in only 15 minutes utilizing customized dashboards, trending graphs & alerting.

  • BlueStripe FactFinder Express is the ultimate tool for server monitoring and solving performance problems. Monitor URL response times and see if the problem is the application, a back-end call, a disk, or OS resources.

  • aiScaler, aiProtect, aiMobile Application Delivery Controller with integrated Dynamic Site Acceleration, Denial of Service Protection and Mobile Content Management. Cloud deployable. Free instant trial, no sign-up required.  http://aiscaler.com/

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

  • www.site24x7.com : 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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Monday
Mar312014

How WhatsApp Grew to Nearly 500 Million Users, 11,000 cores, and 70 Million Messages a Second

When we last visited WhatsApp they’d just been acquired by Facebook for $19 billion. We learned about their early architecture, which centered around a maniacal focus on optimizing Erlang into handling 2 million connections a server, working on All The Phones, and making users happy through simplicity.

Two years later traffic has grown 10x. How did WhatsApp make that jump to the next level of scalability?

Rick Reed tells us in a talk he gave at the Erlang Factory: That's 'Billion' with a 'B': Scaling to the next level at WhatsApp (slides), which revealed some eye popping WhatsApp stats:

What has hundreds of nodes, thousands of cores, hundreds of terabytes of RAM, and hopes to serve the billions of smartphones that will soon be a reality around the globe? The Erlang/FreeBSD-based server infrastructure at WhatsApp. We've faced many challenges in meeting the ever-growing demand for our messaging services, but as we continue to push the envelope on size (>8000 cores) and speed (>70M Erlang messages per second) of our serving system.

What are some of the most notable changes from two years ago?

  • Obviously much bigger in every dimension, except the number of engineers. More boxes, more datacenters, more memory, more users, and more scale problems. Handling this level of growth with so few engineers is what Rick is most proud of: 40 million users per engineer. This is part of the win of the cloud. Their engineers work on their software. The network, hardware, and datacenter is handled by someone else.

  • They’ve gone away from trying to support as many connections per box as possible because of the need to have enough head room to handle the overall increased load on each box. Though their general strategy of keeping down management overhead by getting really big boxes and running efficiently on SMP machines, remains the same.

  • Transience is nice. With multimedia, pictures, text, voice, video all being part of their architecture now, not having to store all these assets for the long term simplifies the system greatly. The architecture can revolve around throughput, caching, and partitioning.

  • Erlang is its own world. Listening to the talk it became clear how much of everything you do is in the world view of Erlang, which can be quite disorienting. Though in the end it’s a distributed system and all the issues are the same as in any other distributed system.

  • Mnesia, the Erlang database, seemed to be a big source of problem at their scale. It made me wonder if some other database might be more appropriate and if the need to stay within the Erlang family of solutions can be a bit blinding?

  • Lots of problems related to scale as you might imagine. Problems with flapping connections, queues getting so long they delay high priority operations, flapping of timers, code that worked just fine at one traffic level breaking badly at higher traffic levels, high priority messages not getting serviced under high load, operations blocking other operations in unexpected ways, failures causing resources issues, and so on. These things just happen and have to be worked through no matter what system you are using.

  • I remain stunned and amazed at Rick’s ability to track down and fix problems. Quite impressive.

Rick always gives a good talk. He’s very generous with specific details that obviously derive directly from issues experienced in production. Here’s my gloss on his talk…

Stats

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Friday
Mar282014

Stuff The Internet Says On Scalability For March 28th, 2014

Hey, it's HighScalability time:


Looks like a multiverse, if you can keep it.
  • Quotable Quotes:
    • @abt_programming: "I am a Unix Creationist. I believe the world was created on January 1, 1970 and as prophesized, will end on January 19, 2038" - @teropa
    • @demisbellot: Cloud prices are hitting attractive price points, one more 40-50% drop and there'd be little reason to go it alone.
    • @scott4arrows: Dentist "Do you floss regularly?" Me "Do you back up your computer data regularly?"
    • @avestal: "I Kickstarted the Oculus Rift, what do I get?" You get a lesson in how capitalism works.
    • @mtabini: “$20 charger that cost $2 to make.” Not pictured here: the $14 you pay for the 10,000 charger iterations that never made it to production.
    • @strlen: "I built the original assembler in JS, because it's what I prefer to use when I need to get down to bare metal." - Adm. Grace Hopper
    • tedchs: I'd like to propose a new rule for Hacker News: only if you have built the thing you're saying someone should save money by building themselves, may you say the person should build that thing.
    • lamby: Bezos predicted they would be good over the long term but said that he didn’t want to repeat “Steve Jobs’s mistake” of pricing the iPhone in a way that was so fantastically profitable that the smartphone market became a magnet for competition.
    • @PariseauTT: I feel a Netflix case study coming...everybody get your drinks ready...#AWSSummit
    • seanmccann: That's no different than startups of the past having to pay thousands to millions of dollars to setup servers. These days those same servers can be setup in minutes for a fraction of the cost. Timing is everything. Sometimes the current market pricing for a commodity is too expensive to make your business viable today but in the future that will not be the case. Just depends how long that will take. 
    • Petyr 'Littlefinger' Baelish: Chaos isn't a pit. Chaos is a ladder. Many who try to climb it fail and never get to try again. The fall breaks them. And some, are given a chance to climb. They refuse, they cling to the realm or the gods or love. Illusions. Only the ladder is real. The climb is all there is.
  • We turn those who first climb the peaks of tall mountains into heros. But what of the mountain? Mariana Mazzucato The Entrepreneurial State: Debunking Private vs. Public Sector Myths: Every feature of the iPhone was created, originally, by multi-decade government-funded research. From DARPA came the microchip, the Internet, the micro hard drive, the DRAM cache, and Siri. From the Department of Defense came GPS, cellular technology, signal compression, and parts of the liquid crystal display and multi-touch screen (joining funding from the CIA, the National Science Foundation, and the Department of Energy, which, by the way, developed the lithium-ion battery.) CERN in Europe created the Web. Steve Jobs’ contribution was to integrate all of them beautifully.

  • This is not an April Fools' joke, as the name might make a certain sort of mind consider. WebScaleSQL: MySQL goes web scale with contributions from MySQL engineering teams at Facebook, Google, LinkedIn, and Twitter. It includes lots of good work on the test suite, performance enhancements, and features to make scaling easier. So many forks at the table (MariaDB, Percona, webscale).

  • This is why we can't have nice code. Martin Sústrik argues In the Defense of Spaghetti Code, quite successfully I think, that it's often clearer to have one large 1500 line function than it is to have a refactored great big ball of mud. Commenters argue from a perfect world stance that if you do X from the start and then continue the same practices over the years and and hundreds of programmers then code can be perfected. Not so. The nature of many domains is they are just messy. At a certain level of abstraction messiness can be hidden, but when you are in the guts of a thing, messiness is preserved. 

Don't miss all that the Internet has to say on Scalability, click below and become eventually consistent with all scalability knowledge...

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Thursday
Mar272014

Strategy: Cache Stored Procedure Results

Caching is not new of course, but I don't think I've heard of caching store procedure results before. It's like memoization in the database. Brent Ozar covers this idea in How to Cache Stored Procedure Results.

The benefits are the usual for doing work in the database, it doesn't take per developer per app work, just code it once in the stored proc and it works for everyone, everywhere, for all of time. The disadvantage is the usual as well, it adds extra load to a probably already busy database, so it should only be applied to heavy computations.

Brent positions this strategy as an emergency bandaid to apply when you need to take pressure off a database now. Developers can then work on moving the cache off the database and into its own tier. Interesting idea. And as the comments show the implementation is never as simple as it seems.