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Tuesday
Sep182007

Amazon Architecture

This is a wonderfully informative Amazon update based on Joachim Rohde's discovery of an interview with Amazon's CTO. You'll learn about how Amazon organizes their teams around services, the CAP theorem of building scalable systems, how they deploy software, and a lot more. Many new additions from the ACM Queue article have also been included.

Amazon grew from a tiny online bookstore to one of the largest stores on earth. They did it while pioneering new and interesting ways to rate, review, and recommend products. Greg Linden shared is version of Amazon's birth pangs in a series of blog articles

Site: http://amazon.com

Information Sources

  • Early Amazon by Greg Linden
  • How Linux saved Amazon millions
  • Interview Werner Vogels - Amazon's CTO
  • Asynchronous Architectures - a nice summary of Werner Vogels' talk by Chris Loosley
  • Learning from the Amazon technology platform - A Conversation with Werner Vogels
  • Werner Vogels' Weblog - building scalable and robust distributed systems

    Platform

  • Linux
  • Oracle
  • C++
  • Perl
  • Mason
  • Java
  • Jboss
  • Servlets

    The Stats

  • More than 55 million active customer accounts.
  • More than 1 million active retail partners worldwide.
  • Between 100-150 services are accessed to build a page.

    The Architecture

  • What is it that we really mean by scalability? A service is said to be scalable if when we increase the resources in a system, it results in increased performance in a manner proportional to resources added. Increasing performance in general means serving more units of work, but it can also be to handle larger units of work, such as when datasets grow.

  • The big architectural change that Amazon made was to move from a two-tier monolith to a fully-distributed, decentralized, services platform serving many different applications.
  • Started as one application talking to a back end. Written in C++.
  • It grew. For years the scaling efforts at Amazon focused on making the back-end databases scale to hold more items, more customers, more orders, and to support multiple international sites. In 2001 it became clear that the front-end application couldn't scale anymore. The databases were split into small parts and around each part and created a services interface that was the only way to access the data.
  • The databases became a shared resource that made it hard to scale-out the overall business. The front-end and back-end processes were restricted in their evolution because they were shared by many different teams and processes.
  • Their architecture is loosely coupled and built around services. A service-oriented architecture gave them the isolation that would allow building many software components rapidly and independently.
  • Grew into hundreds of services and a number of application servers that aggregate the information from the services. The application that renders the Amazon.com Web pages is one such application server. So are the applications that serve the Web-services interface, the customer service application, and the seller interface.
  • Many third party technologies are hard to scale to Amazon size. Especially communication infrastructure technologies. They work well up to a certain scale and then fail. So they are forced to build their own.
  • Not stuck with one particular approach. Some places they use jboss/java, but they use only servlets, not the rest of the J2EE stack.
  • C++ is uses to process requests. Perl/Mason is used to build content.
  • Amazon doesn't like middleware because it tends to be framework and not a tool. If you use a middleware package you get lock-in around the software patterns they have chosen. You'll only be able to use their software. So if you want to use different packages you won't be able to. You're stuck. One event loop for messaging, data persistence,
    AJAX, etc. Too complex. If middleware was available in smaller components, more as a tool than a framework, they would be more interested.
  • The SOAP web stack seems to want to solve all the same distributed systems problems all over again.
  • Offer both SOAP and REST web services. 30% use SOAP. These tend to be Java and .NET users and use WSDL files to generate remote object interfaces. 70% use REST. These tend to be PHP or PERL users.
  • In either SOAP or REST developers can get an object interface to Amazon. Developers just want to get job done. They don't care what goes over the wire.
  • Amazon wanted to build an open community around their services. Web services were chosed because it's simple. But hat's only on the perimeter. Internally it's a service oriented architecture. You can only access the data via the interface. It's described in WSDL, but they use their own encapsulation and transport mechanisms.
  • Teams are Small and are Organized Around Services
    - Services are the independent units delivering functionality within Amazon. It's also how Amazon is organized internally in terms of teams.
    - If you have a new business idea or problem you want to solve you form a team. Limit the team to 8-10 people because communication hard. They are called two pizza teams. The number of people you can feed off two pizzas.
    - Teams are small. They are assigned authority and empowered to solve a problem as a service in anyway they see fit.
    - As an example, they created a team to find phrases within a book that are unique to the text. This team built a separate service interface for that feature and they had authority to do what they needed.
    - Extensive A/B testing is used to integrate a new service . They see what the impact is and take extensive measurements.
  • Deployment
    - They create special infrastructure for managing dependencies and doing a deployment.
    - Goal is to have all right services to be deployed on a box. All application code, monitoring, licensing, etc should be on a box.
    - Everyone has a home grown system to solve these problems.
    - Output of deployment process is a virtual machine. You can use EC2 to run them.
  • Work From the Customer Backwards to Verify a New Service is Worth Doing
    - Work from the customer backward. Focus on value you want to deliver
    for the customer.
    - Force developers to focus on value delivered to the customer instead of building technology first and then figuring how to use it.
    - Start with a press release of what features the user will see and work backwards to check that you are building something valuable.
    - End up with a design that is as minimal as possible. Simplicity is the key if you really want to build large distributed systems.
  • State Management is the Core Problem for Large Scale Systems
    - Internally they can deliver infinite storage.
    - Not all that many operations are stateful. Checkout steps are stateful.
    - Most recent clicked web page service has recommendations based on session IDs.
    - They keep track of everything anyway so it's not a matter of keeping state. There's little separate state that needs to be kept for a session. The services will already be keeping the information so you just use the services.
  • Eric Brewer's CAP Theorem or the Three properties of Systems
    - Three properties of a system: consistency, availability, tolerance to network partitions.
    - You can have at most two of these three properties for any shared-data system.
    - Partitionability: divide nodes into small groups that can see other groups, but they can't see everyone.
    - Consistency: write a value and then you read the value you get the same value back. In a partitioned system there are windows where that's not true.
    - Availability: may not always be able to write or read. The system will say you can't write because it wants to keep the system consistent.
    - To scale you have to partition, so you are left with choosing either high consistency or high availability for a particular system. You must find the right overlap of availability and consistency.
    - Choose a specific approach based on the needs of the service.
    - For the checkout process you always want to honor requests to add items to a shopping cart because it's revenue producing. In this case you choose high availability. Errors are hidden from the customer and sorted out later.
    - When a customer submits an order you favor consistency because several services--credit card processing, shipping and handling, reporting--are simultaneously accessing the data.

    Lessons Learned

  • You must change your mentality to build really scalable systems. Approach chaos in a probabilistic sense that things will work well. In traditional systems we present a perfect world where nothing goes down and then we build complex algorithms (agreement technologies) on this perfect world. Instead, take it for granted stuff fails, that's
    reality, embrace it. For example, go more with a fast reboot and fast recover approach. With a decent spread of data and services you might get close to 100%. Create self-healing, self-organizing lights out operations.

  • Create a shared nothing infrastructure. Infrastructure can become a shared resource for development and deployment with the same downsides as shared resources in your logic and data tiers. It can cause locking and blocking and dead lock. A service oriented architecture allows the creation of a parallel and isolated development process that scales feature development to match your growth.

  • Open up you system with APIs and you'll create an ecosystem around your application.

  • Only way to manage as large distributed system is to keep things as simple as possible. Keep things simple by making sure there are no hidden requirements and hidden dependencies in the design. Cut technology to the minimum you need to solve the problem you have. It doesn't help the company to create artificial and unneeded layers of complexity.

  • Organizing around services gives agility. You can do things in parallel is because the output is a service. This allows fast time to market. Create an infrastructure that allows services to be built very fast.

  • There's bound to be problems with anything that produces hype before real implementation

  • Use SLAs internally to manage services.

  • Anyone can very quickly add web services to their product. Just implement one part of your product as a service and start using it.

  • Build your own infrastructure for performance, reliability, and cost control reasons. By building it yourself you never have to say you went down because it was company X's fault. Your software may not be more reliable than others, but you can fix, debug, and deployment much quicker than when working with a 3rd party.

  • Use measurement and objective debate to separate the good from the bad. I've been to several presentations by ex-Amazoners and this is the aspect of Amazon that strikes me as uniquely different and interesting from other companies. Their deep seated ethic is to expose real customers to a choice and see which one works best and to make decisions based on those tests.

    Avinash Kaushik calls this getting rid of the influence of the HiPPO's, the highest paid people in the room. This is done with techniques like A/B testing and Web Analytics. If you have a question about what you should do code it up, let people use it, and see which alternative gives you the results you want.

  • Create a frugal culture. Amazon used doors for desks, for example.

  • Know what you need. Amazon has a bad experience with an early recommender system that didn't work out: "This wasn't what Amazon needed. Book recommendations at Amazon needed to work from sparse data, just a few ratings or purchases. It needed to be fast. The system needed to scale to massive numbers of customers and a huge catalog. And it needed to enhance discovery, surfacing books from deep in the catalog that readers wouldn't find on their own."

  • People's side projects, the one's they follow because they are interested, are often ones where you get the most value and innovation. Never underestimate the power of wandering where you are most interested.

  • Involve everyone in making dog food. Go out into the warehouse and pack books during the Christmas rush. That's teamwork.

  • Create a staging site where you can run thorough tests before releasing into the wild.

  • A robust, clustered, replicated, distributed file system is perfect for read-only data used by the web servers.

  • Have a way to rollback if an update doesn't work. Write the tools if necessary.

  • Switch to a deep services-based architecture (http://webservices.sys-con.com/read/262024.htm).

  • Look for three things in interviews: enthusiasm, creativity, competence. The single biggest predictor of success at Amazon.com was enthusiasm.

  • Hire a Bob. Someone who knows their stuff, has incredible debugging skills and system knowledge, and most importantly, has the stones to tackle the worst high pressure problems imaginable by just leaping in.

  • Innovation can only come from the bottom. Those closest to the problem are in the best position to solve it. any organization that depends on innovation must embrace chaos. Loyalty and obedience are not your tools.

  • Creativity must flow from everywhere.

  • Everyone must be able to experiment, learn, and iterate. Position, obedience, and tradition should hold no power. For innovation to flourish, measurement must rule.

  • Embrace innovation. In front of the whole company, Jeff Bezos would give an old Nike shoe as "Just do it" award to those who innovated.

  • Don't pay for performance. Give good perks and high pay, but keep it flat. Recognize exceptional work in other ways. Merit pay sounds good but is almost impossible to do fairly in large organizations. Use non-monetary awards, like an old shoe. It's a way of saying thank you, somebody cared.

  • Get big fast. The big guys like Barnes and Nobel are on your tail. Amazon wasn't even the first, second, or even third book store on the web, but their vision and drive won out in the end.

  • In the data center, only 30 percent of the staff time spent on infrastructure issues related to value creation, with the remaining 70 percent devoted to dealing with the "heavy lifting" of hardware procurement, software management, load balancing, maintenance, scalability challenges and so on.

  • Prohibit direct database access by clients. This means you can make you service scale and be more reliable without involving your clients. This is much like Google's ability to independently distribute improvements in their stack to the benefit of all applications.

  • Create a single unified service-access mechanism. This allows for the easy aggregation of services, decentralized request routing, distributed request tracking, and other advanced infrastructure techniques.

  • Making Amazon.com available through a Web services interface to any developer in the world free of charge has also been a major success because it has driven so much innovation that they couldn't have thought of or built on their own.

  • Developers themselves know best which tools make them most productive and which tools are right for the job.

  • Don't impose too many constraints on engineers. Provide incentives for some things, such as integration with the monitoring system and other infrastructure tools. But for the rest, allow teams to function as independently as possible.

  • Developers are like artists; they produce their best work if they have the freedom to do so, but they need good tools. Have many support tools that are of a self-help nature. Support an environment around the service development that never gets in the way of the development itself.

  • You build it, you run it. This brings developers into contact with the day-to-day operation of their software. It also brings them into day-to-day contact with the customer. This customer feedback loop is essential for improving the quality of the service.

  • Developers should spend some time with customer service every two years. Their they'll actually listen to customer service calls, answer customer service e-mails, and really understand the impact of the kinds of things they do as technologists.

  • Use a "voice of the customer," which is a realistic story from a customer about some specific part of your site's experience. This helps managers and engineers connect with the fact that we build these technologies for real people. Customer service statistics are an early indicator if you are doing something wrong, or what the real pain points are for your customers.

  • Infrastructure for Amazon, like for Google, is a huge competitive advantage. They can build very complex applications out of primitive services that are by themselves relatively simple. They can scale their operation independently, maintain unparalleled system availability, and introduce new services quickly without the need for massive reconfiguration.
  • Reader Comments (74)

    Jeff.. Bazos?

    November 29, 1990 | Unregistered Commenterherval

    Werner Vogels, the CTO of amazon, spoke a tiny bit about technical details on SE-Radio. You can find the podcast under http://www.se-radio.net/index.php?post_id=157593
    Interesting episode.

    November 29, 1990 | Unregistered CommenterJoachim Rohde

    That is a good interview. Thanks. I'll be adding the new information soon.

    November 29, 1990 | Unregistered CommenterTodd Hoff

    Amazon uses Perl and Mason.
    See: http://www.masonhq.com/?MasonPoweredSites

    November 29, 1990 | Unregistered CommenterArturo Fernandez

    as i see they reduce c++ part and move to j2ee?

    November 29, 1990 | Unregistered CommenterAlexei A. Korolev

    I am not sure how you can get that one wrong, unless you are a manager, but even then some engineer would school you 'til Sunday.

    November 29, 1990 | Unregistered CommenterAnonymous

    Thanks for catching that. I listen to these things a few times and sometimes I just write what I hear instead of what I mean.

    November 29, 1990 | Unregistered CommenterTodd Hoff

    I actually gave a scrisper definition of scalability at: http://www.allthingsdistributed.com/2006/03/a_word_on_scalability.html">A Word on Scalability


    Personaly I like http://www.acmqueue.com/modules.php?name=Content&pa=showpage&pid=388">the interview in ACM Queue best for a high level view


    --Werner

    November 29, 1990 | Unregistered CommenterWerner

    Seems more that they used Java for a job they usually would have done with Perl.

    November 29, 1990 | Unregistered CommenterAnonymous

    > Use non-monetary awards, like an old shoe. It's a way of
    > saying thank you, somebody cared.

    The one time I was dumb enough to go to the amazon all-company meeting instead of treating it as a free sleep-in day, I saw Bezos give a shoe to a guy.

    And I was like, "this guy builds spaceships, and he gives out stinky old tennis shoes to high achievers? And they don't, like, hit him with it? Where's the self-respect?"

    But I guess that's why I'm an ex-amazonian. Got a 20% salary boost when I ditched 'em, and no pager duty. See ya, Jeff.

    November 29, 1990 | Unregistered Commenterex-amazonian

    That's one of the stupidest things I have read for some time. Why would a smart company spend money on employee "awards" -- that helps nobody except the people from whom you bought the awards? Real high-achievers at Amazon are rewarded when the company does well, and with the stock at ~ $90 I know they are feeling pretty good. My guess is they want to hug Jeff.

    A low achiever would more likely resent this and leave for somewhere else, and the fact that they worked at Amazon likely helped in this job search as I am sure it did in your case. And, it seems like you leaving hasn't hurt Amazon too much :)

    November 29, 1990 | Unregistered CommenterAnonymous

    The thing with the old Nikies for high achievers sounds like the (stupid) diplomas given to IBMers.. If you really want to thank a high-achiever, give them a raise, or a bonus, or.. a axotic cruise.. not an constipated old shoe.. what a pluf :))

    November 29, 1990 | Unregistered CommenterAnonymous

    > And, it seems like you leaving hasn't hurt Amazon too much :)

    Oh, I'm sure amzn is fine without me. But the amazon employee half-life is about 18 months, so it isn't just me who thinks it sucks to work there. Think of how much more efficiently amzn could operate if it didn't have to turn over half its workforce every 18 months. I'm sure that would have an impact on its stock price. :)

    > Real high-achievers at Amazon are rewarded when the company
    > does well, and with the stock at ~ $90 I know they are feeling
    > pretty good. My guess is they want to hug Jeff.

    Sure, the stock is riding high now, and I'm happy for the people there who are making a good buck off it. But amzn pays under market standards for salary and counts on the stock to buff up their wages. Gambling with your paycheck ain't cool by me.

    Counting up all the money I've made over the past few years... if all my amzn grants had paid out at $90 per, I might've made $15-25K more if I'd stayed there. But a $25K premium (or $6.25K a year, since it take 4 years to vest) ain't nearly enough to get me in the door at amazon, considering that in exchange for that premium I'll be required to work 10-30 extra hours a week. I think equity-based compensation is for suckers. Equity compensation in exchange for huge workweek demands is for ... bigger suckers.

    My current company gives me real cash bonuses and extra paid time off for good performance. I'll take that over a stupid old shoe! Money is used for talking; shoes, like bullsh*t, are meant for walking.

    November 29, 1990 | Unregistered Commenterex-amazonian

    As a side effect of my deep studies of your article I translated it into German: http://habacht.blogspot.com/2007/10/amazon-architecture.html

    November 29, 1990 | Unregistered CommenterSebastian Wallroth

    why? perl is a common tool for text processing :) java is more than only perl

    November 29, 1990 | Unregistered CommenterAlexei

    With humility, I would tend to say that Java doesn't fit all the traditional business terms. Efficiency, return on investment. I run a company today and, trust me, Java would not be the ultimate option to design large & critical applications, in a long-term vision. Only pseudo-experts and pseudo-IT-managers consider Java as the first answer to programming issues for tomorrow. I would advise you to check the languages/frameworks landscape far behind J2EE. Perl 6 for instance. I'm joking ? Not really. Our last web services are fully designed with Perl and interfaces made in Ruby. And open-minded users wondered if it was struts+hibernate+weblogic+oracle (with, maybe a SAP R/3 connector). The reality is now quite different : we have to think pure business. Java ? Ok, well, i will check the Sun's blog today. I love Java too.

    November 29, 1990 | Unregistered CommenterAnonymous

    Really interesting, enjoyed reading that. However, I feel that if you really want to thank a high-achiever, give them a raise, or a bonus! thats what I appreciate most, after all we work for money.

    November 29, 1990 | Unregistered Commenterauroo

    Very informative for the most part (specially the parts I agree with ;)

    November 29, 1990 | Unregistered CommenterDickey Singh

    Mason is new for me! Very nice post. http://evandro.net/">Evandro http://www.poker73.com/">Sit&Go

    November 29, 1990 | Unregistered CommenterEvandro

    Very informative for the most part (specially the parts I agree with ;)

    November 29, 1990 | Unregistered CommenterDizi izle

    Very very informative article.Thanks a lot . :)

    March 2, 2010 | Unregistered CommenterPankaj Sharma

    I actually wrote a research paper on the topic of cloud storage services. I present an in-depth understanding and analysis of the key features of generic cloud storage services, and of how such services should be constructed and provided. This is achieved through the demonstration of design rationales and the implementation details of a real cloud storage system (CACSS). Anyone who is interested in Amazon S3's architecture might find this helpful. Here is the link to the paper:
    CACSS: Towards a Generic Cloud Storage Service

    May 22, 2012 | Unregistered CommenterYang Li

    I don't think Amazon staff go work at their warehouses any more

    http://www.motherjones.com/politics/2012/02/mac-mcclelland-free-online-shipping-warehouses-labor

    October 30, 2012 | Unregistered Commenternz viewer

    Great summary. Can anyone help me find the exact source of this interesting insight listed above? I clicked through the links but couldn't find it in a 15 minute search.

    "For the checkout process you always want to honor requests to add items to a shopping cart because it's revenue producing. In this case you choose high availability. Errors are hidden from the customer and sorted out later."

    April 8, 2014 | Unregistered CommenterDerrick

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