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About Me
• Joined Achievers in June 2009
• Prior to Achievers, I was the CTO of ZipLocal
• I have spent the last 7 years worrying about
  how to build scalable applications
• Academic Background:
  – Ph.D. from the University of Toronto
  – Naval Research Labs Post Doctoral Fellow of
    Secure Systems at Cambridge University
Goals
• Tell you about our journey to a scalable
  architecture
• Give you insight into common scaling
  problems
• Give you a way to think about the issues of
  scaling that you can apply today
ACHIEVERS
What Does Achievers Do
• Achievers started in rewards and recognition
  space in 2007
• We provide reward and recognition software
  – Points based system to reward performance
  – Catalog to redeem the points
• Our mission is to “Change the way the world
  works”
The Achievers Home Page
Our Traffic Growth
• From 2009 to today
  – Visits up 903%
  – Unique Visitors up 832%
• Last month we did 2.5 million page views
• During business hours we have about 250
  people on the site at any given moment
Funding
• 3.3 million Series A from JLA Ventures
• 6.9 million Series B form Grandbanks
• 24 million Series C from Sequoia Capital
PRELIMINARIES
Definitions
• Performance
  – Performance measures the speed which a single
    request can be executed
• Scalability
  – Scalability is the ability to handle a growing
    number of requests in a capable manner


            Scalability != Performance
Which Language Scales the Best?
• Languages Don’t Scale Architectures Do
• If you hear “language X doesn’t scale” then
  turn around and walk away.
  – That person doesn’t understand scalability
There is a bit more to Scalability
• Scalability is also about how you scale the
  development team
• If you are successful and need to add people
  how easy is it for them to contribute
• How fast can you write code
  – Your competitors are right behind you
  – He who can develop good code fast wins!
OUR SAAS PLATFORM
The Achievers Platform
• Multi tenant architecture
  – One code base
  – One database
• Module based platform
  – Hundreds of configuration options for each
    module
  – Lots of legacy configurations
Backend Processing
• We handle many millions of dollars of orders
  every month
• We send out hundreds of thousands of emails
  a month
THE ARCHITECTURE CIRCA 2009
The Stack
•   Pretty Standard J2EE stack
•   Hibernate
•   Spring
•   JMS
•   MySql
•   All running on Amazon EC2
Aside – Amazon EC2
• EC2 is great
• Spin up machines for testing then shut them
  down
• A must for any startup
  – Don’t manage your own servers when you are
    small. It isn’t worth it
Architecture
Presentation   Business Logic



JSP Pages




                           Hibernate
Servlet          Objects

HTML
                                       MySql
LOOKS GREAT SO WHAT'S THE
PROBLEM?
Architecture – Data Center View


 Server 1
But J2EE Scales
• Sure it does BUT
• The devil is in the details
MEET THE DEVIL DETAILS
Scaling Was an Afterthought
• We had to scale vertically since the underlying
  design did not consider what would happen if
  we had 2 web servers
• We had the largest EC2 instance money could
  buy
• You cannot retrofit scalability
  – Your architecture and design either have it or they
    doesn’t
Design Decisions
• Your basic approach and philosophy to a few
  things will determine how hard it will be to
  scale your infrastructure
COMPLEXITY
Who doesn’t like magic
• Extensive use of Aspect Oriented
  Programming (AOP)
  – Allows you to define ‘cut-points’ to insert code
    before or after a function call
• As an academic AOP is brilliant
• As a CTO not so much
There is a Pattern for That
• Use of design patterns for the sake of using a
  design pattern
• Don’t get me wrong every developer must
  know and understand design patterns
• But it isn’t a competition to see who can use
  the most design patterns in any given day
  – The right tool for the right job
  – Don’t force it!
Overly complex object model
• The Access Control model had so many
  objects and relationships that other than the
  original author no other person ever
  understood it
Why is Complexity Bad?
• If the system dies at two o'clock in the
  morning and I'm staring at your code, can I
  easily figure out what's going on?
• People Forget about Magic
  – Code needs to be in front of you not buried in an
    XML file or magically invoked
What Does This Have To Do With
            Scalability?
• Complex systems are really, really hard to
  scale
  – In a clustered environment you need to first figure
    out if the problem is because of clustering or
    because of your code
  – This isn’t trivial even for simple systems
• To many things to worry about
• When you hit a wall (and you will) it becomes
  very hard to figure out what to do
Don’t Forget About the People
• As you grow your team you need to ramp
  everybody up
• A complex system takes longer to learn than a
  simple one
• Complexity ALWAYS increases over time. If
  you start with something that is complex it
  will quickly get beyond the scope of a meer
  mortal
Desire for Complex Solutions
Complexity




             Experience
THE DATABASE
The Database
• ORMs make you stupid … kidding … sort of
• You need to understand your data
  – Do not let an ORM define your database you will be
    sorry
• Generating reports out of an ORM is painful
• Developers must understand how a DB works
  – You will forget about what a DB is good for if you
    don’t consider it explicitly
  – New developers usually do not understand the
    importance of the DB in scaling
ORM’s
• Can they scale?
   – Sure
• Is it hard?
   – Yup
• A quote from stackoverflow on scaling ORM’s
   – “… a good ORM will provide plenty of hooks that
     allow you to optimize quite a bit. You just need to
     spend some time learning it.”
Is that all?
• Initially ORMs might allow you to write code
  quickly
  – I would challenge this but that is another topic
• Your system runs into a brick wall. Customers
  are complaining. Your CEO is chewing out the
  CTO. The VP Engineering is curled up in a ball
  in the corner. They turn to you as the
  architect and you answer:
“We just need to learn how to use all the hooks”
Just Learn the ORM
• I have yet to meet somebody that could
  convince me that they knew how to scale an
  ORM
  – It HAS been done, so yes it is possible but it takes
    patience and a CEO that likes to wait
  – I’ve had people tell me “we just have to rewrite
    the ORM with a new ORM that could scale”
Know your database
• I believe that your DB should own all your
  data
  – Let it do what it is good at
• If that is true then simple replication
  strategies and a little bit of coding can get you
  reading data from a replica
• You can then start denormalizing the DB to get
  better performance
Scaling Your Data
• Scaling a DB is a well understood problem
  with well understood solutions
• Don’t confuse this with easy!
SESSIONS
Server Side Sessions
• Very developer friendly
• You have 2 choices to scale:
  – Session replication
  – Sticky Sessions
Session Replication
• Yuck!
• Lots of network chatter
• Slow propagation of the session means the
  user has a bad experience
• You could be moving lots of data around
  – Our sessions were huge
Sticky Sessions
• Works but you now need to worry about a
  machine being overloaded while the others
  are idle
• A machine failure logs out everybody from
  that machine
• You have be very careful when configuring
  – If all IP addresses go to one server then you
    essentially have one company per server
CACHING
When to Cache
• Our platform made extensive use of caches
• That has to be good right?
• Not in our case
  – Items were cached by Java
  – Shared state posed a problem when adding
    another server
  – Yes there are Java based solutions but all you are
    doing is adding complexity
ADMITTING YOU HAVE A PROBLEM
It Won’t Love You Back
• Never fall in love with your technology. It will
  break your heart.
• You must always challenge your assumptions
  and be prepared to throw away something
  – Hard to throw away your ‘baby’
  – Remember it is just a bunch of 1’s and 0’s
THE JOURNEY
Basic Premise
• Every web application follows the same basic
  flow:
1. User makes a request
2. Validate the request
3. Grab some data
4. Process it a bit
5. Build a Page for the user
Guiding Architectural Principles
• Initial deployment would be on 3 machines
   – Forcing us to understand how we are going to scale
     upfront
• Servers must be stateless
• The database owns all the data
• Caching is an explicit choice to solve a real
  problem
• Always use the right tool for the job
• Minimize complexity
Other Goals
• Zero downtime deployments
• We wanted to be able upgrade customers one
  at a time
• Maximize developer productivity
The Target
                              Load Balancer



            Web Server         Web Server           Web Server




                                                          Background
MemcacheD          NAS                                    Processing
  Cluster         Device    MySql           MySql
                            Master          Slave
The Language Choice
• Why PHP
  – Faster code/debug cycles
     • This has increased our productivity
  – Zero downtime deployments
     • We have patched running servers multiple times in a
       day and nobody has noticed anything
  – Shared nothing philosophy
     • Forces a good frame of mind for server development
Doesn’t PHP Suck?
• Languages don’t suck only the developers
  using them do
• PHP isn’t perfect
  – Google ‘why php sucks’ for an extensive list
• But PHP doesn’t scale
  – Remember, languages don’t scale …
  – If you don’t believe me ask
    Wikipedia, Facebook, Digg etc.
Sure but PHP is Slow
• If your web application is not database bound
  then you are probably doing it wrong
• Yes Java might perform at some things but
  that will not be a limiting factor
Surely There are Down Sides?
• Because PHP does not have strong typing you
  need really good error detection and reporting
  – We will do another talk on our struggles and
    solutions
• Coding standards are a must since PHP lets
  you pretty much do whatever you want
  – Naming conventions are super important
  – Don’t start a religious war over bracket placement.
    There really is only one right way 
The Framework
• We use Codeigniter (CI)
• Simple MVC framework
  – The code is very easy to follow
• Works out of the box, but is very extensible
  – Strictly follows the Open/Closed principle
  – We have extended CI a lot to meet our needs
• Doesn’t require learning anything but PHP
Using the Right Tool
• Have Apache (or a faster web server) server all
  static content
• A Network Attached Storage (NAS) device was
  used for a shared file system.
  – This makes life a TON easier
• Have your web servers serve requests
• Move background work to another server
The Problem
• We had about 120 customers and we couldn’t
  just go away to do what we needed to do
  – Not a bad problem to have
THE MIGRATION
Step 1
• We wrote a controller that would forward
  requests to the new code base
• GET requests could be easily forwarded
• POST request were a bit more complicated
• This step allowed us to start developing the
  new platform AND keep releasing features
Step 2
• Start migrating customers to the new platform
• We put a proxy server in front of our old and
  new platforms.
• We then proxied specific requests to the
  version they were running on
The Setup

            HAProxy




Express               Achievers
Platform              Platform




             MySql
HAProxy
• If you don’t have it installed go back to the
  office download it and install it!
• It isn’t just a load balancer
  – We can move specific traffic to specific machines
    for whatever reason
  – We have a machine with profiling capabilities that
    we have used to profile production problems
  – Fine grain control over your request
We did it!
• It took us almost 6 months to migrate every
  customer but we did get there
• Our productivity has improved
• And we have an architecture that we know
  can handle whatever we can throw at it
  – At least in the short term
CONCLUSIONS
Scaling is Hard
• Don’t make it harder on yourself
  – Reduce complexity
  – Understand your database
  – Have an upfront strategy to deal with state
     • We picked stateless but you don’t have to
Never let anybody tell you a
language or framework does or
         doesn’t scale.

     It is all in the details
Scaling High Traffic Web Applications

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Scaling High Traffic Web Applications

  • 1.
  • 2. About Me • Joined Achievers in June 2009 • Prior to Achievers, I was the CTO of ZipLocal • I have spent the last 7 years worrying about how to build scalable applications • Academic Background: – Ph.D. from the University of Toronto – Naval Research Labs Post Doctoral Fellow of Secure Systems at Cambridge University
  • 3. Goals • Tell you about our journey to a scalable architecture • Give you insight into common scaling problems • Give you a way to think about the issues of scaling that you can apply today
  • 5. What Does Achievers Do • Achievers started in rewards and recognition space in 2007 • We provide reward and recognition software – Points based system to reward performance – Catalog to redeem the points • Our mission is to “Change the way the world works”
  • 7. Our Traffic Growth • From 2009 to today – Visits up 903% – Unique Visitors up 832% • Last month we did 2.5 million page views • During business hours we have about 250 people on the site at any given moment
  • 8. Funding • 3.3 million Series A from JLA Ventures • 6.9 million Series B form Grandbanks • 24 million Series C from Sequoia Capital
  • 10. Definitions • Performance – Performance measures the speed which a single request can be executed • Scalability – Scalability is the ability to handle a growing number of requests in a capable manner Scalability != Performance
  • 11. Which Language Scales the Best? • Languages Don’t Scale Architectures Do • If you hear “language X doesn’t scale” then turn around and walk away. – That person doesn’t understand scalability
  • 12. There is a bit more to Scalability • Scalability is also about how you scale the development team • If you are successful and need to add people how easy is it for them to contribute • How fast can you write code – Your competitors are right behind you – He who can develop good code fast wins!
  • 14. The Achievers Platform • Multi tenant architecture – One code base – One database • Module based platform – Hundreds of configuration options for each module – Lots of legacy configurations
  • 15. Backend Processing • We handle many millions of dollars of orders every month • We send out hundreds of thousands of emails a month
  • 17. The Stack • Pretty Standard J2EE stack • Hibernate • Spring • JMS • MySql • All running on Amazon EC2
  • 18. Aside – Amazon EC2 • EC2 is great • Spin up machines for testing then shut them down • A must for any startup – Don’t manage your own servers when you are small. It isn’t worth it
  • 19. Architecture Presentation Business Logic JSP Pages Hibernate Servlet Objects HTML MySql
  • 20. LOOKS GREAT SO WHAT'S THE PROBLEM?
  • 21. Architecture – Data Center View Server 1
  • 22. But J2EE Scales • Sure it does BUT • The devil is in the details
  • 23. MEET THE DEVIL DETAILS
  • 24. Scaling Was an Afterthought • We had to scale vertically since the underlying design did not consider what would happen if we had 2 web servers • We had the largest EC2 instance money could buy • You cannot retrofit scalability – Your architecture and design either have it or they doesn’t
  • 25. Design Decisions • Your basic approach and philosophy to a few things will determine how hard it will be to scale your infrastructure
  • 27. Who doesn’t like magic • Extensive use of Aspect Oriented Programming (AOP) – Allows you to define ‘cut-points’ to insert code before or after a function call • As an academic AOP is brilliant • As a CTO not so much
  • 28. There is a Pattern for That • Use of design patterns for the sake of using a design pattern • Don’t get me wrong every developer must know and understand design patterns • But it isn’t a competition to see who can use the most design patterns in any given day – The right tool for the right job – Don’t force it!
  • 29. Overly complex object model • The Access Control model had so many objects and relationships that other than the original author no other person ever understood it
  • 30. Why is Complexity Bad? • If the system dies at two o'clock in the morning and I'm staring at your code, can I easily figure out what's going on? • People Forget about Magic – Code needs to be in front of you not buried in an XML file or magically invoked
  • 31. What Does This Have To Do With Scalability? • Complex systems are really, really hard to scale – In a clustered environment you need to first figure out if the problem is because of clustering or because of your code – This isn’t trivial even for simple systems • To many things to worry about • When you hit a wall (and you will) it becomes very hard to figure out what to do
  • 32. Don’t Forget About the People • As you grow your team you need to ramp everybody up • A complex system takes longer to learn than a simple one • Complexity ALWAYS increases over time. If you start with something that is complex it will quickly get beyond the scope of a meer mortal
  • 33. Desire for Complex Solutions Complexity Experience
  • 35. The Database • ORMs make you stupid … kidding … sort of • You need to understand your data – Do not let an ORM define your database you will be sorry • Generating reports out of an ORM is painful • Developers must understand how a DB works – You will forget about what a DB is good for if you don’t consider it explicitly – New developers usually do not understand the importance of the DB in scaling
  • 36. ORM’s • Can they scale? – Sure • Is it hard? – Yup • A quote from stackoverflow on scaling ORM’s – “… a good ORM will provide plenty of hooks that allow you to optimize quite a bit. You just need to spend some time learning it.”
  • 37. Is that all? • Initially ORMs might allow you to write code quickly – I would challenge this but that is another topic • Your system runs into a brick wall. Customers are complaining. Your CEO is chewing out the CTO. The VP Engineering is curled up in a ball in the corner. They turn to you as the architect and you answer: “We just need to learn how to use all the hooks”
  • 38. Just Learn the ORM • I have yet to meet somebody that could convince me that they knew how to scale an ORM – It HAS been done, so yes it is possible but it takes patience and a CEO that likes to wait – I’ve had people tell me “we just have to rewrite the ORM with a new ORM that could scale”
  • 39. Know your database • I believe that your DB should own all your data – Let it do what it is good at • If that is true then simple replication strategies and a little bit of coding can get you reading data from a replica • You can then start denormalizing the DB to get better performance
  • 40. Scaling Your Data • Scaling a DB is a well understood problem with well understood solutions • Don’t confuse this with easy!
  • 42. Server Side Sessions • Very developer friendly • You have 2 choices to scale: – Session replication – Sticky Sessions
  • 43. Session Replication • Yuck! • Lots of network chatter • Slow propagation of the session means the user has a bad experience • You could be moving lots of data around – Our sessions were huge
  • 44. Sticky Sessions • Works but you now need to worry about a machine being overloaded while the others are idle • A machine failure logs out everybody from that machine • You have be very careful when configuring – If all IP addresses go to one server then you essentially have one company per server
  • 46. When to Cache • Our platform made extensive use of caches • That has to be good right? • Not in our case – Items were cached by Java – Shared state posed a problem when adding another server – Yes there are Java based solutions but all you are doing is adding complexity
  • 47. ADMITTING YOU HAVE A PROBLEM
  • 48. It Won’t Love You Back • Never fall in love with your technology. It will break your heart. • You must always challenge your assumptions and be prepared to throw away something – Hard to throw away your ‘baby’ – Remember it is just a bunch of 1’s and 0’s
  • 50. Basic Premise • Every web application follows the same basic flow: 1. User makes a request 2. Validate the request 3. Grab some data 4. Process it a bit 5. Build a Page for the user
  • 51. Guiding Architectural Principles • Initial deployment would be on 3 machines – Forcing us to understand how we are going to scale upfront • Servers must be stateless • The database owns all the data • Caching is an explicit choice to solve a real problem • Always use the right tool for the job • Minimize complexity
  • 52. Other Goals • Zero downtime deployments • We wanted to be able upgrade customers one at a time • Maximize developer productivity
  • 53. The Target Load Balancer Web Server Web Server Web Server Background MemcacheD NAS Processing Cluster Device MySql MySql Master Slave
  • 54. The Language Choice • Why PHP – Faster code/debug cycles • This has increased our productivity – Zero downtime deployments • We have patched running servers multiple times in a day and nobody has noticed anything – Shared nothing philosophy • Forces a good frame of mind for server development
  • 55. Doesn’t PHP Suck? • Languages don’t suck only the developers using them do • PHP isn’t perfect – Google ‘why php sucks’ for an extensive list • But PHP doesn’t scale – Remember, languages don’t scale … – If you don’t believe me ask Wikipedia, Facebook, Digg etc.
  • 56. Sure but PHP is Slow • If your web application is not database bound then you are probably doing it wrong • Yes Java might perform at some things but that will not be a limiting factor
  • 57. Surely There are Down Sides? • Because PHP does not have strong typing you need really good error detection and reporting – We will do another talk on our struggles and solutions • Coding standards are a must since PHP lets you pretty much do whatever you want – Naming conventions are super important – Don’t start a religious war over bracket placement. There really is only one right way 
  • 58. The Framework • We use Codeigniter (CI) • Simple MVC framework – The code is very easy to follow • Works out of the box, but is very extensible – Strictly follows the Open/Closed principle – We have extended CI a lot to meet our needs • Doesn’t require learning anything but PHP
  • 59. Using the Right Tool • Have Apache (or a faster web server) server all static content • A Network Attached Storage (NAS) device was used for a shared file system. – This makes life a TON easier • Have your web servers serve requests • Move background work to another server
  • 60. The Problem • We had about 120 customers and we couldn’t just go away to do what we needed to do – Not a bad problem to have
  • 62. Step 1 • We wrote a controller that would forward requests to the new code base • GET requests could be easily forwarded • POST request were a bit more complicated • This step allowed us to start developing the new platform AND keep releasing features
  • 63. Step 2 • Start migrating customers to the new platform • We put a proxy server in front of our old and new platforms. • We then proxied specific requests to the version they were running on
  • 64. The Setup HAProxy Express Achievers Platform Platform MySql
  • 65. HAProxy • If you don’t have it installed go back to the office download it and install it! • It isn’t just a load balancer – We can move specific traffic to specific machines for whatever reason – We have a machine with profiling capabilities that we have used to profile production problems – Fine grain control over your request
  • 66. We did it! • It took us almost 6 months to migrate every customer but we did get there • Our productivity has improved • And we have an architecture that we know can handle whatever we can throw at it – At least in the short term
  • 68. Scaling is Hard • Don’t make it harder on yourself – Reduce complexity – Understand your database – Have an upfront strategy to deal with state • We picked stateless but you don’t have to
  • 69. Never let anybody tell you a language or framework does or doesn’t scale. It is all in the details