With the move to SOA, IGN's API engineering became a traditional Java/Ruby shop. We introduced Scala to the team in August '11. As of April '12 we have our major services running on Scala, and we could not be happier. I'll talk about the strategic & tactical rationale, gradual introduction to the new language, cultivating experts and mentoring junior developers. We will also cover the common roadblocks the leaders may run into, addressing the concerns of engineers and stakeholders, and building an engineering culture that facilitates innovation and talent growth. Please note that this talk is not a Ruby/Java/Scala religious debate - we believe in using the best tool for the job; and what works for us may not work for every org (which is where the culture comes in). My team's journey from "Holy crap! This looks academic and scary!" to "Let me whip out a service by EOD today" in a matter of months is something I am very proud of, and would love to share it with fellow developer community.

1. Introducing Scala to your
Java/Ruby Shop
My experiences at IGN
Manish Pandit
Silicon Valley Code Camp ‘12
Oct 7th, 2012

2. About me
Manish Pandit
Director of Engineering, IGN
@lobster1234
linkedin.com/in/mpandit

3. About IGN
We are a leading online media and services
company
obsessed with gaming and entertainment.
56MM Monthly Unique Views
737MM Monthly Page Views
20MM Monthly Video Views

4. My Objective
Is:
To share my story of introducing Scala to IGN, and
(hopefully) show you the path to enlightenment.
Isn't:
To incite a functional vs. imperative, or Scala vs. ____
debate.

5. The IGN Tech Stack

6. Best tool for the job
• Front End : JS, CSS3, HTML5, backbone,
Coffeescript, jQuery
• Middle Tier : ZF2 (PHP), Rails
• APIs : Scala, some Java
• Persistence : MongoDB, MySQL, Redis
• Search : ElasticSearch
• Caching : Memcached, Varnish

7. APIs at IGN : Numbers
• ~5 Billion requests a month
• Average Response time of under
20ms on cache misses
• 17 APIs between Social, OAuth,
and Content
• Hardest hit APIs doing about
25K RPM at peak

8. The Kitchen Sink
• CMS – JSPs talking to Oracle DB and some Java
services
• V1 API : Java Services using Oracle DB with
Memcached
• V2 API : Rails based API layer using MongoDB and a
Java/Memcached front cache
• Lots of duct tape like messaging and cron jobs for
simple tasks
• Too diverse of a stack in the API infrastructure

9. The API Evolution : V3 [2012]
• A fresh look at the APIs and IGN’s direction
• First attempt to
– Integrate all content types
– Open up the APIs to external consumers
– Evolve the CMS, traditionally a monolithic system
– ElasticSearch
– Varnish Response Caching
• A learning opportunity for traditional Java
stack engineers

10. Roadblocks
• Resistance to change
– Culture
– Willingness and commitment
• Too many choices – making the right pick
– Involve every one
– Do not decide by committee, decide by learning
– Time box and measure everything
– Be accountable, as you’re looked upon as the
expert

11. The hunt for…
• A runtime as fast, if not faster than Java
• Concise, yet expressive
• Less boilerplate
• Smooth learning curve and ramp up
• Re-use ecosystem of libraries
• Growing adoption and developer velocity
• Built in support for concurrency
• Fast and fun development
• Next level of programming – disrupt!

12. Why Scala : Strategic Reasons
• Evolve the talent brand along side evolving
the platform
• Establish an API platform by replacing
“rewrite” with learning instead of porting
• Start thinking functional
• Align with the leaders in the APIs
• Get involved with a technology as it is evolving
(vs. established). Helps with influence.

13. Why Scala : Tactical Reasons
• Performance tied to cores than processor
speed, i.e. concurrency
• Ideal for API development – (relatively) simple
to handle concurrency and immutability
• JVM based = Performance
• Re-use Java toolkits and libraries
• Concise, yet expressive code
• Actor model makes the difficult parts easy

14. Why Scala : Tactical Reasons
• Richer Collections API
• Traits enabling Mix-Ins and behavior re-use
• Statically Typed w/Type inference
• Functional, but not alien (it can be!)
• REPL

15. Yes, Virginia, Scala is hard : DPP
So, how can you figure out if Scala will be "easy" or "hard" for your
organization:
•Your company has speakers at JavaOne, OSCON, Strangle Loop, QCon: Scala
will be easy
•Lunch-time discussions involve the criteria for moving from a developer to a
senior developer: Scala will be hard
•Your developers can write code in NotePad if they have to: Easy
•Your developers stare blankly or say 3 "Hail Marys" when they hear the
name "Zed Shaw": Scala == Hard
•Developers all follow Dean Wampler on Twitter: Scala Easy
•Your developers come in at 9:15 and leave before 6 and don't check work
email at night: Hard
http://blog.goodstuff.im/yes-virginia-scala-is-hard

17. Picking up Scala : Week 1
• Scala for Java Developers fast-tracked the
learning
• Syntax Familiarity
• Java without semicolons?
def total(nums: List[Int]) :Int = {
var sum:Int=0
for(num<-nums) {
sum+=num
}
sum
}

18. Picking up Scala : Week 4
• Reduce the lines of code, embrace
immutability, use the functional paradigms
built into the language
• Unmystrify the implicits magic
nums.foldLeft(0)((n,c) => n+c)

19. Picking up Scala : Today
• Focus on immutability
• Think functional – with the knowledge gained
from using the functional aspects of the
language, build control abstractions
• Explore and implement ScalaZ
• Keep learning, and applying
• Move all the Actor processing to Akka

20. Less Boilerplate
public class HelloWorld{
public static void main(String... args){
System.out.println("Hello, World!");
}
}
object HelloWorld extends App{
println("Hello, World!")
}
scala> println("Hello, World!")

21. Expressive, yet concise
val x = if(n%2==0) "Even" else "Odd"
val x = for(i <- 1 to 10) yield i*2
val x = for(i <- 1 to 10; if(i%2==0)) yield i*2
val y = 20 match{
case p if(p%2==0) => "Even"
case _ => "Odd"
}
val largest = List(1,5,2,6).foldLeft(0)((a,b)=> if(a>b)
a else b)

22. Less pain points
No more dreaded null or throwing unwanted exceptions :
Use Option[T]
def thisMayReturnNull[T](x:T):Option[T]={
if(true) Some(x) else None
}
No more creating classes only to return more than 1 value :
Use Tuples
def doublePair(x:Int)= (x,x*2)

23. Try-catch mess
try{
//Construct a URL which can throw a MalformedURLException
//do something with a URL which can throw IOException
//do something with string encoding which can throw
// UnsupportedEncodingException
} catch{
case mal:MalformedURLException => //something
case ioe: IOException => //something
case e: Exception => //something
}

24. Type Inference
scala> val x = "Sunday"
x: java.lang.String = Sunday
scala> def x(n:Int) = n*3
x: (n: Int)Int
scala> 1 to 5
res2: scala.collection.immutable.Range.Inclusive =
Range(1, 2, 3, 4, 5)
scala> def x = if(true) Left("Yes!") else Right(new
Exception("Didn’t work out!"))
x: Product with Serializable with
Either[java.lang.String,java.lang.Exception]

25. Dynamic Mix-ins
class Home(bedrooms:Int=3,bathrooms:Double=2.5)
trait Garage{
def park(n:Int) = println("Parking " + n + "cars")
}
val someHome = new Home
val someHomeWithGarage = new Home with Garage
someHomeWithGarage.park(2)

26. Concurrency
• Actors make concurrency so much easier
– Messaging vs. Blocking
– Lightweight, 300-500 bytes per instance
– Isolated

27. Scala API Components
• Scalatra
• Lift-MongoRecord for MongoDB
• Casbah for MongoDB
• PlayFramework 2
• Actors for tasks like syndication
• sbt and Maven for Builds
• MongoDB for persistence

28. Other API Components
• Varnish Cache
• Elasticsearch
• Yammer Metrics (ping, healthcheck)
• Swagger (self-documenting RESTful APIs)
• 3Scale for Partner APIs
• IntelliJ IDEA and Eclipse with ScalaIDE
• PlayFramework 2.0 (New!)
• ScalaTest for Testing

29. Challenges with Scala *
• Steepness of the Learning curve depends
entirely on your org culture
• Scala is what you make of it
• http://scalaz.github.com/scalaz/scalaz-2.9.1-
6.0.4/doc.sxr/scalaz/BKTree.scala.html
• Middle Ground between Simplicity and,
well..elegance
* None of these challenges outweigh the benefits. They’re just something to
be aware of.

30. Challenges with Scala
• Slow compilation based on the source
• No (binary) compatibility of dependencies for
the major releases (2.8, 2.9, 2.10(?))
• Tooling not as rich as Java
– Changing (rapidly) with Typesafe investing in
ScalaIDE
– ScalaIDE comes with a Scala Worksheet, which is
like REPL but richer

31. Lessons Learned : Culture
• Culture of Meetups, Hack
Nights and Code Jams
• Being able to connect with
the contributors and
language creators
• Willingness to invest in
learning, evolving vs.
maintaining

32. Lessons Learned : Team
• Small team (~5 engineers)
• Java background helped a lot
• 10% time set aside for skill building
• Learn and share
• It is a commitment
• Communication!

33. Lessons Learned : Material
• Books that have exercises, so you
can quantify your learning.
• Online tutorials
• StackOverflow
• Coursera : A course on Functional
Programming by Martin Odersky

34. Resources
• Books
– Programming in Scala by Odersky
– Scala for the Impatient by Horstmann
• Interwebz
– http://debasishg.blogspot.com
– http://www.reddit.com/r/scala
– http://stackoverflow.com/tags/scala/info
– http://twitter.github.com/scala_school
– https://www.coursera.org/course/progfun

35. scala> case class Me(name:String="Manish
Pandit",twitter:String="@lobster1234")
defined class Me
scala> val me = new Me
me: Me = Me(Manish Pandit,@lobster1234)
scala> println(“Questions!”)
Questions!