Scala has long been part of the CrowdStrike stack, the primary language in fact. I helped lead the adoption of Scala as we first started to develop our applications back in 2012. In fact it was one of pros for my decision making process of wanting to come to CrowdStrike. Several of the early developers were interested in adopting it as well so it seemed to be a nice fit.
I had come from a company called Gravity, who were also heavy Scala users. It was the primary language there. I was used to it, enjoyed it, saw the power of it and thought I could prevent some of the issues I saw with Scala as CrowdStrike grew. We were doing high scale analytics, batch jobs over Hadoop and our Chief Architect (hi Bissel!) was doing lambda architecture before it was what the cool kids were doing.
A recent quote from one of our senior engineers prompted me to finally write this post describing why we’re transitioning most of our stack to Go and why new services default to Go by developer choice.
Instead of waiting until the end of the this post I should clarify that Scala will not be leaving our stack completely. In fact it will complement where Go does not shine. Scala is a big part of our machine learning / analytics stack. It’s interop with java projects we use, and its ability to provide a nice DSL that our analysts can use still make Scala a solid choice. It’s becoming more of a specialized tool vs the core development language.
I’m going to take you through this from the lens of a Technical Director. A lens where you need to scale a company from the early days of 5 engineers to 200+ engineers as the business grows. It’s about having a maintainable code base where you can have people cross projects easily and get new hires up to speed rapidly.
I remember when I first saw the potential issues of scaling Scala at Gravity back in 2009/10ish. It was close to the end of the day when we had a major issue reported in production that was affecting our large customers. Several of us started investigating and were able to track the source of the issue. The only problem was we had no idea what the code was doing at first. We came across a strange symbol we hadn’t seen in our projects before. The spaceship operator <|*|> . Someone said out loud “what the hell is that?”. There was some other implicit magic going on that wasn’t immediately apparent. A CMD+B to traverse into the method yielded nothing in our IDE as it couldn’t find the symbol (IDE’s have improved here since). A quick googling of “<|*|>” yielded nothing as well. We were stumped and didn’t have sources pulled down. 
The developer who wrote the code was unreachable on vacation so we had to figure it out. We noticed a new library was being included called scalaz, hours later we had tracked down the mystery symbol and grok’d what was going on, made the fix and life was good again. That blip turned a fix that should have taken minutes into a fix that took hours. That was the point I started seeing the split in our engineering team.
Scala is a powerful language, it comes from academic roots and gives enough flexibility that you can easily start writing “write-once” type code. Scala developers typically travel down two paths: You have the “it’s a better java ” camp you have the “I (heart) Applicative Functors” camp.
The “it’s a better java” camp like the terseness of Scala, and the standard features that make Scala generally more enjoyable than Java. There’s functional programming in their new Scala code but it’s not the main focus. The “I (heart) Applicative Functors” camp really takes to their new functional world and begin to expand their knowledge deeper down that path or they bring their already functional backgrounds from places like Haskell.
Based on my experiences you start to split down these camps and have excellent programmers in each so you can’t say one side is superior to the other. On the semi-functional side you potentially have more generalists working across languages, or those who may not want to learn lambda calculus theories to work with an API server.
As an example, this is a code sample from a project we had one of our more advanced Scala developers start:
Some of you may look at that and say awesome, but some will say WTF is that? There were thousands more lines like above. This was to be something the whole team could work on but half the team didn’t want anything to do with it. The developer who wrote it is a brilliant person but the fact it divided half the team was a problem. Luckily this was caught in code review and rejected based on our internal guidelines. It never made it out to production.
As you’re scaling an engineering team this split becomes more apparent when trying to get new hires up to speed. Scala has a lot of rough edges already around getting a build environment, SBT pain, IDE environment pain , release upgrade pain, slow build times, add on top of that a heavy dose of functional concepts required for proficiency and the ramp up time grows and dev output slows down. Now there’s more upfront training from existing developers required which slows things down as well. SBT is also a real sore spot. There’s always that one person who actually knows what the heck SBT is doing and can debug everyone’s issues. I’m aware that Scala is not scalaz and they can be mutually exclusive, but I’ve seen issues with or without it.
It’s also not a question of Scala being “too hard”. I’ve never had someone not be able to learn the language. It’s about the investment. You make an investment in something with the hope of it paying off somehow down the line. Whether that’s faster time to market, higher performance/lower cost, or increased stability. There are specialized places I’ve seen that happen with Scala but not in the general case.
This isn’t unique to companies I’ve worked for. Twitter has gone through the same growing pains, as well as other companies I’ve talked to at conferences and people I know working with Scala. It’s a common theme, in fact. While you can have very high performing small teams going with Scala, trying to grow and engineering organization > 50 is an uphill battle. If you’re already invested in the JVM, Java8 is a solid choice that borrows some of the concepts of Scala to make Java easier to work with.
Other references from larger teams seeing issues:
Is LinkedIn Moving off of Scala? https://www.quora.com/Is-LinkedIn-getting-rid-of-Scala
Former Twitter Platform VP heard saying Java8 may have been a better choice if available when they made the choice of Scala for similar reasons https://www.quora.com/Is-Twitter-getting-rid-of-Scala
and a funny Tweet about the subject:
That’s where Go enters the picture. One of Go’s reasons for existence is to make developers more productive, limit the number of ways you can do something and have a very opinionated view of the world at the compiler level. I fought Go internally for a while. I worried about splintering even more, having another language for people to learn as we already had quite a few technologies in play. We have an internal policy about looking at adopting new technologies when you have at least 3 people willing to support it at 3am if there’s a production issue. After much prod’ing (thanks Sean Berry) and getting past that 3 number, I dug in to the Go world and saw it solved a lot of issues I had with Scala at the organizational scaling level.
Fast build times, small binaries, one file, built in formatting, great tooling, built in test framework, race detector, visual profilers, a nice concurrency model? Wow, sold! We did a sample project in Go that was successful, then another, then another, expanded out the number of developers we had on Go and it started to become the language of choice people wanted to write in. You can jump into any Go project and know immediately what it’s doing. Do I miss immutable types and some of the great features of Scala? Sure do, but I think the maintainability side of the story is too great to overlook with Go. We’ve seen faster ship times, better stability and better test coverage being written.
One of the other benefits of Go was widening the pool of backgrounds we can hire. We can take someone from any language background and have them ramped up on Go in weeks. With the Scala side there’s the JVM learning curve, the Java world of containers, black magic of JVM tuning, profiling tools, etc…
New developers we’ve hired are ramped up in weeks vs months (we have lots of services that operate at extremely high scale, across several divisions). We now have the majority of our services written in Go and one of the last holdouts to move to Go just wrote his first project and said to me afterward “Wow, I read through that library once and I knew exactly what it was doing , I’ve read the Scala version of that library four times and I still have no idea what it does, I can see why you guys like it so much”. That was one of our senior engineers who’s previously worked for one of the largest web properties in the world. This process was a complete bottoms up initiative from our development team who pushed for the move to Go.
We now process hundreds of thousands of messages per second and Terabytes of data per day with our GoLang services. Some try to equate Go’s simplicity with weakness, I’ve seen the opposite. You can do some pretty powerful stuff in Go. There is power in simplicity. The error handling, while seemingly annoying at first, actually has lead to more robust error handling and stability in application code. You can’t just throw something and hope it gets caught somewhere.
Google is also a major investor and having that technical alignment opens up access to additional resources that we can leverage.
I’m not here to bash Scala, or ScalaZ (I love ValidationNel! ) but more to give some real world context of Scala in a production environment over 7 years with two companies. I still use Scala and love hacking in Scalding. Some of our more ambitious projects coming up will most likely be Scala based but I’m just not as sold on it anymore as the core language when trying to scale a fast growing engineering team. Go sits in a place that happens often… when you need small’ish, high performance services. Where you’re doing light transformations, shuffling data around and putting APIs in front of data or supporting systems.
Go just makes it too easy.
If you’re interested in hearing more or chatting, follow me on Twitter https://twitter.com/jimplush
…and we’re hiring
 Code Reviews would have solved this issue as someone else would have stumbled on that symbol and asked for more clarity and understanding. That would have help introduced the library to the team easier than a surprise. Unfortunately, at Gravity we didn’t have required code reviews in place. We do have code reviews in place at CrowdStrike. However, given not every person is on every code review there’s no guarantees.