Software Leviathans and the weird dominance of good enough.

One day in Spring 1989, I was sitting out on the Lucid porch with some of the hackers, and someone asked me why I thought people believed C and Unix were better than Lisp. I jokingly answered, “because, well, worse is better.” We laughed over it for a while as I tried to make up an argument for why something clearly lousy could be good.

https://www.dreamsongs.com/WorseIsBetter.html

It has long been wondered why Java took the crown for the ‘enterprise’ language. I can’t really argue on that topic since I came onto the scene long after Java was all there was. This article is about why software leviathans are written in Java more than anything else. 

You have a huge software project to build. What language do you build it in? The prototype was written in ruby on rails by one guy and an Adderal prescription. Now they want you to scale this thing to a 1000+ engineers over 5 years of development. You might think “aha this is my chance, lets save an order of magnitude lines of code and use lisp”, except this story happened in the past and they chose Java. 

Why is it always Java? Sure it’s reasonably fast, but Facebook made PHP work, can’t we at least use Haskell? Since we have the benefit of hindsight, we know that most of the biggest software systems are built in Java. Google built so many leviathans in Java that they bankrolled a new language like Java but with less features. Amazon is based on Java. Netflix is java again. Facebook made their own language and Microsoft is old enough to have existed before Java, but still made their own version of Java, C#. 

The real question should be, “What is Java’s secret?”. 

Java requires a lot of boiler plate

Java just plays well with the major constraints in a software leviathan and at Leviathan scale that is all that matters. 

This one is the corollary of “Java doesn’t support meta-programming”. Creating your own DSL is great, 1000 engineers creating their own DSL is 999 nightmares. Software Leviathans are too big for any one engineering team to understand. Any DSL you create makes your code unintelligible to the rest of the people working in hell with you. I can understand boilerplate written by a monkey, but a DSL written by another software engineer could take me days to understand. When your team gets poached to go work on a startup where the code base isn’t humongous, it’s a lot easier to bring in Java programmers to replace you lot than it would be to get Haskell engineers to figure out your undocumented dialect. 

Google got to the point where they figured Java had too much meta-programming ability so they created Go which is basically Java without inheritance. That is what happens when you work in a leviathan project. You begin to resent the ability of your peers to do anything unusual, because you know it’s just going to be more work for you. 

Adding more onboarding time to understand 1) the functional language and 2) the DSL your team created might push our already long 6 month on-boarding period closer to the 1 year mark. I wrote an article about onboarding time and functional languages aimed at startups, but honestly I don’t think the hiring market is the real reason Java dominates the top end. FAANG is already willing to train new grads to work on their giant software projects. 

It boils down to comprehension honestly. Humans can only comprehend so many things and at leviathan scale the max is a tiny fraction of the entire system. 

In a software leviathan your team constantly works with other teams’ systems. How does this API work? There isn’t any documentation and one 30 minute office hours isn’t going to explain that hair ball. If you all use the same language and that language is Java there is a chance you can open up their code base and figure out what is going on. They probably didn’t do anything you wouldn’t expect like pre-allocating all of their memory and storing all objects into a ring buffer. But if they did do something crazy you can probably figure it out. Besides Java doesn’t have anything like Scalaz so you won’t be surprised by a functor where you weren’t expecting it. 

Lets take the opposite side, away team work. You have been given the glorious task of implementing a new feature. But it’s impossible to do it cleanly without an API change in another team’s system. That team fully supports the change and has contributed 2 paragraphs to your architecture document describing the change to make in their system. But the change isn’t on their team’s roadmap so you are going to have to do it. 

Getting their service to run and pass integration tests in your virtual development machine takes a week. Now you need to navigate their system where they have conveniently used dependency injection to ensure that you can’t know which of the 5 implementations of this interface is in play. Do you still wish the other team could use Clojure? You might never figure out the DSL. 

Have you ever looked at somebody else’s Lisp code and wondered what was inside the variables? Now imagine this is your job and you will spend the next month making a 200 line change to a 100,000 line of code API service you didn’t know existed until this week. Except this will happen every quarter for the rest of your career. 

People complain about how Java forces you to write the type of things everywhere, but for software leviathans this is a benefit. I can see helpful type signatures everywhere, whether I’m reading your code in my IDE, an email, an excerpt in an arch doc, or in a Slack message you sent me at 3 am. 

Java and Go are great in Software Leviathans. You don’t have to worry about stumbling upon a programming mystery created 10 years ago by a disgruntled new grad. You can expect a consistent syntax and language whichever microservice you are working on. The code has self-documenting types that are ‘easy’ to understand. Honestly, they are a lot of benefits which make a tough coding environment a little more manageable.