Why Programming Should Be Hard

Or… How I Learned To Stop Worrying And Love The Free Monad

“That’s not easy what I just did!” — Carl (River Phoenix) from Sneakers

I hate the word “elegant.” It’s one of those words you hear a lot when talking to programmers, like “refactor” or “trivial.” Like those words, it’s overused. And like all overused words, it’s lost its meaning. “Elegant” (when used in the context of programming) once referred to a program or architecture that was so beautifully simple that it was almost unbelievable. The recursive solution to the Towers of Hanoi is elegant. Most code isn’t. We sure like to use that word a lot, though.

I hate “elegant” because it’s become a rhetorical bludgeon used against complex code that must be complex in order to accomplish its task. Not every problem has a Towers-of-Hanoi-esque solution. Most don’t, or at least the world is too short of geniuses to invent truly elegant solutions to every problem. Also, programming problems are becoming more complex every day. My team writes cloud software, which means we need to write code that runs across hundreds or thousands of independent compute nodes and somehow appears to an end user to accomplish a coherent, unified task. Worse (or better, depending on your perspective), we write IoT software for industrial machines, which means our software has to process hundreds of thousands of discrete events per second and somehow make sense of all that data in a way that can be presented to a human.

In order to manage the complexity of these new programming tasks, we as a community of software engineers must invent new tools. Those tools include:

  • New programming languages with better facilities
  • New programming paradigms (OOP, functional, immutable, reactive)
  • New vocabularies to describe and encode solutions to harder problems (category theory, type-level programming, stream processing)
  • Entirely new types of systems (cluster managers, NoSQL databases, streaming frameworks)

All of these are difficult to learn. Code written in a language you don’t know, using paradigms you’re not familiar with, in vocabularies you have never learned is likely to be incomprehensible to you. If you call this code “inelegant,” you’re not helping. You are making excuses for your own refusal to learn something new and difficult. It’s not a programmer’s duty to make code easy to comprehend for those unwilling to learn. It’s a programmer’s duty to learn, so that they can write and comprehend better and more powerful code.

The reluctance to learn difficult things is understandable, and I can even understand why someone might get defensive about it and start throwing “inelegant” around. But this is ultimately not constructive. Every software engineer that wants to evolve with the industry has to continue to learn. In this post, I’ll talk about my personal learning journey in my career and what I’ve learned about learning, so to speak, from early in my career to as recently as this past year.

The Dangers And Rewards Of Geeking Out

I am a geek. I define “geek” as someone who likes things — often certain kinds of things — just because he or she thinks they’re cool. Geeks often make good engineers, and engineers are often geeks. You can geek out about anything really — I geek out about cooking. I also geek out about software engineering. This has, on occasion, gotten me into some trouble.

Software engineering, like most human endeavors, is a game. It has constraints (i.e rules), and you’re trying to win it (i.e. ship a successful product). Winning games is all about understanding the rules and finding optimal ways to work within these rules to produce the desired outcome. In any sufficiently complex game, the problem space is large enough that there’s plenty to geek out about. An enthusiast for the game of chess might geek out about openings, for instance. I believe this is why many engineers are also gamers. Any game can be a dress rehearsal for the real thing.

Where geeking out can go wrong is when it steers you away from winning the game. Most deep dives into a geek-out session begin with the best of intentions: maybe you read about some cool new software engineering technique. Maybe you did a book club on it. Now you’re in a big hurry to put it into practice. At some point though, you stop caring that you learned about this thing in the first place to win the game, and start caring more about doing the thing. This might lead to doing the thing badly, and in particularly bad cases, you and others might rack up a list of failures that are then used as evidence of why the thing is a bad idea in the first place.

My Awkward Unit Testing Adventure

This happened to me with unit testing. When I first read about automated testing — and unit testing in particular — I was immediately sold. At first, I was thinking about the game. If we write good unit tests I thought, we will save countless hours of manual testing time, find bugs earlier, and have code divided into small comprehensible units that are independently tested. Then I — and other like-minded geeks I worked with — started doing it.

The problem was, nothing works like it does in books. When you start working with real software — legacy software in particular — compromises must be made. Engineering trade offs must be considered. The game has to be played and played well. However, at this point I was so geeked out over unit testing that I was determined to make it work by any means necessary. Because it was cool!

The result was a disaster. Thousands of lines of of un-maintainable, often-useless, poorly performing tests were written by myself and others. About the only thing this accomplished was to give ammunition to those who were skeptical of automated testing from the outset. Now they had a real live train wreck they could point to as evidence they had been right all along. The group then entered a sort of testing dark age that took years of concerted effort to recover from. That recovery was still in process when I left that company.

A Better Way

I like to think I learned the hard-won lesson from that experience. A year or two later, I geeked out about Test Driven Development (TDD). As with unit testing, I had read about it in books and various blogs, and I had a concrete idea of how it could improve our software engineering — even how it could right some of the wrongs from the misadventure above. Also as before, I totally geeked out about it. But this time I caught myself and used my geek powers for good.

As with unit testing, I immediately ran into problems applying the practice to actual code. However this time, I kept the game in mind. Ultimately I wanted to make our software engineering better and more efficient. This meant first and foremost that I accept failure as a possibility. If I can’t make TDD work in our code base, I am doing no one any favors by trying to use it anyway because it’s cool.

Then — and this was my epiphany — I accepted that programming is supposed to be hard. I decided to have some faith in the people that wrote these books and blogs — that they were able to make these technologies work with real software. If I stumbled early on, I told myself, the blame is likely mine, not the technology’s. I kept trying, and I practiced. I referred back to the literature and sought out more reading and advice when I got stuck. Ultimately, I reached the point where the technology I geeked out over met with my goal of playing the game more effectively.

Obviously healthy skepticism of the technology is fine, but don’t let your skepticism rule you. Too many people do this. People with unhealthy skepticism are the same folks that call necessarily-complex code “inelegant.” Take the time to watch the first 3:40 or so of this youtube video. Most of it is about how to play guitar — another thing I geek out about — but the first part is great advice about getting good at anything difficult and dealing with skepticism — yours and others’. It’s almost identical to my own mental model on the subject.

Once you have a comfortable mastery of the technology and a decent track record of applying it to real problems, evangelize it. Start with people more likely to accept it and less likely to show unhealthy skepticism (fellow geeks!). Pretty soon, you’ll have built a tribe not only of believers, but fellow experts that can help spread the use of the technology throughout the organization, and ultimately move a step closer to winning the game.

You Said Something About A Free Monad?

This brings us to the final chapter of our story. In my current position, I am fortunate to have a lot of very smart programmers working for me. One of them, Phil Quirk, I have worked with for several years, including the company involved in my anecdotes above. He likes to geek out about category theory and functional programming. He also believes that they allow him to write more powerful code that’s easier to reason about. For a long time, I stubbornly disagreed with him about this. This is the story of how I was wrong.

I am a firm believer in writing easy-to-read, easy-to-maintain code. Clean Code — one of my favorite books — deals with this subject exclusively. Code is read and changed a lot more often than it is written (which is one time), so of course any engineer would optimize for readability and maintainability. In my discussions with Phil however, I caught myself confusing “easy to read and maintain” with the misuse of the term “elegant” that bothers me so much. I was calling Phil’s code “inelegant” for the same reasons my code had been called that so many times before: because I lacked the patience to learn the vocabularies necessary to understand it. When I realized this, I decided to give Phil and his categories a fair shake.

A book club (on the excellent Scala With Cats) and a few programming experiments later, and I am not only a convert, but I am ashamed I dug in my heels for so long. In the book club, I raised the question to the group “is it fair to require anyone that wants to play in our code base to learn these concepts, even though they are difficult and unfamiliar?” The unanimous answer: of course. Knowing these concepts makes us better at playing the game. If you want to play the game at our level, you must know them.

Phil also loves Dr. Strangelove. I hope that the alternate title of this blog post will suffice as an apology.


Programming is a constant learning journey, at least if you want to continue to work on new and cutting-edge problems. Somehow, the ethos of “false elegance” has crept into the software community, and this sometimes causes us to be inappropriately cynical about new techniques and ways of reasoning about problems. In the worst cases, we disparage these new methods, because if we try to use them and fail, we might look foolish. We should stop this and embrace increasing complexity as an unavoidable fact of technology itself. Only by continuing to be smarter than the problems we’re trying to solve will we continue to win the game.

In future blog posts, I and others will delve into some of the technical details behind some of the technologies I mentioned above. One might even involve my adventures using the free monad in database programming. In them, we’ll show how embracing necessary complexity empowers you to solve difficult problems with — dare I say it? — elegance. Stay tuned!

KUKA Careers: What I Do As a Cloud Engineer

I’m Devin and my title is Principal Software Engineer on the Cloud team. Here’s what I do at KUKA and why I enjoy working here.

I work on the backend team, a small group of three people developing the server-side components of the KUKA Connect web application.

KUKA Connect is a web app that gives our customers the ability to monitor their KUKA robots, and one day to preemptively diagnose potential failures.

The People

Every person on the team and in the office is enjoyable to work with: pleasant, helpful, and capable.

We have a cooperative atmosphere, and on our backend team we often do “mob programming” where we go into a room together and have a group coding session to implement important features. This practice 1) brings the team together, 2) gets everyone up to speed on coding style and feature architecture, and 3) facilitates better code through the group dynamic (three heads are better than one).

I’ve never worked at a company that fostered such a collaborative environment. Oftentimes it is wrongly thought that having developers code together slows down velocity: the opposite is true in my experience. By working together, obstacles are overcome more quickly and development effort is more focused.

We have some talented people on our team, and these people share their wealth of knowledge through mentorship, so everyday affords the opportunity to grow and learn.

The Technical Aspects

It’s one thing to work with great people. We’ve got that. Pair it up with cutting edge software development practices and tools, and now you have something really special.

We are writing a scalable web app that is global in scope with massive data pouring in every day. We need near 100% uptime; we need to be able to dynamically scale up the web app based on load; and we need to be able to evolve the architecture as we move forward.

To solve these challenges, we employ paradigms and tools that are industry leading: test-driven development, event sourcing, the concept of a log (we use Kafka for this), a distributed and highly scalable database, data streaming (Akka), and microservices. This is in addition to fundamental practices like dependency injection and interfaces/protocols/traits.

We deploy our system to Amazon Web Services (AWS) and manage our app through Kubernetes with Docker containers. Each microservice is packaged up in a Docker container and then one or more replicas of it are deployed by Kubernetes as pods to an AWS instance in our cluster.

We capture live metrics on all important aspects of our app and have a huge TV that shows the DataDog dashboard for our different tiers. When something goes wrong, we know it quickly and can fix it.

The bottom line: being on this team has leveled up my software experience by leaps and bounds.

The Product

KUKA Connect is our first product. We just released it. Industrial robots like the ones KUKA makes have been around a long time and do things like assemble vehicles.

But the software for monitoring and managing these robots has developed more slowly. We are changing that with KUKA Connect, giving our customers unprecedented ability to manage their robots: visualize what each robot is doing, know when maintenance milestones are coming up, find out when a robot hits a critical fault, and see important operating data about their robots.

We have already been getting feedback and the good news is people love the app and want even more features. So we have lots of great work to do.

The Next Step in Your Career

We’re hiring, and you can go to our Careers page right here to see all the positions we have open.

If Cloud engineering or another role sounds intriguing to you, apply for it! Look forward to seeing you here.

Devin Rose