If you want your blog’s tag list to also show the tags' frequency, what is better? Adding the very specific feature of frequency computation to the blog engine or making it possible to supply a custom function that takes the whole program state and can return a new version of it (including e.g. tag frequencies)? I want to argue that in this case the latter is far superior.

This article is about "the death [of productivity] by thousand cuts" - about the many obstacles that make enterprise development unnecessarily slow, costly, and painful. And it is about the "invisible cost" of ignoring them. I look at the top obstacles that we encounter and at what we could do about them. I argue that we must prioritize great developer experience and invest into our tools and into simplicity - and that this will yeld benefits both to developers and to the business. Those in power need to realize that developer happiness isn’t about perks, huge monitors, and relaxation pods (though those would be cool!). It is, to a large extent, about our ability to do our job without hindrances and thus it is about delivering more value, faster.

Our Java and Spring webapp may take 5-10 min to restart after a change on my PC, especially when something else (such as IntelliJ) is using the CPU. On Friday I was trying to factor out a new endpoint and it took me about three attempts to get it right. Every time I had to wait for the behemoth to restart to discover that my code was still broken.

And that is why I love Clojure with its interactive development, which provides me an immediate feedback. You could argue that if only I knew Spring better and were a better programmer, I could have made the change right the first time. And you would be right. But I am not that good and, even though I like learning, I do not feel like learning Spring perfectly before coding anything. (I would actually prefer not to have to learn Spring at all, but that is another story.)

Fulcro’s stateful components serve normally both as elements of the UI and to define the data model, i.e. data entities with their unique IDs and attributes. And that is what you want 95% of the time. But what if your UI and data model needs diverge?

We will take a look at what different kinds of divergence between the UI and data entities you might encounter and how to solve them.

Updated: 2021-04-17

A decision tree to help you go from a problem to the most appropriate troubleshooting steps.

The Gradle application plugin provides you with a run task to run your Java application (provided you have set the mainClassName). But how do you customize it, e.g. by setting extra JVM arguments? No amount of searching helped me so I want to share what I have learned.

The run task is of the type JavaExec and accepts the same settings, such as args, debug, debugOptions, jvmArgs, environment, systemProperties. And you can configure it simply by declaring it:

What makes a great team? How to make our teams great? I want to contribute to the answer by sharing the experience of the best team I have ever been on. This team of 3 + 2 has challenged the established way of working, bringing development in-house and together with the business, replacing a shelf product with a purpose-built one, going from on-premise to the cloud and from e-mail to Slack, from Java to JavaScript, with the first production release being a single product page "pasted" on top of the existing application. We were productive and happy.

So what was so great about this team? In short - problem, people, power (and fun).

Once upon a time, the Spring Framework provided a much more lightweight and flexible solution than J2EE. Even in around 2013 I was happy to learn in detail about the then new Spring 4. Nowadays, 7 years later, when I see Spring, I get a panic attack. Annotations and @ComponentScan have replaced XML with something nicer - that requires a visualization tool to understand your system. And Spring has become a hydra that keeps on growing (and changing) heads. I have suffered through taking over and trying to understand a Spring application written by others. And, last but not least, Clojure has taught me how simple code can/should be. So what are my main issues with Spring?

An extended transcript of my talk at DevFest Norway 2020 (slides here).

Do you also love creating useful (web)apps and get easily frustrated by any friction in the development process? I will compare Redux + REST with a full-stack, component-centric solution based on a graph API (think GraphQL) that I came to love. You might not be able to use the same framework - Fulcro - but you can still look for similar, more developer-friendly solutions that implement some of the same ideas and provide some of the same functionality. We will discuss REST vs. Graph APIs, networking, error handling, and more. (You should have an idea about React, Redux, and GraphQL to gain most out of this.)

Once again I have wasted 1-2 hours trying to figure out where the damn "403 Forbidden" was coming from. Yet, with a little forethought and a few seconds or minutes of time, hours could have been saved on such cases. This one would have been trivial if this was already in place, instead of the original, spartan response.sendError(403):

I would know to look into HomeController and that there is no problem with that particular user’s credentials. I could also search the code for that error message.

In total I have certainly spent days hunting for the source of HTTP errors, especially auth-related ones. So I beg you, when you write any error-handling or secondary-flow code, think about the poor person who is going to troubleshoot it and give her - likely your future self - friendly hints instead of ugly, useless 403 Forbidden / 401 Unauthorized / 500 Internal Server Error / …​. Let’s have a look at what you can do to prevent a lot of frustration and wasted time.

I present three ways of detecting, handling, and showing server-side errors: globally and at the component level.

By default, Fulcro considers only non-200 HTTP status as an error. It is up to you to tell it what is an error and how to handle it.

This is somewhat controversial - as Programming with Pure Optimism in the Fulcro Developers Guide explains:

And, as Tony explained elsewhere (paraphrasing):

In my case, I have an internal application and I encounter mostly bugs and downstream service issues so this approach is a better fit for me than if I had a public-facing application.

Terraform - the popular infrastructure as code tool and language - looks very appealing at start and many people swear by it. However, I have had a great deal of frustration with it, which I want to share here as an input for future discussions of Terraform vs. AWS Cloud Development Kit (CDK) vs. other solutions. (I have written about this already 2 years ago and there is partial overlap between this and the older Pains with Terraform (perhaps use Sceptre next time?))

Originally published at the Telia Engineering Blog

A month ago I have started learning Rust and would like to share my impressions, the good things I have appreciated, and the things I have struggled with. Why Rust, do you ask? Primarily to challenge myself, to leave the land of managed runtimes (Clojure, JavaScript) and to get as close to the metal as you can without assembly. Knowing a systems (&more) programming language is handy, for example for writing fast serverless functions and command-line utilities. Why not Go? For the same reasons why Clojure: it is more innovative, more mind-bending. Go is optimized, I understand, for approachability (and performance, of course) and is popular for writing web services - but it failed to capture the C/C developers at Google it was aimed at, I hear. Rust's focus is on performance and safety, the latter forcing it to take a really innovative approach to the issue of memory management. And some experienced C/C developers swear by it. So Rust already seemed more attractive to me and reading Bryan Cantrill’s Falling in love with Rust and Sylvain Wallez' Go: the Good, the Bad and the Ugly sealed the deal. From the former:

How to share a 3GB archive with a remote client when both might have unreliable connection that doesn’t keep up for the full download? Upload it to S3 using multipart upload with a resume capability and download it from S3 using BitTorrent.

This has been a year of Clojure (and DevOps). Since the beginning of the year, I have worked to persuade my team to adopt Clojure instead of (or rather in addition to) to the current mixture of Java and Groovy, argued to rewrite a key batch job in Clojure (thank you, Monica, for providing the business case!), and did all I could to spread Clojure knowledge and skill in the team and surroundings. It has been a success - the job has been rewritten, we have already benefited from it, and we are finishing a new, Clojure-based micro-service. I have learned a lot about Java vs. Clojure, about the value of business-level tests and "living documentation", about leveraging Spec and property-based testing, about core.async (and error handling). On the DevOps front, I have grown to really dislike Terraform (wishing repeatedly to have a proper programming language instead of the frustrating Terraform DSL and the hacks it requires, not mentioning the nightmare of upgrading providers and Tf itself; 🤞for CDK/cdk-clj), have spent more time then I ever wanted with Kubernetes (and am working hard on simplifying our infrastructure and replacing K8s with AWS Fargate and thus spending less time on operations and more on development), and fell more and more in love with Clojure REPL, whether embdded in a Java app, in an actual Clojure code, or opening the door (securely!) to a "serverless" container on Fargate.