For quick, scalable, highly-available web services, few options compare to AWS Lambda. Just provide your code, add a little configuration, and you're done! In this article, Milap Neupane will introduce us to Lambda, show us how to get it working with Ruby and the Serverless Framework, and discuss reasons to use — or to not use! — Lambda in production.
Every Rails app has a breaking point; a level of activity that it simply cannot handle. Your braking point depends on big architectural decisions, yes — and also on the tiniest changes committed by your most junior developer. That's why it's vital to regularly test your application's performance under load. In this article, Milap Neupane gives us a Rails-centric introduction to load testing with a powerful open-source tool called JMeter.
Many of the concepts you're already familiar with as a web developer are applicable in Go. In this article, Ayooluwa Isaiah shows us how middleware, templating, and other aspects of the go language work together to create a coherent web-development experience.
You'll probably never implement sorting from scratch. But sorting algorithms are foundational in computer science and have become a standard feature of the ritual hazing...er...interview process for developers at all levels. In this article, Julie Kent introduces us to the merge sort algorithm. She'll show us how it works, implement it in ruby, and discuss its performance characteristics.
Understanding parsers is like seeing the matrix. You start to understand the tree-like structure of your code. You begin to realize that so many language features are just syntactic sugar concealing a simple core. In this article, Alex Braha Stoll will guide us through the world of parsers. He'll explain basic concepts, then use Ruby to implement a simple parser for his toy language, Stoffle.
If you've ever built a UI in Rails, you've probably noticed that views tend to get slower over time. That's because adding features to a UI often means adding DB queries to the view. They add up. Fortunately, Rails provides us with an easy-to-apply band-aid in the form of view caching. In this article, Jonathan Miles introduces us to view caching, discusses when it's appropriate to use, and covers common pitfalls to watch out for.
When you inherit a legacy app with no tests, your first step should be to add them. But that can be a huge task! How do you even start? In this article, José will introduce us to a testing workflow called test-commit-revert (TCR) that is particularly useful for adding tests to legacy systems. He'll show us practical examples and help us set up our tooling for minimal friction.
You're doing some currency calculations in your app. It seems to be working well. But after a while, strange discrepancies emerge. The books stop balancing. People get mad. All because the code treated currency like any other number. In this article, Julio Sampaio shows us which of Ruby's number classes are unsuitable for currency, and walks us through better options.
If I asked you to sit down right now and sort a list of numbers, there's a good chance that you'd intuitively rediscover the selection sort algorithm. It's a simple approach that can have significant performance implications. That's why it shows up so frequently in technical interviews - even though most developers never implement sorting from scratch. In this article, Julie Kent walks us through the selection sort algorithm, builds a working implementation in Ruby, and discusses its performance characteristics.
Whoever first said that "the fastest code is no code" must have really liked memoization. After all, memoization speeds up your application by running less code. In this article, Jonathan Miles introduces us to memoization. We'll learn when to use it, how to implement it in Ruby, and how to avoid common pitfalls. Buckle up!
Building a neural network isn't *exactly* like building a human brain, but it's the closest any of us are going to get. In this article Julie Kent introduces us to neural nets as a concept and shows us how to implement a simple one in Ruby.
Few projects are as enticing or as rewarding as creating your own programming language. It's impractical, sure. But as an exercise, it strengthens muscles that most of us don't get to use very often and makes us better all-around developers. In this article — the first in a series — Alex Braha Stoll shows us how to get started building our own toy language and interpreter from scratch using Ruby.
We've all been there. You're clicking around your Rails application, and it just isn't as snappy as it used to be. You start searching for a quick-fix and find a lot of talk about caching. Take your existing app, add some caching, and voila, a performance boost with minimal code changes. However, it's not this simple. Like most quick fixes, caching can have long-term costs. In this article, Jonathan Miles discusses what caching is and what can go wrong, as well as explains non-caching strategies you can use to speed up your Rails app.
The world is full of linear relationships. When one apple costs $1 and two apples cost $2, it's easy to figure out the price of any number of apples. But what happens when you have 100s of data points? What if your data source is noisy? That's when it's helpful to use a technique called linear regression. In this article Julie Kent shows us how linear regression works, and walks through a practical example in Ruby.
When you deploy a new Rails app, you typically face a double-bind. If you use an easy platform like Heroku, you could create problems for yourself as your application scales. If you use a more fully-featured platform, you risk wasting time on ops that could be spent on your product. What if you could have both: an easy deployment option that is easy to scale? In this article, Amos Omondi argues that AWS Elastic Beanstalk gives us both, then he shows us everything we need to know to get a Rails 6 app up and running on EB.
If software's been eating the world for the past twenty years, it's safe to say machine learning has been eating it for the past five. But what exactly is machine learning? Why should a web developer care? This article by Julie Kent answers these questions.
How often do you think about the bits -- the ones and zeroes -- that make up your app's data? If you're doing web development in Ruby there's rarely any need to. But what if you want to interact with the operating system or a piece of hardware? What if you'd like to understand network protocols or databases? In that case, a solid understanding of bitwise operators is foundational. In this article José M. Gilgado will introduce you to bitwise operations in Ruby, give practical examples of how they can be useful, and finish big with with some fun math tricks.
As programmers we often have to mentally run code. To imagine how a program will behave given certain inputs. This is hard enough for experienced developers. But for juniors? It can seem impossible. In this article, Melissa Williams argues that pry is an invaluable tool for junior rubyists because it allows them to see exactly what is going on as their code is run.
We've all worked with tightly-coupled code. If a butterfly flaps its wings in China, the unit tests break. Maintaining a system like this is...unpleasant. In this article, Jonathan Miles dives into the origins of tight-coupling. He demonstrates how you can use dependency injection (DI) to decouple code. Then he introduces a novel decoupling technique based on delegation that can be useful when DI is not an option.
As a Ruby developer you probably use tools like Sidekiq that rely on concurrency. But would you know how to *build* your own sidekiq, or add concurrency to an existing app? This article will open Ruby's concurrency toolbox and show you how each tool works. It shows you how to solve the same problem in multiple ways, so you can compare tools. And it looks at new tools that might possibly ship with future versions of ruby.