If you’re running a production application, you need metrics. There are great products out there that allow you to gain visibility into how your application is performing, give some nice graphs, and charge you for it. In the Rails community, this is commonly achieved by using NewRelic and Skylight. But for some of us, we achieve visibility by using Prometheus and Grafana that we build and host ourselves.
Most Rails developers should be pretty familiar with this work flow: open up a controller file in your editor, write some Ruby code inside an action method, visit that URL from the browser and the code you just wrote comes alive. But have you thought about how any of this works? How did typing a URL into your browser's address bar turn into a method call on your controllers? Who actually calls your methods?
No matter how carefully coded, reviewed, and tested your Ruby code is, odds are good that at some point you’ll cause a catastrophic failure to at least one system you’re responsible for. How do you prepare yourself? You need a Ruby debugger. In this post, I’ll cover the whole Ruby debugger process—from finding the issue to determining the root cause. Use these instructions for debugging a single Ruby file, a Rails app, or a gem.
Docker Compose is a great tool to develop your Ruby on Rails application locally. It allows you to easily isolate your ruby environment, database, and even Redis if you use something like Sidekiq.
When developing new applications, it’s typical to run into a variety of competitors with similar goals. This is one reason why it is not enough to create an application without ways to monitor and manage it. In fact, usually market leaders emerge rather quickly. So who are these market leaders?
Logging provides critical value to applications with insight to usage, stats, and metrics, and saves us when debugging a problem. But we often leave logging to poorly implemented afterthoughts. So what should we know to get the most out of our logging? We will look at the Rails logger and some logging best practices.
Troubleshooting is a critical skill for developers and DevOps. As our software grows more sophisticated, our problems do too. The cloud adds a new layer of complexity since we need to know how to find a problem that doesn’t occur locally, but has cropped up on a remote system.
Because Ruby is an object-oriented language, we tend to model the world as a set of objects. We say that two integers (x and y) are a Point, and a Line has two of them. While this approach is often useful, it has one big problem. It privileges one interpretation of the data over all others. It assumes that x, and y will always be a Point and that you'll never need them to act as a Cell or Vector. What happens when you do need a Cell? Well, Point owns the data. So you add a your cell methods to Point.
Using the right Ruby interpreter to run your programs can make all the difference. Unfortunately, it can be tough to find resources about different Ruby interpreter options, or about how to choose the right one.
There are many things to praise about the Ruby language: adherence to the object orientation paradigm, simplicity, elegance, and powerful meta-programming capabilities. Unfortunately, performance isn’t top of mind when people think about the many qualities of the language.
