Software developers and software architects have, for a very long time, stood on opposite sides of the “whose is better” competition. They have completely different beliefs, with each vowing that theirs is the correct one. Some swear by Java as the holy grail of backend; some worship Go as the right solution to all your backend problems. But, really, is there one right answer? Apart from the tools that you use, the architecture you will be using differs from company to company.

Being a UI developer, I’ve learned one thing: It doesn’t matter how carefully you write your code. Suppose you’ve double-checked that you defined and called all functions the right way or followed all the best practices. Even then you’ll see that a tiny variable can sneak behind and create an error. Now, suppose you find out that for some unknown reason a form validation or submit button isn’t working.

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 today’s post, we’ll learn what gRPC is, when you should reach for such a tool, and some of the pros and cons of using it. After going over an introduction of gRPC, we’ll dive right into a sample application where we’ll build an Elixir backend API powered by gRPC. Let’s jump right in!

“All code and no logging makes John a black box error-prone system.” Logging is a key aspect of monitoring, troubleshooting and debugging your code. Not only does it make your project’s underlying execution more transparent and intelligible, but also more accessible in its approach. In a company or a community setting, intelligent logging practices can help everyone to be on the same page about the status and the progress of the project.

If you take a long hard look at the DevOps movement, you will find it actually divides neatly into two sub-movements. The bigger and often noisier of the two is about technology, advocating for the latest and the greatest tools and techniques, be they Cloud, CI/CD, Serverless, or Containers. The smaller sister, however, is much different, stemming from Management Theorem and focusing more on processes.

Finding slow JavaScript code can be a tricky problem to solve. Small code changes can have a big impact on the performance of your code. Fortunately, many different approaches can help you nail down the exact source of the problem. In this post, you’ll learn about three methods that’ll bring you the results you’re seeking. You can trust manual code inspection, but that has its disadvantages.

Rostyslav Kosmirak is a .NET developer from Ivano-Frankivsk, Ukraine using Rider and Visual Studio IDE. Kosmirak was not looking for a Dynamic Code Profiler when he came across Prefix. Kosmirak explains that initially he was searching through Google for a log management system when he stumbled on Prefix. Upon downloading, Kosmirak discovered hidden performance problems in his code before they manifested to actual performance problems.

In today’s post, we will be looking into a software design pattern called Facade. When I first adopted it, it felt a little bit awkward, but the more I used it in my Rails apps, the more I started to appreciate its usefulness. More importantly, it allowed me to test my code more thoroughly, to clean out my controllers, to reduce the logic within my views and to make me think more clearly about an application’s code’s overall structure.

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. I don't have kids yet, but when I do, I want them to learn two things: Whether or not you believe that the singularity is near, there's no denying that the world runs on data.