In growing companies, as software systems become complex and extensively engineered, maintenance can be a challenging problem. Moreover, when high profile bugs arise and/or a lack of system availability arises, it can have disruptive consequences on a business. Hence there is little room for mistakes in these crucial systems.
Howdy, lazy bum! Enjoying the ReactiveX magic? Want to take a look at polling?
I’ll be walking you through a solution I put together for one of our up and coming apps! It works rather well, I learned a lot, and so far no complaints…although there are no users yet either!
Feeling quite charitable, I’m going to let you in on some useful bits and pieces as we build up to polling: threading, late subscribing, replay, manual re-triggering and error handling (a must for preserving replays).
The Relational Model & SQL
The relational model was proposed in a paper published in 1970 by Edgar Codd, a computer scientist working at IBM. In previous years, some storage systems had already emerged, but the relational model was first proposed with a strong theoretical basis.
As part of my exploration of a minimum set of devops tools, I’ve been learning how to stack containers full of Rails apps onto the Docker. There are plenty of examples of how to get started with Rails and Postgres on Docker, even one from the whale’s mouth, as it were. Working from this example, it was pretty clear to me that one of Docker’s major strengths is that it makes it really, really easy to get something running with a minimum of fuss; it took all of about a half day to learn enough Docker to hoist anchor, and even tweak a few things to my liking. One thing kept nagging me about the Docker example, though, and that was a warning from bundler when running docker-compose.
Software Engineering is about more than just writing code. It is a complex process that has a lot of moving parts. Requirements gathering, planning, testing, deployment and source control management are just a few of the pieces to the software engineering puzzle. So how do we manage all this complexity? Software methodologies come to the rescue.
In the past we would often treat a server as a machine which has a variety of roles. A single server may be responsible for serving web content, email, processing background jobs, and even hosting a database system. Your application is really only one of the many things that runs on that machine.
A common way to describe requirements on Agile projects is through the use of user story mapping, and, as a result, user stories. This post will not cover this process, but rather the process of taking an existing set of user stories and leveraging them within our development workflow to ensure that an application is built as accurately and efficiently as possible. To this effect, we will set up tools (Rails, RSpec, Capybara, FactoryGirl, and Guard, to be precise) for implementing our app using behavior-driven development. Structuring our app in this way gives us much better odds of producing robust, low-defect code that delivers on the requirements we set out to build.
I use Chrome extensions all the time and decided it was time to figure out how to make my own. I found it to be incredibly easy and I’d like to share with you some of the basics, as well as an example of an extension I made. Let’s get started!
I work from all over the place: Home, on public transit, the office, coffee shops, etc.
A big challenge to developing android apps in an environment where my laptop and phone are on different networks (wifi vs. LTE, or laptop tethered through phone) is the inability for my phone to see the API server that is often running locally on my laptop. Here is a simple tip to allow your phone to hit the backend over ADB and a usb cable.