Blog Posts

Just knowing git and all team members pushing code to the main branch (master) is not a good practice. To leverage the most out of git, it is a good idea to do feature branching and follow a branching model. GitFlow is one of the options for doing a feature branching model but it is not so straight forward, In this blog post with a video and presentation I would elaborate on how a team can use simplified gitflow and get the most out of using git.

The process of getting a completed feature or bug fix code from the development environment to your web servers is web software deployment. We have been deploying code in various ways, a decade back we were used to uploading our files using File Transfer Protocol (FTP). I would not considering copying files from the development machine to a web server a form of automated deployment, basically it was a necessary evil at that time.

If you still use FTP at this time like 22% of Nepali developers you really need to move on. In this post I will briefly mention some deployment tools and try to analyze their pros and cons. Still as the title reads the best automated deployment tool is the one that best fits your needs.

We have seen many technology software products coming, some coming up as the next big thing, some
a multi-tenant Software As A Service (SAAS). Sometimes I see lots of new, useful and innovative
products on Product Hunt and think how would they have planned such
amazing products. If you are planning to build your software product, this post will unfold why
you should make your web Application Programming Interface (API) working first.

"This feature we deployed last week was working fine till yesterday now I have no idea why is it not working!" This is like a typical sentence you hear from developers when there is no logging in place. It can be to a great extent solved by having automated tests, still having logging and monitoring gives you a different viewpoint. In this post, I am going to reveal the importance of having logs for your code and monitoring your code to cut down the firefighting time for bugs and errors by huge margins.

Getting code done for a feature from developer's machine to production in less time is a quality of efficient
tech/engineering teams. Automated deployment with tools like capistrano or fabric makes deployment an easy task than a dreaded operation where you miss one step and then screw up on production. This post will highlight things to consider when you deploy a new major feature that involves some big code and database changes.