This is the last part in our series of blog posts concerning the development of an Alexa Skill. If you missed the previous parts you can catch up by reading part 1 here, part 2 here and part 3 here.
Every student group that has worked on a software project can retell the following situation: you’re one week ahead of the deadline, every team member has spent the last weeks working on their part of the project. So far, everything looks great – every module works on its own, the GUI is designed and implemented, the database is modeled and set up, client and server are both running smoothly. All that’s left is combining all the bits and pieces to see everything in action together. Easy, right? Fast forward another five days, it’s the weekend before the final presentation: the air is thick with panic with everyone furiously debugging their code, solving merge conflicts left and right while trying to get the project to some kind of working state that will at least survive the demo. Things that were already working in isolation are now broken and quite a bunch of features that were an inch close to completion will never make it into the presentation. So what has gone wrong? And what have we done to prevent the same from happening with our Alexa Skill?
In this blog entry we take a look at Travis CI, Jenkins, Gitlab CI and Buildbot and evaluate their benefits and downsides when trying to build a content heavy project with it (e.g. games). Continue reading
Welcome to part four of our microservices series. If you’ve missed a previous post you can read it here:
IV) Continuous Integration
V) Lessons Learned
In our fourth part of Microservices – Legolizing Software Development we will focus on our Continuous Integration environment and how we made the the three major parts – Jenkins, Docker and Git – work seamlessly together.
In the the course Software Engineering and Management and Interactive Media at Stuttgart Media University, we launched an interactive web application called Emoji College.
The following blog entry is a brief description of what is going on in this project. The main focus relies on the implementation of a continuous integration pipeline with TravisCI and hosting with AWS. As newcomers in dealing with AWS services it was not easy for us to get started. We have had to try a lot and have paid too much money for the services. Therefore it is our mission to explain the most important steps during the setup of AWS services easily and mention all the lessons learned. So far, there is no easy and understandable guide as we needed it.
Introduction to the Project
It is becoming obvious that chatbots are quickly emerging to the next Big Thing. This is especially evident by the recent flood of publication of software development kits by major tech companies to encourage developers to build applications for their ecosystem.