The sample code associated with what follows can be found on GitHub.

One of the biggest paradigm shifts in software engineering, since the invention of the computer and software that would run on it, was the idea of a MVR (minimum viable release) or MVP (minimum viable product). With the lack of internet access becoming the exception in developed countries, it becomes more and more powerful to put your product out there on display, and to design a way to continuously make improvements to it. In the most aggressive of circumstances, you want to be able to push something up to a source control server, then let an automated process perform the various steps required to actually deploy it in the real world. In the best case, you can achieve all of this with zero downtime–basically, the users of your service are never inconvenienced by your decision to make a change. Setting up one very simple example of that is the subject of this post.

The sample code for this post can be found on GitHub.

While we can always install PostgreSQL on our host machine, it’s a much cleaner solution to create something like a local virtual machine with Vagrant or a container using Docker. That way, any changes we make to the database and then forget about are not around as soon as we destroy either the container or the virtual machine. It is one more way to tighten that feedback loop we need as developers.

Elasticsearch, Logstash, and Kibana, commonly referred to as ELK or the Elastic Stack, is a set of tools that can, well do a lot of things. It is most famous for its logging and analytics capabilities.

In our last post on simulating a cloud environment on your local machine, we saw that we could use virtual box to create a virtual machine that could both talk to your local computer, with its own IP address, and to the internet.