building_in_the_open

Choosing a technology stack to build microservices is not an easy task. Large, batteries included frameworks like Spring, Rails or Django don’t feel like the fit the bill anymore. The Spring framework for example feels like an antiquated and excessive choice for building microservices. It can easily get sluggish startup times the more complex your dependency graph gets and just using Hibernate/JPA makes it unbearably slow to start. Using Spring also comes with a mental overhead, not just a startup one, since it aims to facilitate more enterprise-y and monolith-y applications, meaning even simple stuff require either some expertise or some waddling through documentation a bit too often....

Product development is one of those underrated activities that don’t get enough credit. You never hear people advising to close you IDE, put down the iPad and just think about the problem you’re trying to solve and what your users want and when. Product development is the process of discovering the need and exploring how the solution that addresses it looks like. When this process produces results everything else falls into place....

Thalasio.com is a web application targeted to sailors and yacht owners. It’s an app that helps you find interesting places and plan your boat trips according to your tastes. The app is an offline first Progressive Web App based on Angular that talks to a Django API. The prototype was built in the course of a month or so but finding out how to build content for it has proven a frustrating process....

With the system architecture more or less finalized, at least the first version of it, I now need to make a decision about the stack of the system. getlabeltext.com microservice architecture diagram v0.1 Obviously some parts will be pure python: the classifiers are built on Pandas and Scikit but the rest of the system will probably need to be built on something more manageable: flask is not a good web framework and Django is probably overkill....

Getlabeltext.com is a cloud text classifier. Text classifiers are nothing more that statistical functions that accept text as input and product a label as output. To do that text classifiers rely on an internal “database” of text tokens and their frequencies. This “database” is built during the training phase and can be re-used for every run there after. Training classifiers is time consuming and usually requires large amounts of data which means getlabeltext....

Too many ideas go unrealized. This is the start, a promise to myself to build and release to the world three fully built ideas that have been gathering dust inside my head. Each and everyday, brick by brick, line of code by line of code I promise to my self to build these 3 ideas to the best of my abilities or fail trying. The plan is simple, two hours everyday, 22:00 to midnight are devoted to making progress and writing about it....