Consulting

Do you need a hand with custom software development in Go or Python? Let us know. We can also provide advice on Programmable Infrastructure such as Docker and on development methodologies and tools.

Training

We teach corporate workshops and courses on software development in Go and Python, as well as on development tools and methodologies including Git and CI/CD.

Research

We do custom research involving cloud native tools and technologies. This includes evaluation of tools and technologies, writing posts, and providing recommendations.

From our blog

Musings on software development in Go and Python, IT infrastructure, Serverless and Cloud technologies.

Taming a Legacy Application with Docker

By Gavrie Philipson on September 28, 2016

I’ll be the first one to admit that I have been spoiled by programmable infrastructure. It becomes easy to forget that not too long ago we used to spend hours upon hours on installing a physical server or VM, when nowadays all it takes is a simple docker run to do so many things.

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Mail to Lambda, Part 1

By Gavrie Philipson on September 25, 2016

For a while now, I’ve been interested in experimenting with the new Serverless fad and see what it is all about. The idea is that you don’t need to care any more about installing a real or virtual server, or even about creating a container image. Instead, you just write some code and deploy it somewhere in the cloud as a function.

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From Python to Go

By Gavrie Philipson on May 13, 2015

I have been programming in Python in one capacity or another since around 2000. That’s almost 15 years. Over those years, I’ve come to know the language fairly well. I originally came to Python from C and Perl, and it was quite refreshing to come to a language that is simple to use, has a consistent syntax and library, and is quite powerful.

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A subprocess bug? Nah.

By Gavrie Philipson on July 1, 2014

A few weeks ago, a colleague came to me with an interesting bug: When running a child process with Python’s subprocess module, no exception is thrown when the child process fails. In essence, what happened was the following (typed at the interactive Python prompt):

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