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In my previous post, I talked about my studies on Kernel Development with a simpler Unix-like OS, called xv6. After finishing the MIT course 6.S081 Operating System Engineering (available online), I decided it was time to learn how to build the Linux Kernel. I joined a free software group (FLUSP) at the University of São Paulo (USP) and started taking a course on Free Software and Linux Kernel Development. In this post, I’ll detail the environment setup I utilized for creating and testing my first contributions to the Linux Kernel.

After years of working in high-level development, I decided it was time to delve deeper. I decided to learn more about how Operating Systems are built. This is my inaugural article on the topic, and it covers how to compile the necessary tools and run the XV6 kernel for a RISC-V machine/emulator.

In my last blog post, I shared the latest tool that I have added to my arsenal - Apache Arrow (or the libraries based on it). In this post, I will delve deeper into the topic and demonstrate some of the techniques I employed.

In the field of Data Engineering, the Apache Spark framework is one of the most known and powerful ways to extract and process data. It is well-trusted, and it is also very simple to use once you get the infrastructure set up. Understandably, most engineers will choose it for every task. However, in a lot of ways, it can be overkill. And a very expensive one.

This is a (small) presentation I gave to my coworkers at CEPESC. At the time, most of the software there was written in Java, and our team (researchers from the Federal University of Brasilia) was developing in Python. I was advocating using Golang in some performance-critical areas of our system.

If you want to write LaTeX on your machine, VS Code is a great option for you! Installing all the necessary packages is a simple process. And with the power of Git, you can sync with web-based editors like Overleaf, and have satisfying versioning and backup.