Mauri870's dev blog

Nov 3
AMD 2.0
We finished the full rollout of a new version of our AMD project, let’s find out the improvements made alongside some implementation notes!
Mar 6
O(n^2) Redis memory usage with Laravel Horizon
O(n^2) again, now with Laravel Horizon memory usage.
May 9
Plan9 br-abnt2 keyboard map
This is a quick post about a new Plan9 keyboard map, supporting the brazilian ABNT2 layout.
May 3
Writing an Asterisk PBX module in Rust and C
Asterisk modules are commonly written in C, but what about writing an Asterisk module in Rust? Let’s find out.
Dec 5
Asterisk leaking resources? No, it's gsutil :'(
This week we solved a resource leak in our asterisk images reserved for call handling. Here’s the path we follow to mitigate the issue, which we find out to be related with the gsutil command line tool.
May 31
Plan9 on raspberry pi 3
Plan9 is a research operating system from the same group who created UNIX at Bell Labs Computing Sciences Research Center (CSRC). It emerged in the 80s, and its early development coincided with continuing development of the later versions of Research UNIX. Let’s install it in the raspberry pi 3!
May 24
Audio Spectrograms in Tensorflow
A Spectrogram is a picture of sound. A common approach for audio classification tasks is to use spectrograms as input and simply treat the audio as an image. After several tries I finally got an optimized way to integrate the spectrogram generation pipeline into the tensorflow computational graph.
May 21
How to export the CIFAR10 model to Tensorflow Serving
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. In this blog post I’ll cover how to export a trained CIFAR-10 tensorflow model to Tensorflow Serving.
May 19
Writing a Golang client for the Tensorflow Serving Inception model
Tensorflow Serving is the most optimized way to serve a Tensorflow machine learning model in production. The official tutorials only cover the python client, so lets implement a Go/Golang one.
May 13
Using Opentracing/Jaeger with Laravel
Microservices become the new standard for scalable and maintanable arquitectures. Monolithic aplications are splited into smaller pieces to keep things simple and decoupled. Tracing comes in hand when you need to aggregate the events during the request lifecycle between a single or multiple services.