In my previous post I explained how you can get started with Container Apps. The one missing piece of that puzzle is how you can utilize a queue behind to dynamically scale your workload based on items in a queue! This has been one my most difficult blog items so
Recently I've been working a lot with different AI Models for a variety of use cases, ranging from simple object classification to massive crowd counting models. While working with these models, I saw that it is always difficult to implement a model in custom code since the Architecture is never
For a new project I am working on, I am utilizing a Queuing architecture where jobs come in and a cluster of containers is processing work on this queue. Each job takes an item from a queue, runs the item through its AI pipeline and spits out a JSON response.
Did you find yourself ever having to set-up your development environment all the time? Well I did as well! What if I could tell you, you could save many minutes each day by automating this? Enter the world of Windows Terminal and WSL! 😎 Requirements WSL Environment For this post we
Dapr is simply amazing, allowing you to interact with libraries that otherwise take a couple of hours to implement or even days depending, on your level of comfort with them. Next to that, when you would utilize libraries, you also need to take care of correct authentication, error handling, and
Once in a while a new project comes out that I am totally hyped about! Dapr is such a Project! In this article I would like to go in-depth on how we can quickly (< 10min!!!) create a Microservice that will send an email through a Microservice invocation mechanism! Dapr Introduction
Typescript is quite cumbersome to set-up… it's not built in in Node.js but it is important to write stable code with type checking. Since I write a lot of Typescript projects, it's quite handy to have an explanation on how to set-up a typescript project quickly. For this I
Running CUDA on the Windows Subsystem for Linux (WSL) is not a trivial task seeing that it requires the GPU to be available on a Virtual Machine. In this article I go in more detail how you can get your GPU working in WSL through something NVIDIA calls "Paravirtualization" 💡 It