Posts

Following the subject from my last post, Reflections about Supervised Learning on Security, I put down some more thoughts about the implementation of learning-based systems in the Security domain. This is my extension to the problems and recommendations presented on the paper Dos and Don’ts of Machine Learning in Computer Security (Quiring, et al, 2022). I encourage you to also read the paper, as it’s excellent and provide a lot of insights about how to better build machine learning models....

A common requirement that I face on multiple projects is to safeguard some API endpoints to administrative access, or to provide a secure way for other applications to consume our service in a controlled and traceable manner. The usual solution for it is API Keys, a simple and effective authorization control mechanism that we can implement with a few lines of code. However, when doing, so we also need to be aware of threats and possible attacks that we may suffer, specially due to the usual privileges that these keys provides....

Introduction Kubernetes won the battle for the cloud-native platform and the characteristic that makes me enjoy the most working with it is its extensibility. By providing an open model through the kube-apiserver, without splitting an internal and external interface, we can interact with the cluster and any other system to integrate both from the same application (Controller) and even use custom resources to describe our unique operations, know as the Operator Pattern....

Photo by Joshua Coleman on Unsplash Caching is one of the most popular tools used to scale systems and anyone looking to maintain high throughput, resilient and cost-effective products should understand how to use it because it is financially impractical to apply only compute resources in order to meet the access demands. Knowing the basics about it and what parameters you should be looking when choosing your solution is rarely addressed and hence is the purpose of this article....