Hi everyone! A little late, perhaps, but in this article, I’d like to share that my new project is participating in Hacktoberfest. I have been participating with projects for three years now, and this year was no exception. Today, I would like to talk about this in more detail. Well, let's get started!
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Flock Under Fire: How the Latest Court Ruling Turns Employee‑Monitoring Into Mass Surveillance – What IT Leaders Must Do Now Introduction A U.S. federal judge just declared that the popular employee‑monitoring platform Flock is “indiscriminate mass surveillance.” The ruling has sent ripples through corporate IT, privacy‑rights groups, and regulators on both sides of the Atlantic. In the days after the decision, Google Trends showed a 250 % surge in searches for “Flock privacy lawsuit,” “detect monitoring software,” and “GDPR employee tracking.” If you’re an IT manager, compliance officer, lega
🧛 JLScript — Do Básico ao Avançado Aprenda JLScript do primeiro mostrar() até APIs, banco de dados, dispositivos e interfaces. JLScript, também chamado de JLS, é uma linguagem de programação criada com o objetivo de possuir uma sintaxe simples, legível e agradável para quem está começando, sem impedir a criação de projetos maiores. Os arquivos da linguagem utilizam a extensão: .jls Neste guia vamos começar absolutamente do zero. No final, você já terá visto: variáveis; valores; operadores; condições; loops; funções; listas; objetos; tratamento de erros; módulos; aliases; tempo; APIs; banco de
When running Kubernetes locally with Docker Desktop, you have a handy superpower: your local Kubernetes cluster shares your computer's local Docker daemon. Any image you build via docker build is immediately available to your local pods without needing to push it to the internet. However, the moment you decide to deploy to a managed cloud cluster like Google Kubernetes Engine (GKE), that magic ends. GKE nodes run in Google Cloud's data centers and have no access to your laptop's disk. They need a secure, centralized container registry from which to pull your container images.
Keep one immutable master private, generate a versioned watermarked derivative once, and let only that derivative cross the public cache boundary. For an edtech creator portfolio that turns prompts into short promo videos, the poster image shown in galleries is disposable and cacheable while the clean frame used to regenerate or re-edit the video is neither. The decision rule is blunt: if changing an object would require creative work again, it is a master; if it can be reproduced from a master plus a recipe, it is a derivative. TL;DR: Put masters and derivatives in separate storage namespaces
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