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I built a browser-based desktop environment (IP Linux) with React, TypeScript and Vite

I built a browser-based desktop environment (IP Linux) with React, TypeScript and Vite I have been working on a project called IP Linux : a browser-based desktop environment that runs as a static web app. Live site: https://ip-os-linux.vercel.app/ GitHub Repository: https://github.com/ikerperez12/IP-OS-LINUX It is not a real Linux distribution, and it does not run native binaries. The idea is different: I wanted to explore how far a polished desktop-like experience can go inside a normal browser tab. The result is a small web OS-style environment with: A splash / entry screen A desktop with icons, folders, and widgets A top panel with system controls A dock and app launcher Resizable and draggable windows Virtual workspaces Snap assist A global search / Spotlight-style command palette Local-first apps (Files, Terminal, settings, player) Reactive wallpapers Glass UI and visual effects Why I built it Most web demos are landing pages, dashboards, or small single-purpose apps. I wanted to build something that feels more like an environment. I was interested in questions like: Can a web app feel physical and desktop-like? How should windows behave inside a browser viewport? How far can local-first storage go before a backend is actually needed? How do you organize many small apps without making the UI messy? IP Linux became a way to test all of that in one project. The app includes a catalog of built-in apps and tools: Files, Terminal, Browser, Settings, App Store, Music Player, Matrix Rain, games, developer tools, productivity apps, and visual utilities. The virtual file system and user preferences are stored locally in the visitor's browser with IndexedDB/localStorage. There is no backend, no account system, and no required environment variables for the public release. Would love to get feedback on the interaction design, responsiveness, or features!

2026-06-15 原文 →
AI 资讯

AI Tooling on OpenShift: A Practitioner's Evaluation Framework

Pipeline & Prompts | Byte size guides on DevOps, Cloud and AI ** AI in the Stack #1** Byte size summary After reading this article, you'll have a framework for evaluating AI tools in platform engineering contexts — not by capability type, but by where in your workflow the tool actually changes the outcome. You'll understand why the tools that sound most compelling are still hype, where genuine productivity gains exist today, and what governance infrastructure you need in place before any AI component gets near production. This article is the foundation for the series; subsequent articles implement each touch point against real OpenShift infrastructure. The story I spent months selling IBM's AI and data science portfolio before I truly understood what I was selling. I knew the pitch. Predictive analytics. Optimization. Decision intelligence. I could walk a room through the business value without breaking a sweat. CPLEX for scheduling, Watson for insights — I had the slides, the talking points, the customer stories. Then I sat in on a data scientist demo. Not a sales demo. An actual working session — models being trained, outputs being interrogated, assumptions being challenged in real time. And somewhere in that room, watching someone do the thing I'd been describing from the outside, something clicked — and not in a good way. The models were impressive. The theory was solid. But I kept asking myself the same quiet question: where does this go next? Because most of what I saw never made it anywhere near production. It lived in notebooks. In slide decks. In proof-of-concept environments that were never ready to cross the line into something real. I'd been selling outcomes — optimised schedules, smarter decisions, reduced costs — without a clear path to how you'd actually get there. And underneath all of it, something else bothered me that nobody was talking about loudly enough: the data going into these models was often messy, unvalidated, and ungoverned. Bias wasn't

2026-06-15 原文 →
开发者

Building Lightweight PHP Microservices with webrium/core — No Framework Bloat Required

Do you really need a full framework to handle a few API endpoints or webhooks? Laravel and Symfony are excellent tools — for large applications. But when you're building a focused microservice, a webhook receiver, or a lightweight REST API, bootstrapping a full-stack framework means carrying hundreds of files, a massive autoloader, and a dependency tree you'll never fully use. That's the problem webrium/core was built to solve: a minimalist, zero-dependency PHP micro-framework written entirely from scratch, designed to stay out of your way. Installation composer require webrium/core That's it. No configuration files to publish, no service providers to register. The Entry Point Every webrium application starts with the same three lines: <?php require_once __DIR__ . '/vendor/autoload.php' ; use Webrium\App ; use Webrium\Route ; App :: initialize ( __DIR__ ); // ... your routes here App :: run (); App::initialize() sets the root path and loads the global helper functions. App::run() initializes error handling and dispatches the current request through the router. Routing The router supports all standard HTTP methods. Route handlers can be closures, a Controller@method string, or an [Controller::class, 'method'] array. Basic routes: Route :: get ( '/status' , fn () => [ 'status' => 'alive' ]); Route :: post ( '/items' , fn () => [ 'created' => true ]); Route :: put ( '/items/{id}' , fn ( $id ) => [ 'updated' => $id ]); Route :: patch ( '/items/{id}' , fn ( $id ) => [ 'patched' => $id ]); Route :: delete ( '/items/{id}' , fn ( $id ) => [ 'deleted' => $id ]); Route handlers return an array — the framework automatically encodes it as JSON and sends the correct Content-Type header. Dynamic parameters: Route :: get ( '/users/{id}/posts/{postId}' , function ( $id , $postId ) { return [ 'user_id' => $id , 'post_id' => $postId , ]; }); Named routes: Route :: get ( '/users/{id}' , fn ( $id ) => [ 'id' => $id ]) -> name ( 'users.show' ); // Generate the URL elsewhere: $url = rout

2026-06-15 原文 →
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