I've run both platforms in a real production environment — 600+ users, 50+ SaaS platforms, an international software company with distributed teams across multiple timezones. This isn't a vendor comparison page. This is what I actually experienced running both, migrating between them, and managing the transition in parallel.
The question "JumpCloud or Okta?" comes up constantly in IT communities. It almost always gets the same frustrating non-answer: "it depends." That's technically true — but let me break down exactly what it depends on, and why.
The demand for live sports streaming has grown rapidly across OTT platforms, IPTV services, and mobile streaming applications. Today’s viewers expect real-time access to sports events without buffering, lag, or playback delays. Whether it is football, cricket, basketball, esports, or live tournaments, audiences want an experience that feels as close to live television as possible.
Low latency sports streaming has become one of the most important technologies for modern OTT platforms. It reduces the delay between the live event capture and viewer playback, enabling sports fans to watch matches in near real time. For OTT providers, broadcasters, and streaming businesses, low latency delivery improves viewer satisfaction, engagement, and platform reliability.
Platforms that deliver ultra-low latency live streaming can create immersive sports viewing experiences while supporting interactive features such as live betting, real-time commentary, instant replay, and audience engagement tools.
AI coding assistants are becoming better every day. But most still work one prompt at a time. You ask something, get an answer, and then guide the next step manually.
Renowned biologist Richard Dawkins recently published an essay exploring the possibility of LLM consciousness following a two‑day conversation with Claude AI.
Let“s first look at why an essay by this particular author caused such a stir in scientific circles, while thousands of ordinary users fail to turn heads when they claim their AI companions are sentient. The latter constantly post endless walls of text from their chats with LLMs, where the density of words like ‘consciousness,’ ‘soul,’ ‘reflection,’ ‘recursion,’ ‘emptiness,’ ‘warmth,’ ‘love,’ and ‘pain’ exceeds all reasonable limits. It is worth noting that the semantic density of these dialogues is practically zero‑but we will return to that later.
In Part II we saw that an API key is essentially a long, secret password your software shows to a server. It works, but it has a hidden cost: every time the key is used, the server must look it up in a database to find out what the key is allowed to do, whether it has expired, and whether it has been switched off. A JSON Web Token (JWT) removes that lookup by carrying all of that information inside the token itself. This article explains the problem JWT solves and shows where it sits in the larger story of web authentication.
Part I covered Basic Authentication — sending a username and password with every request. Part II covered API keys — replacing that reusable password with a single opaque secret string that identifies an application rather than a person.
In early 2026, one new law and one far‑reaching legislative initiative are expected to seriously affect digital freedoms in the EU. The first allows police to collect biometric data and target individuals; the second aims to put all metadata into one box and then use AI to run investigations. Naturally, both laws were adopted under the mantra of protecting democratic values, rights, and freedoms. Xeovo has examined the sprawling regulatory texts and explains what exactly Members of the European Parliament are aiming at.
Просто крик души. Невозможно проводить собеседования на позицию Go-разработчика.
Все эти Ghost GPT, CodeShot AI, ENIGMA AI привели к тому, что единственный способ действительно понять квалификацию человека — пригласить его в офис. С одной стороны, мы получили инструмент, который снижает уровень стресса: помощника, способного подсказать и поддержать в нужный момент. С другой — человек из условного Усть-Дальневска уже вряд ли сможет пройти собеседование в Москве на хорошую позицию и достойную зарплату, потому что, похоже, скоро компании начнут массово возвращаться к офлайн-собеседованиям. Лично у меня уровень доверия к онлайн-интервью сейчас где-то на уровне плинтуса.
И, к слову, если человеку кажется, что использование AI-помощника на интервью незаметно — ему только кажется. Это видно. В итоге все просто тратят время друг друга впустую.
VPN age checks are a new initiative by British authorities aimed at protecting children from “harmful information.” It follows a series of other puritanical ideas, such as banning social media for people under 16, introducing age verification for viewing adult content, and similar measures. Xeovo explains why VPNs do not actually contribute to the criminalization of teenagers — and what the introduction of age checks could lead to.
Hi, I thought about this problem because on the internet I couldn't find information on how to correctly connect MySQL in a basic backend project. Also, I'll show you how to use it in a monorepo project. In this lesson, we'll be using NestJS and Prisma, as they are the most popular tools in backend development.
Okay, now, create a folder wherever you're comfortable, and open the terminal. In the terminal, type these commands:
$ npm i -g @nestjs/cli
$ nest new project-name
$ cd project-name
The next steps — you can start building anything with your project. But when you need a database, you'll need to import Prisma into your project. It's easy — run this command:
$ npm install prisma --save-dev
As a best practice, it's recommended to invoke the CLI locally by prefixing it with npx:
$ npx prisma
$ npx prisma init
Nice! Now, the following files should appear in your project:
My name is Vladimir Smirnov, and I am responsible for testing the trading backend at EXANTE. Development moves fast. Regression suites grow. With them come the chaos and inconsistency of test environments, and a steady rise in unstable failures, known as flakes. Real problems hide behind those flakes. How do we keep our automated tests in acceptable shape without spending too much time on it? That is what this article is about.
Like millions of others convinced they possess knowledge the world desperately needs to hear, I decided to write a book on prompting. In the process (which, by the way, turned out to be far more difficult than anticipated), I found myself examining LLM clichés. You know the ones. At least, in the comment sections of tech blogs, hundreds of self-proclaimed experts use them to spot AI-generated text.
Anyway, these clichés definitely exist, and many authors now routinely add blocklists of these phrases to their prompts to weed them out. Whether this is actually a good or a bad thing is what I’ll break down below.
UX audit is a professional review and evaluation of a software product's UX, aimed to identify any types of issues that have a negative impact on the product's performance and provoke user frustration. Its ultimate goal is to provide recommendations on which areas of the product need to be improved to make it more user-oriented and therefore more useful and profitable for the business. Let's discuss how to know when the product needs a UX audit, how to prepare for the process as the product owner, which steps the process consists of and what to do with the results.
Does your team actually use PRDs, or has something else taken over?
Anthropic recently said they don’t really rely on classic PRDs. They build a prototype, ship it internally, and let people use it. In that world, the prototype becomes the main reference.
A lot of people heard that and thought, “PRDs are dead.” I don’t think that’s quite right.
It works at Anthropic because everyone is technical, they use the product themselves, and they trust AI‑generated code enough to ship it early. The product evolves through real use, not documents.
Most teams are not like that. There’s a short call, a loose agreement, and then a ticket that misses half the conversation. By the time something ships, it’s working code, but not what was really meant.
So to me, Anthropic is not killing PRDs. It’s replacing them with heavy internal usage and fast feedback. If you remove PRDs and don’t have that, you’re not being like Anthropic. You’re just losing context.
For me, the key question is not “do we need PRDs.” It’s “what makes sure the team actually builds what it agreed on.”
What arе the most dangerous things in the world? Viruses, highways, processed foods, Australian spiders? And what is danger, really? Regardless of how we define it, there must be clear risks and measurable harm.
Somehow social media platforms are not showing up on any list of the most dangerous things, although even antibacterial soap and apathy have had such an honour. Why, then, did the Australian government prohibit having a social media account for those younger than 16?
Google recently released the Agentic CLI, a powerful tool that makes building, testing, and deploying AI agents faster and more intuitive. I think it’s super useful, so I’ll walk you through the entire lifecycle of an AI agent using the CLI.
C++ has trapped itself in an evolutionary dead end due to backward compatibility and UB, and the only realistic successor capable of displacing it in large codebases will be a transpiler that generates C++ and enables gradual, low-risk adoption.
В последнее время появляется всё больше новых решений, но выбрать по-прежнему сложно. Поэтому я потратил время, чтобы сравнить и провести бенчмарк всех решений для интернационализации в Next.js и TanStack Start.
На одном и том же приложении я протестировал 4 сценария, комбинируя динамическую загрузку и JSON-скоупинг по неймспейсам.
Что я измерял:
размер библиотеки
размер страницы
утечки неиспользуемого контента на страницу и локаль
размер компонентов
время загрузки, переключение страниц и реактивность приложения
После 6 часов тестов вот результаты: Тренд оказался неожиданным. Чем более «хайповым» и модным является решение, тем хуже оно справляется с реальными задачами интернационализации. Самые приятные сюрпризы оказались там, где их меньше всего ожидаешь.
(Считайте это версией v1. Интерпретация результатов частично основана на моих личных предпочтениях и опыте как автора решения. Буду рад обратной связи и предложениям по улучшению.)
In 1976, Richard Dawkins introduced the concept of the meme in The Selfish Gene—a unit of cultural information that behaves like a gene: it copies itself, mutates, and undergoes selection. The idea proved so infectious that it became a meme itself: it entered science, spilled over into popular culture, morphed into internet folklore, and... got stuck.
I propose patching memetics via an IT metaphor. A meme is not a virus. A meme is mere data. The actual virus is the Narrative—the executable code of culture.
Key takeaways:
The human as a server, not a user: We are hosting providers for ideas.
Emotion is the spike protein of the narrative virus.
The user is a biological USB flash drive for AI.
A meme is a corpse. A narrative is a zombie.
Consciousness is a narrative that evolved into an Operating System.