Development

We used to think of Telegram as a reliable and secure transmission medium for messages of any sort. But under the hood it has a rather common combination of a- and symmetric encryptions. Where’s fun in that? And why would anyone trust their private messages to a third-party anyway?

TL;DR — inventing a private covert channel through users blacklisting each other.

Have you heard about memoization? It's a super simple thing, by the way,– just memoize which result you have got from a first function call, and use it instead of calling it the second time - don't call real stuff without reason, don't waste your time.

Skipping some intensive operations is a very common optimization technique. Every time you might not do something — don’t do it. Try to use cache — memcache, file cache, local cache — any cache! A must-have for backend systems and a crucial part of any backend system of past and present.

How Tax Service, OpenStreetMap, and InterSystems IRIS
could help developers get clean addresses

I like PHP for development speed and excellent portability. It's great to have such a tool in your pocket, always ready to solve problems.

For me it was quite sad that there was no Waves Platform SDK for PHP when i first met this nice blockchain. Well, I had to write such kit.

Важным событием позапрошлой недели стало масштабное заражение npm-пакетов червем Shai-Hulud. Эта вредоносная программа нацелена на разработчиков открытого ПО. Она ставит под угрозу данные для доступа к облачным сервисам, выкладывает в общий доступ приватные репозитории. Данная вредоносная операция может быть квалифицирована как атака на цепочку поставок: взлом популярного npm-пакета приводит к компрометации множества других программных решений. На прошлой неделе специалисты «Лаборатории Касперского» подробно разобрали схему работы зловреда Shai-Hulud. Также с высокой вероятностью был определен «нулевой пациент» — первый зараженный пакет в репозитории npm.

Атака начинается с загрузки зараженного пакета из репозитория npm. После установки автоматически запускается вредоносный скрипт размером более 3 мегабайт с названием bundle.js. Он содержит набор легитимных модулей для работы с облачными сервисами Amazon и Google Cloud Platform, инструменты для взаимодействия с GitHub API, а также имеет функциональность для работы с TruffleHog, свободно распространяемой утилитой для поиска ссылок на конфиденциальные источники данных.

This tutorial will guide you through the process of integrating OpenAI’s powerful Codex coding agent directly into your Visual Studio Code environment. This tool functions as an AI pair programmer, capable of understanding complex prompts to execute commands, write code, run tests, and even build entire applications from scratch.

CAPTCHA protocols are designed to tell bots from humans, yet in the worlds of automation and testing there is often a need to bypass them. Dedicated CAPTCHA‑solving services take over this task, combining algorithms with human labor.

In this article we present an in‑depth comparison of four popular platforms — 2Captcha, SolveCaptcha, DeathByCaptcha, and AntiCaptcha. We will examine not only pricing and the types of CAPTCHAs supported, but also internal architecture, API integrations, speed and stability, plus the quirks of using each service.

The technical community will find a deep dive here — from API and SDK structure to real‑world use cases. Below you will see a table comparing key characteristics, lists of pros and cons, and a discussion of which service best fits particular automation tasks.

Postgres Pro recently announced the release of Enterprise Manager 2, commonly known as PPEM.

In short, PPEM is an administration tool designed for managing and monitoring Postgres databases. Its primary goal is to assist DBAs in their daily tasks and automate routine operations. In this article, I'll take a closer look at what PPEM has to offer. My name is Alexey, and I'm part of the PPEM development team.

Today, I want to talk about one of those sneaky tricks that can help speed up query execution. Specifically, this is about reordering conditions in WHERE clauses, JOINs, HAVING clauses, and so on.

The idea is simple: if a condition in an AND chain turns out to be false, or if one in an OR chain turns out to be true, there's no need to evaluate the rest. That means saved CPU cycles — and sometimes, a lot of them. Let’s break this down.

Here I describe the results of developing a PostgreSQL extension I built just out of curiosity. Its purpose is to automatically manage extended column statistics. The idea came to me while finishing work on another "smart" query-driven product for improving PostgreSQL planning quality. I realized that the current architecture of PostgreSQL isn’t quite ready for fully autonomous operation — automatic detection of bad plans and adaptive optimizer tuning. So why not try the other way around and build an autonomous data-driven assistant?

Hi everyone, I’m Alexey. I’m a big fan of observability, and in this post, I want to share something I’ve been working on — the pgpro-otel-collector.

TL;DR: pgpro-otel-collector is an OpenTelemetry collector (aka monitoring agent) tailored for gathering Postgres metrics and logs — brought to you by PostgresPro.

This article presents a business-driven approach to software architecture, focusing on maximizing profitability through technical decisions. It advocates for:

Distributed, stateless services with immutable models for scalability

Isolated third-party integrations without disrupting core logic

Simple, modular design 

Best for:

✔ Tech leads designing scalable systems
✔ Managers optimizing dev efficiency
✔ Stakeholders evaluating ROI on architecture

Would you like to know which indexes are used frequently or rarely? Which ones aren't used at all? Which tables and indexes are the largest? It's very easy to create visualizations for this. They're both visually appealing and practically useful.

If you work with PostgreSQL, you've likely run into performance issues at some point — especially as your database grows. Things may have been running smoothly at first, but as your client database expanded, queries started slowing down. Sound familiar? Here's a guide to help you identify and fix problematic queries, so you can get your PostgreSQL database running at peak performance again.

Armenia is a lucky country. Back in the 1990s somebody lobbied Synopsys, the #1 leader in the Electronic Design Automation market, to create a division there. It was joined by Mentor Graphics / Siemens EDA, another EDA leader, then NVidia. Synopsys Armenia became the largest Synopsys division outside the US Silicon Valley and Boston, although the Taiwanese may tell you otherwise. Since Synopsys and Mentor make software used by chip designers in Apple, Samsung, AMD and all other electronic companies, Armenia has an unfair advantage over all their neighbors in Caucasus and Central Asia.

In addition, Armenia has friendly relations with Russia, and most Armenians speak Russian as well. This has facilitated the move of many Russian companies to Armenia, for example, a RISC-V semiconductor IP provider Syntacore. Finally, as we can see from the recent conference EDA Connect, Armenia is attracting the attention of electronic and EDA companies from China.

EDA Connect featured not only academic and industrial papers but also a hackathon on FPGA design, attended by local students from Yerevan State University, the American University of Armenia, the Russian-Armenian University, the French University in Armenia and others.