Why might a feature not get to production on time? What prevents the team from releasing before the deadline? Can the product owner influence the timeline?
In this article, I will try to answer these questions and suggest solutions for the processes we are implementing and improving within the product team at EXANTE.
SSH (Secure Shell) is the backbone of remote system administration and secure remote access, serving millions of developers and system administrators daily. However, when SSH connections fail, the cryptographic nature of the protocol can make debugging challenging. The complex interplay between authentication mechanisms, encryption algorithms, and network layers often obscures the root cause of connection issues. This complexity is further compounded by the protocol's security-first design, where error messages are intentionally vague to prevent potential attackers from gathering system information. Whether we're dealing with key authentication failures, network connectivity issues, or configuration mismatches, understanding the underlying SSH architecture becomes critical for effective troubleshooting.
In today's interconnected development world, secure authentication is not just a luxury—it's a necessity. Whether you're a seasoned DevOps engineer or a junior developer just starting your journey, understanding SSH key pairs is crucial for your daily workflow. They're the unsung heroes that keep our git pushes secure, our server access protected, and our deployments safe from prying eyes.
But let's be honest: SSH keys canbe confusing. With terms like “public key infrastructure,” “cryptographic algorithms,” and “key fingerprints” floating around, it's easy to feel overwhelmed. This guide aims to demystify SSH key pairs, breaking down complex concepts into digestible pieces that will help you make informed decisions about your security setup.
This article is the first in the series about the upcoming PostgreSQL 18 release. Let us take a look at the features introduced in the July CommitFest.
Planner: Hash Right Semi Join support
Planner: materializing an internal row set for parallel nested loop join
Planner support functions for generate_series
EXPLAIN (analyze): statistics for Parallel Bitmap Heap Scan node workers
Functions min and max for composite types
Parameter names for regexp* functions
Debug mode in pgbench
pg_get_backend_memory_contexts: column path instead of parent, new column type
Function pg_get_acl
pg_upgrade: pg_dump optimization
Predefined role pg_signal_autovacuum_worker
Firebase Performance offers a free, comprehensive solution for tracking app performance. As part of the Firebase suite, it provides seamless integration with other Firebase services like Crashlytics, making it easier to manage all performance and crash data in one place. This not only simplifies access but also streamlines team collaboration without the need to manage multiple platforms.
Recently I have bought starfive visionfive-2 SoC for my own experiments, honestly speaking
I am striving to work with risc-v. After some time I decided to share my experience. Here my bulletpoints:
Small preparation USB-to-Serial connector Write image to microSD/SSD Set boot mode settings
Boot Update bootloader Build kernel Native build Pod build Cross-build on amd64: fast and handy
Chroot to risc-v system from amd64 and install packages
Bonus 1: run qemu with risc-v
Bonus 2: build deb packages for risc-v
Bonus 3: kernel build script
Conclusions
I came across a script on the Internet that allows you to parse product cards from Amazon. And I just needed a solution to a problem like that.
I wracked my brain while looking for a way to parse product cards from Amazon. The problem is that Amazon uses different design options for different outputs, in particular – if you need to parse the cards with the search query "bags" – the cards will be arranged vertically, as I need it, but if you take, for example, "t-shirts" – then the cards will be arranged horizontally, and in such way the script falls into an error, it works out opening the page, but does not want to scroll.
A story about evolving our CI process for a monolithic Python repo with tests, challenges faced, and solutions. Discussing Docker, linters, Allure TestOps, and more.
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.
Want Higher Google Rankings?
Try These 6 Backlink Strategies That Actually Work.
In the end, you’ll get tips to help you build a strong backlink strategy.
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
Users don’t fear changes. They fear wasting time. Why users reject “best” products — and how to win them over.
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.
If you’ve been working with Unreal Engine for a while, you’ve probably come across nodes that let you call a function now and get the result later — while also continuing execution once the function completes.
As part of my scientific and research interests, I decided to experiment with bypassing complex types of CAPTCHAs. Well, by “experiment” I mean testing the functionality and verifying that my electronic colleague can write code on my behalf. Yes, there was a lot of extra stuff—follow ethical norms, blah blah blah… But the simple fact remains: dude, I’m doing this solely as part of research, and everyone agreed.
Have you ever heard of Gemini Code Assist? It’s an AI-powered coding assistant from Google that helps with writing, completing, and debugging code. The best part? It’s now free for individuals, freelancers, and students!
In this article, I’ll show you how to set up and use Gemini Code Assist inside VS Code. Whether you’re new to coding or an experienced developer, this tool can save you time and make coding easier. Let’s get started!