Development

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.

I’ve been wanting to sort it out about String memory optimization and all these ways to improve the performance and memory usage for Collections and Arrays in C#(as you remember String is an array of chars, loaded a bit differently but anyway) code. I finally managed to find some time to dive deeper into the System.Span.

I have put together this guide to share what I’ve learned. It’s filled with practical tips and examples to help you leverage Spans in your own projects. If you want to optimize your C# code, this guide is a great place to start!

Code Push in Flutter

In the fast-paced world of mobile app development, the ability to quickly push updates to users is crucial. Enter Code Push - a game-changing technology that allows developers to update mobile apps instantly without going through the traditional app store review process. This article explores how to implement Code Push in Flutter applications using Shorebird, a powerful tool that brings this capability to the Flutter ecosystem.

Recently, there has been a lot of talk about the success of artificial intelligence (AI), although this usually means another achievement in the field of generative neural networks.

And few people, speaking about AI, try to explain what they themselves understand by the term “artificial intelligence.” After all, it’s one thing to write about “AI problems,” and quite another to endow an ordinary computer algorithm with at least the rudiments of intelligence.

After all, the etymology of the established phrase “artificial intelligence” is not unambiguous and can take on different meanings depending on what meaning the author is trying to put into it.

According to the Oxford Dictionary, empathy is “the ability to understand and share the feelings of another”. In UX, there is a special term “user empathy”. It refers to the ability of UX designers to fully understand what users need from a particular software product. Having user empathy and basing design solutions around users” comfort is one of the most true indicators of a designer”s professionalism. Without that, any product a designer works on has a high chance of turning out to be pointless. Apart from having empathy as a soft skill in general, there are several ways a designer can practice user empathy through different UX methods and techniques. In this article we would like to talk on how a UX designer can treat users with empathy and make the product more accessible for different groups of target audience.

I always pay attention to assessing the complexity of programming in a particular language. Programming is indeed not an easy task and this is perceived as a fact and usually does not require any confirmation.

But the concept of “complexity” is akin to the term “heap”. For some, five coconuts is not so much, but for someone who ate one and “didn’t want any more,” this means that even one coconut will be too much for him.

The same goes for the complexity of programs. It seems that the constant increase in the complexity of programs is obvious to everyone and is observed in all areas of application of IT technologies, and programming languages themselves become more and more complex as they develop, but assessing “complexity” using numerical metrics is a problem. obviously a thankless task, but also “You can’t manage what you can’t measure...”

Typically, talk of “complexity” only implies value judgments without any numerical evaluation. And since I am personally interested in the issue of the complexity of programming languages, I decided to calculate the complexity of implementing the gcc compiler on some conditional “parrots”. What if we could see some patterns of difficulty changing over time?

S.B. Pshenichnikov

The article outlines a new mathematical apparatus for verbal calculations in NLP (natural language processing). Words are embedded not in a real vector space, but in an algebra of extremely sparse matrix units. Calculations become evidence-based and transparent. The example shows forks in calculations that go unnoticed when using traditional approaches, and the result may be unexpected.

The use of IT in Natural Language Processing (NLP) requires standardization of texts, for example, tokenization or lemmatization.

After this, you can try to use mathematics, since it is the highest form of standardization and turns the objects under study into ideal ones, for example, data tables into matrices of elements. Only in the language of matrices can one search for general patterns in data (numbers and texts).

If text is turned into numbers, then in NLP these are first natural numbers for numbering words, which are then embedded into real vectors is irreversible ed in a real vector space.

Perhaps we should not rush to do this but come up with a new type of numbers that is more suitable for NLP than numbers for studying physical phenomena. These are matrix hyperbinary numbers. Hyperbinary numbers are one of the types of hypercomplex numbers.

Hyperbinary numbers have their  own  arithmetic,  and  if  you get used to  it,  it  will  seem  more  familiar  and  simpler  than  Pythagorean arithmetic.

In Decision Support Systems (DSS), the texts are value judgments and a numbered verbal rating scale. Next (as in NLP), the numbers are turned into vectors of real numbers and used as sets of weighted arithmetic average coefficients.

In this report we describe our implementation experience of a stopwatch system executing on an FPGA board. We programmed this device in the Quartus Prime II software environment by using Verilog hardware description language. The program is tailored to the Altera MAX 10 FPGA board, as well as uses a set of other peripheral devices for progress visualization purposes.

This is a step-by-step research of a clear and intuitive approach to validate custom data in .NET applications with help of the Minimal API filters and the FlatValidator.

If you are new to IT, the first thing I recommend is focus. Don’t try to learn everything at once. Instead, choose a field that increases your chances of landing your first job quickly.

They might sound complicated, but they are actually a fundamental part of the language. In this article, we’ll explore closures in a straightforward and practical way. Let’s clear up common misunderstandings. Walk through real-world examples. Nail those tricky interview questions about closures. By the end, you’ll see closures not as a hurdle, but as a valuable part of your JavaScript toolkit.

Continuous socket connection can be crucial to ensure correct app behavior. Whether it’s delivering real-time chat updates, stock prices, or in-app indicators, a reliable connection is vital.

One of the irritating problems with sockets is a sudden loss of connection. If the true cause is not visibly evident, i.e., unstable internet connection, then the disruption cause is often well hidden. To tackle this issue we can implement an automatic socket reconnection strategy. Let’s see what options we have in the industry-standard socket library for Dart — web_socket_channel.

For the last 30 years digital chip design is not a schematic entry anymore: hardware engineers write code just like software engineers.

The difference is that the code software engineer writes becomes a chain of CPU instructions stored in memory, while the code in a hardware description language (HDL) becomes the CPU itself, its transistors and metal connections. And not only a CPU: the same technique is used to design processor-less ("fixed function") blocks in GPU that shuffle triangles and pixels, as well as network router chips that edit packet headers 100 times faster than CPU.

There are ways to experience this workflow without paying a million dollars to a silicon fab. One way is simulation, and another way is to use a matrix of reconfigurable logic cells, a Field Programmable Gate Array (FPGA). You can come on January 14 to Hacker Dojo in Mountain View, California. We have a bunch of computers and FPGA boards, and we will show you how to use them not only to blink LEDs but also to output graphics and recognize music.

This will change your perspective of what the code is.

In the DevOps realm, where automation is crucial, the management of resources and updating processes in the cloud is vitally important. Many modern projects, particularly in AWS cloud environments, leverage Auto Scaling Groups (ASG). This mechanism aims to achieve three key objectives: balancing loads, increasing service reliability, and optimizing operational costs for efficiency and effectiveness.

Imagine working at a company where you deploy applications on Amazon's resources. To streamline this process and manage configurations more effectively, you use pre-built AMI images. These are crafted with tools like HashiCorp Packer, ensuring your applications launch swiftly and reliably. For the actual infrastructure deployment, you turn to Terraform. It's widely recognized as the standard in many major companies for managing cloud resources and using the IaC (Infrastructure as Code) approach.

As an IT engineer, you sometimes need to update instance versions to a newer AMI image, either for the latest security patches or to introduce new functionalities. The challenge lies in updating an active ASG without causing downtime. It's crucial to ensure the new AMI performs as reliably as the existing one, balancing the need for updates with system stability and uptime.

ASG's instance refresh is a crucial feature that allows for updating instances within a group while minimizing downtime, thereby maintaining high availability. However, ensuring the success of such updates, especially in large, complex systems, can be a challenge. Terraform resources, such as aws_autoscaling_group, can initiate this process but don't provide progress tracking. This limitation becomes apparent when other infrastructure components, such as certificate renewals or DNS updates, depend on the state and version of the instances. Monitoring the update process is essential to maintain an accurate infrastructure state after Terraform's execution.

To overcome this challenge, Ansible can be utilized...

Hey everyone! Today, I'll guide you through creating a boundless cloud storage solution on Telegram using TeleDrive. This open-source project is a game-changer, offering functionalities like Google Drive/OneDrive via the Telegram API.