
If your code has many nested executions of stored procedures, you can benefit from building popular "flame diagram" of the execution time which is de facto standard for performance profiling.
If your code has many nested executions of stored procedures, you can benefit from building popular "flame diagram" of the execution time which is de facto standard for performance profiling.
Postgres Pro Enterprise 17 introduces major improvements in performance and scalability. The key feature of this new release is the proxima extension, which combines connection pooling, proxying, and load balancing within the database core. Developers also gain improved tools for managing message queues, optimizing queries, enhancing security, and utilizing smart data storage. Want to know how these and other features can impact your applications and simplify database administration?
This article provides a brief overview of the release, accompanied by the links to more detailed information.
Automation can be an exhilarating, albeit exhausting, journey‑especially for those just dipping their toes into it. The tasks are often labeled as “interesting” or “non‑standard,” which, let”s be honest, often translates to “challenging” or even “impossible.” Among these challenges, one question halts around 50% of novice automators in their tracks: How to bypass CAPTCHA!
In the world of blockchain, where the word "gas" is most often associated not with gas stations, but with fees for transactions in Ethereum, the search for ways to minimize these costs is becoming increasingly relevant. Less heartache for an empty wallet and more time to solve really important issues... for example, what to cook for lunch =)
Similar to the epic Batman vs Superman battle, compare GSN and Account Abstraction. As in any superhero story, each of them has its own unique abilities and disadvantages, which we will look at in detail.
Wilhelm Röntgen discovered X-ray November 8th 1895, when he did experiments with cathode rays in a vacuum tube. To capture and save images of the shadows from the X-rays, he used ordinary photoplates. Fortunately, sensitive to visible light silver based photoemulsions turned out to be sensitive to the X-ray too. These photoplates became the first X-ray detectors.
More than 100 years of scientific progress led to the creation of a number of various detectors for recording X-ray images. Developments of the microelectronics and semiconductor manufacturing technologies are crucial for development of the modern X-ray detectors. These detectors can transform the energy of the X-ray photon directly to the electrical signal. They allow capturing detailed, digital, high-resolution X-ray images.
Digital images are easy to work with. For example one can merge multiple macro images into an image of the whole object and represent monochrome images in false colors like Simon Procz did with this X-ray image of a flower he did in 2012.
Hey! My name's Kirill Ziborov and I'm a member of the Distributed System Security team at Positive Technologies. In this article, I'll be continuing the discussion of methods and tools for the formal verification of smart contracts and their practical application to prevent vulnerabilities. The main focus will be on the deductive verification method, or more precisely, the ConCert framework for testing and verifying smart contracts.
Kata Containers is actually now the main way to run containers in an isolated virtual machine for greater security. I tell you how to install them for use with Containerd and Docker while still being able to switch between release versions.
Secret Management and Why It’s Important
Hi! My name is Evgeny, and I work as a Lead DevOps at Exante. In this article, I will discuss the practical experience of setting up a high-availability HashiCorp Vault with a GCP storage backend and auto unseal in Kubernetes (K8s).
Our infrastructure used to consist of thousands of virtual and physical machines hosting our legacy services. Configuration files, including plain-text secrets, were distributed across these machines, both manually and with the help of Chef.
We decided to change the company’s strategy for several reasons: to accelerate code delivery processes, ensure continuous delivery, securely store secrets, and speed up the deployment of new applications and environments.
We decided to transition our product to a cloud-native model, which required us to change our approach to development and infrastructure. This involved refactoring our legacy services, adopting a microservices architecture, deploying services in cloud-based Kubernetes (K8s), and utilizing managed resources like Redis and PostgreSQL.
In our situation, everything needed to change—from applications and infrastructure to how we distribute configs and secrets. We chose Google as our cloud provider and HashiCorp Vault for secret storage. We've since made significant progress on this journey.
Why HashiCorp Vault?
There were several reasons:
Riverpod is a powerful library that I like to think of as the Swiss Army knife of Flutter development. It offers elegant solutions for both state management and dependency injection, giving you the freedom to "cook" your app architecture just the way you like it.
In this tutorial, I’ll explain in simple terms what AI, AI agents, and workflows are, and then I’ll walk you through building your very first AI agent in Python using Google’s Agent Development Kit (ADK). By the end, you’ll understand the differences between these concepts and have a working content-assistant agent you can run from your terminal or a web interface.
Admit it, how many times have you wanted to quickly create an image for a post or presentation, but instead got stuck in an editor or endless searches for a suitable image on Google? Wouldn't it be great if the picture in your head could just appear instantly? Time is money, inspiration is on pause, and that's where AI comes to the rescue. Neural networks can generate anything you want, including the craziest ideas. No need to spend hours searching when, with a few clicks, you can see what was in your thoughts just a second ago.
By the way, notice the cover with the dinosaur? Let's call him Rex. Rex is himself a product of neural network creation. Today he'll be the main star of our experiments. But what will we do? Remember I mentioned crazy ideas? Well, to understand all the possibilities of generation, let's give AI a difficult task. We'll send Rex somewhere in space, for example to the Moon, let him put on a spacesuit and and have him grill some barbecue with Earth in the background. Interested? Then buckle up, we're heading into the world of image generation.
Historically, we’ve ended up using a few rather obscure PHP extensions—written and barely (if at all) maintained by their original authors—that aren’t available in standard Debian package sources.
We stick to the principle of “do it right, and it’ll work right,” which means Slackware-style dropping binaries into the system outside of package managers is frowned upon.
So instead, we’ll be building proper .deb
packages for PHP extensions—without breaking compatibility with the existing environment.
A lot of people around me spend time trading on the stock market. Some trade crypto, some trade stocks, others trade currencies. Some call themselves investors, others call themselves traders. I often see random passersby in various cities and countries checking their trading terminals on their phones or laptops. And at night I sometimes write analytical or backtesting software—well, I did up until recently. All these people share a common faith and a set of misconceptions about the market.
We are a brokerage platform operating in a dynamic and complex domain. This specificity comes with a set of challenges. On the one hand, it entails a high variability of scenarios and potentially significant risks associated with errors. On the other hand, it has short development iterations with frequent delivery cycles.
In this article, we will share how we maintain the quality of our numerous backend services, which provide essential information to our trading terminals.
The goal of the Intelligent Systems Department is to facilitate the road to high-quality professional life. The Ph.D. degree requires three publications in peer-reviewed journals. They are the core of the student’s thesis. This year each of our bachelor students delivered at least one publication. It means they pave the road to their Ph.D. To facilitate this, the Department provides state-of-the-art research topics, scientific advisors with excellence in science, and fine-tuned educational courses. Below, we are proud to recognize our students for their outstanding achievements.
Gen Z – a generation of young people born between the last few years of the 20th century and the first ten years of the 21st, are the primary users of a modern-day Internet. They started using technology since their early childhood, being almost constantly glued to their smartphones and tablets, which led to them being very demanding users that have their own requirements in UX. At the same time, they are known for their sense of humor and straightforwardness – which means they love using products that are both easy to navigate but full of interactive elements. Below we’ve collected a few things you should consider when creating a UX design aimed at a young audience.
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