All streams

How we turned a NAS control panel into an extension platform, why Log Manager was needed, and what the Plugin Template is for.

In the previous article (Mini Bucket 3.6.2: from beta to release), I showed how the panel matured to a stable state: we patched holes, separated databases, and added HTTPS.

But it’s still just a panel. SMB, FTP, and the rest are standard features found in almost any admin panel. It’s time to expand the functionality.

The best solution turned out to be: .....

How a Product Owner at Exante uses AI to cut complex feature delivery time in half — without replacing human input in product decisions.

Author: Sergey Lukyanchikov, C-NLTX/Open-Source

Disclaimer: The views expressed in this document reflect the author's subjective perspective on the current and potential capabilities of jBPM.

TL;DR: Zero "quantum supremacy". Zero "agentic orchestration". Zero other hype. Just an approach to achieving an efficient quantum-assisted automation using 100% free open-source components (except for Azure).

In my previous article, I discussed the rationale for adopting jBPM as an AI orchestration platform. This article extends that discussion by examining jBPM’s ability to automate quantum computations and to incorporate their results into business processes and related analytical workflows:

About a year ago, I decided to create a universal open-source solution for list visualization. In the first versions, I tested the virtualization technology with various parameters, and there was a lot of research and questions. Today, version X.12.X was released, which runs on Angular 14-22. I’d like to talk about the capabilities of the tool (ng-virtual-list), the problems it solves, and give a brief overview with examples.

All examples below are contained in the code sample documentation.

The ng-virtual-list tool provides virtualized, high-performance lists with a variety of features that standard lists don’t have.

In a rapidly changing and ever evolving world of modern technologies and new gadgets that appear every few months, each software product needs a regular update both in terms of external appearance and internal compounds. In particular, one thing that can play a major role in freshening up an outdated app and changing the way users interact with it for the better is UX redesign. 

What if an LLM could observe its own hidden states? Meta-transformers use cognitive tokens and meta-attention to turn internal uncertainty into usable signal.

Hey you. Yes you. Do you have more routers than you can reasonably explain? Do you flash custom firmware for fun? Have you ever spent an entire evening troubleshooting an issue with router, then called it “relaxing”?

Xeovo is looking for you and your router, network and technical knowledge. We are going to give an opportunity for our community members to expand guides for routers, earn money and get recognition on Hub.

Our router tutorial section has the biggest gaps. Let's change this together.

Why I built Requester, a real-time HTTP load testing app for macOS, and what Swift structured concurrency taught me about telling the truth under load.

I wanted to hammer an HTTP endpoint and see what happened. Not read a summary report three minutes later — watch it, live, the way you watch a profiler.

The existing options are great but they all live in the terminal: wrk, hey, k6. I love them, but I kept wishing for a native window with a chart that moved. So I built one for macOS, in Swift and SwiftUI, and called it Requester.

This post is less “here are the features” and more “here are the three things I made building it.” The most interesting one: making the tool honest about backpressure turned out to be a design decision, not an accident.

Why Debian 9, PHP 7.0, and no frameworks. And how to set up HTTPS in 5 minutes.

Foreword for those who haven't read the first article

Last time, I told the story of how I wanted to make a couple of pages for SAMBA and NFS, but ended up with a NAS control panel of 20+ pages. I named the project Mini Bucket.

Important: That version was a beta. Raw, with rough edges, but alive. Its goal was to demonstrate the concept. And people got interested. So, it needs to be polished.

Now – version 3.6.2. A ton of problems have been fixed, security has been added, a separate domain, forum, and wiki have appeared. Today, I'll walk you through the installation step-by-step with screenshots.

But first – a quick summary of what has changed. Then – pure practice.

I ran into a very practical problem after doing a lot of local work with AI agents. I had Codex projects, Claude Code projects, regular repositories edited with agents, drafts, pipelines, instructions, skills, artifacts, and several machines. At some point it became hard to tell where the current version of a project lived, which files were safe to push, where agent instructions belonged, and where source code had already been mixed with logs and intermediate output.

That is why I built AI Workspace System: a small set of shell scripts, conventions, and Markdown documentation that makes local AI-agent work predictable. It is not an IDE and not an agent orchestrator. It is a thin infrastructure layer around Git, GitHub, Codex, and Claude Code.

The core idea is simple: all projects should be visible from one list, instructions should follow one structure, sync should be safe by default, and machine-specific details should not live in the repository.

Abstract. This work examines the physical foundations of Ekahau Sidekick measurements and the device offset mechanism from the perspectives of antenna theory, receiver noise theory, statistical signal theory, and the IEEE 802.11 standard family. It is shown that the scalar received signal strength indicator (RSSI) offset constitutes a linear level shift and does not model the true signal-to-noise ratio (SNR) of the client device, the quadrature amplitude modulation (QAM) constellation structure, the rate adaptation algorithm, or roaming behaviour. In addition to five independent physical and systemic sources of inaccuracy, the paper addresses modeling assumptions in Ekahau with respect to multiple-input multiple-output (MIMO) gain, multipath propagation, airtime estimation, and SNR visualisation. Verified numerical error estimates for representative deployment scenarios and practical recommendations are provided.

Fair warning right away: I'm not a programmer. The code could be prettier, the architecture more elegant. But my goal was different – to make a convenient tool for myself as a system administrator. What came out came out. Don't judge too harshly, it's beta.

How it all started

I had some free time. I had an old Netgear Stora MS2000 lying around – I'd installed Debian 7 and OpenMediaVault on it back in the day. Then a disk crashed, I reinstalled Debian 9, but OMV turned out to be too heavy for this hardware.

Editing configs in the console every time was tedious. And all I really needed was SAMBA and NFS. So I thought, why bother? I'll write a couple of PHP scripts to create and edit shares.

And so Mini Bucket began.

The first two pages – and off we went

I whipped up the first two pages quickly: shares started working. Then I thought, "It would be nice to have a dashboard to see all the stats." A third page appeared – a dashboard with graphs.

Then I figured: since I've got SMB and NFS, might as well add rsync and FTP too. Added them.

Day by day, my "two-page panel" grew into a project now called Mini Bucket – NAS Control Panel.

And you know what? It actually works. On hardware where modern panels simply won't start or slow to a crawl.

What is this thing?

Mini Bucket is a web-based NAS control panel focused on resource efficiency. It runs on:

It was 10 PM on a Tuesday. An employee sent a message: "I lost my laptop. Somewhere in the city. I have no idea where it is."

Inside that laptop: access to work tools, internal conversations, probably cached authentication tokens. Potentially a way into systems that had nothing to do with the device itself.

We locked it remotely in a few minutes. No panic. No emergency calls. No incident post-mortem the next morning.

And then we just went to sleep.

That's what MDM actually is — not technology for technology's sake, but the ability to not turn a bad moment into a crisis. The difference between "we handled it" and "we need to talk about what happened."

When you buy a $20 ChatGPT subscription, you get access to about $1,000 worth of tokens. When you buy a $100 Claude subscription, you get access to about $2,000 worth of tokens. However, these subscriptions cannot be connected to Cursor directly. The API and subscription request formats are different, so you need a workaround — proxying the requests.

By the time this article is published, it will be 99 days until Google starts blocking unverified app developers. 

Developers of smart cameras, smart DVRs, and neural-network video analytics for surveillance systems need AI models capable of operating in real-world street conditions. Out there, nobody walks around with professional cameras, carefully adjusts angles, sets up lighting, records without compression, or follows the common sense taught in cinematography textbooks.

Of course, Gambit can be used for many other tasks, but its main focus is the convenient collection of material FROM video surveillance systems and dataset annotation specifically FOR video surveillance neural networks.

Gambit is not designed for polished photos and Internet reels. Quite the opposite — it is intended for low-quality surveillance archive footage. At SpesLab, we call this kind of content “wild.”

We are all fascinated by the ability of AI to describe what is happening in front of a video camera, but so far we have not seen anyone answer the question — why? Is there at least one truly practical use case?

At SpecLab, however, we came up with our own application...

By diving deeper into robotics, we keep discovering more and more about human beings. Apparently, God designed us in much the same way

Malicious code was injected into four Laravel-Lang projects, presumably stealing credentials from the devices on which it was run.

Popular projects were affected: Lang, Actions, Attributes, and HTTP Statuses.

The incident concerns not only Laravel...

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.