The demos look super cool! An AI agent detects a failing deployment, rolls it back, opens a GitHub issue, and notifies Slack — all before the on-call engineer has finished reading the alert. If you’ve been following the DevOps tooling space over the last 18 months, you’ve probably seen some version of this pitch. But here’s the honest question: How much of this is actually running in production today, and how much is still a well-staged conference demo? This article cuts through the noise. We’ll look at what AI agents in DevOps actually are, where they’re delivering real value right…
Author: drweb
If you work with financial data, you have probably asked yourself how to forecast volatility. I keep coming back to this problem because simple moving averages do not capture the clustering effect of volatility. That is where the GARCH model helps. It models time-varying variance in a way that reflects how markets actually behave. In this article, I walk through the GARCH model from scratch, show you how to fit it in Python, and highlight the practical differences between its variants. The GARCH model shows up everywhere in quantitative finance. Risk managers use it to estimate Value at Risk. Options…
Learn how to use systemctl with the –failed flag to instantly spot broken services on your Linux system, without scrolling through hundreds of healthy ones. A server starts acting up, something is clearly wrong, but systemctl status dumps a wall of text that tells you nothing useful. You scroll, you squint, you give up and open the logs. The faster move is to ask systemd one simple question, which services actually failed, and let it answer in two lines instead of two hundred. Every command below was tested on Ubuntu and Rocky Linux, and the behavior is identical on any…
SUSE today revealed it is collaborating with multiple providers of artificial intelligence (AI) agents with the ability to manage IT infrastructure resources via integrations with the Model Context Protocol (MCP) server embedded in its platforms. Announced at the SUSECON 2026 conference, AI agents from Fsas Technologies, n8n and Revenium, Stacklock and Amazon Web Services (AWS) can invoke the MCP server that SUSE has embedded in its Rancher Prime and SUSE Multi-Linux Manager offerings. Rick Spencer, general manager, engineering at SUSE, said that capability makes it possible, for example, for the Amazon Quick AI agent that AWS developed to automate workflows…
Python ships with a philosophy that prioritizes readability and transparency. The interpreter executes source code directly, which means anyone with access to your .py files can read, copy, or modify your logic. For open-source projects this is a feature. For proprietary software, commercial products, or any code that handles sensitive algorithms, this openness becomes a liability. Obfuscation addresses this problem by transforming readable source into something that still executes correctly but resists human comprehension. The goal is not to make code impossible to run, but to make reverse engineering impractical. String literals get encoded, class and function names get replaced…
Python database programming isn’t just about writing queries, it’s also about understanding the right tools. From sqlite3 to MySQL and PostgreSQL (via mysql-connector-python and psycopg2), and even NoSQL with pymongo, each plays an important role. You also need a basic understanding of SQLAlchemy and pandas. In this article, I’ve combined all these concepts into a set of 100 Python SQL & Database MCQs, helping you prepare for your upcoming interviews or exams. 100 Python SQL & Database MCQs Each of these 100 Python SQL & Database MCQs covers a key concept. Master them, and you’ll be interview-ready. Q1. Which built-in…
Your on-call phone rings at 2 AM. Application timeouts are climbing and someone is already asking for updates in the incident channel. You open one dashboard. Then another. Then a cloud portal. Then the legacy monitoring tool nobody wanted to retire. Forty minutes later you are still figuring out which SQL Server instance is actually responsible. Meanwhile, the LCK_M_S wait chain has quietly been building for an hour. Let us talk about SQL Server Monitoring Across Cloud, Hybrid, and On-Prem. This is not a tooling problem. Most teams have tools. It is a visibility problem. And it becomes painfully obvious…
Agentic AI is rapidly entering DevOps pipelines, platform engineering platforms and cloud-native infrastructure. DevOps Experience 2026 brings the community together to decide which tools matter, how they should be governed and what comes next. The DevOps ecosystem is entering one of its most consequential transitions since the rise of CI/CD. Across the industry, vendors are racing to introduce agentic AI systems designed to automate DevOps workflows. These systems promise to assist with everything from pipeline orchestration and incident response to infrastructure management and security remediation. The promise is compelling: faster delivery, less operational toil and smarter automation. But alongside that…
A critical vulnerability in a popular Microsoft GitHub repository could allow a threat actor to easily exploit its CI/CD infrastructure to run arbitrary code in the repository and gain access to secrets, according to researchers with cybersecurity firm Tenable. In an advisory issued April 21, Rémy Marot, staff research engineer at Tenable, wrote that “by exploiting this vulnerability, an attacker with an unprivileged GitHub account could exfiltrate secrets available to the workflow run and perform unauthorized operations on the target GitHub repository.” The security flaw can be easily exploited, and illustrates the growing security risks as CI/CD pipelines play an…
Images and NumPy arrays are closely related in Python. An image is fundamentally a grid of pixel values, and NumPy makes it easy to work with that grid directly. Whether you are building a machine learning pipeline or just need to manipulate pixels, converting an image to a NumPy array is the first step. Different Python libraries read images in different ways. Each approach produces a slightly different array shape, dtype, and value range. Here is how the four most common methods compare. TLDR Pillow + NumPy – best for general use, no extra dependencies OpenCV – fastest for bulk…