Alan reflects on a chaotic yet inspiring year in DevOps, highlighting the rise of AI in engineering, the maturation of DevSecOps, the evolution of hybrid work culture, the surge of platform engineering and IDPs, and the continued strength and inclusivity of the DevOps community — while acknowledging the talent crunch, tool sprawl and security theater that still challenge the industry.
Author: drweb
Working with statsmodels feels great when everything runs smoothly.But we’ve all hit those frustrating moments when the library throws cryptic warnings, produces NaN values, or refuses to converge.After building dozens of statistical models with statsmodels, I’ve learned that most problems fall into predictable categories with straightforward solutions.Statsmodel Beginner’s Learning PathWhat causes multicollinearity errors and how do you resolve them?Statsmodels uses generalized inverse for linear models, which means cases of almost perfect multicollinearity or ill-conditioned design matrices might produce numerically unstable results. You’ll notice this when coefficients have wildly large standard errors or when signs flip unexpectedly between models.The Variance Inflation…
Vulnerability management in 2025 is overwhelmed by escalating CVEs and costly breaches; organizations must shift from slow, manual patching to continuous, risk-based, AI-powered remediation to stay secure.
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When you’re building regression models with Python’s statsmodels library, you’ll quickly encounter add_constant. This function determines whether your model fits y = mx + b or just y = mx, which fundamentally changes how your model interprets data.I’ll walk you through what add_constant does, why you need it, and how to use it correctly in your statistical modeling work.Statsmodel Beginner’s Learning PathWhat Does add_constant Actually Do?The add_constant function adds a column of ones to your data array. That’s it at a mechanical level. But what this column of ones accomplishes is mathematically significant.When you run a linear regression, you’re estimating…
Modern DevOps teams face outages driven by complex dependencies and AI-enabled systems; success now depends on moving from reactive monitoring to prescriptive, AI-assisted incident resolution that shortens MTTI and MTTR.
Do you know who managed to cut costs by a staggering 90% by abandoning microservices for a monolith in May 2023? Not a cash-strapped startup or an indie project—Amazon itself, for its Prime Video service. The same AWS that earns billions every year by selling microservices infrastructure admitted that, sometimes, a good old monolith wins. This reversal from the company that practically wrote the playbook on distributed systems sent shockwaves through the cloud-native community. Amazon later removed the original blog post, but the internet never forgets, as you’ll see later. I’ve been speaking up against unnecessary or premature use of…
Cary, North Carolina, USA, 26th November 2025, CyberNewsWire
Let me be clear. I do not like the term “vibe coding.” The label is sloppy and the concept it pushes is even sloppier. It lumps together two very different practices and turns a serious profession into a trend. On one side, experienced developers use AI to speed up real work. They ask pointed questions, […]
Statsmodels organizes its functionality into topic-based subpackages rather than dumping everything into a single namespace. Understanding this structure helps you find the right models quickly and import them efficiently.The library provides two primary access points: statsmodels.api for general use and statsmodels.formula.api for R-style formula syntax. Beyond these, specialized subpackages contain models, tools, and functions organized by statistical domain.Statsmodel Beginner’s Learning PathHow the API structure worksWhen you import statsmodels.api, you’re not loading the entire library. The API module collects the most commonly used classes and functions from various subpackages and presents them through a clean interface.Standard import convention: import statsmodels.api as…