The landscape of data management has dramatically shifted from rigid, siloed systems to flexible, integrated platforms designed to handle the unprecedented volume, variety, and velocity of modern data. This evolution is driven by the increasing demand for real-time insights, advanced analytics, and sophisticated AI/ML capabilities across all business functions.You may have read my previous post about lakebases, this post digs a little bit deeper into the modern Business Intelligence (BI) platform, delineating the roles and optimal applications of three pivotal architectural paradigms: the Data Warehouse (DW), the Data Lakehouse (DLH), and the emerging Lakebase. While Data Warehouses traditionally excel in…
Author: drweb
We may have just witnessed the closing of one of the most iconic chapters in modern tech. Microsoft CEO Satya Nadella recently stated that the company is transforming from a “software factory” into an “intelligence engine.” This came on the heels of another round of layoffs — with now over 7% of Microsoft’s workforce having been laid off recently — even as the company continues to report strong earnings. The implications of Nadella’s statement are far more profound than just a catchy metaphor for AI adoption. This may be the official end of the era Marc Andreessen launched when he…
If you’re working with networks, managing domains, or troubleshooting connectivity issues, two essential tools you’ll come across are dig and nslookup, both network utilities help you query domain name records, inspect DNS responses, and even verify mail servers or IP addresses associated with a domain. In this guide, you’ll learn how to install dig and nslookup on major Linux distributions, how to use both tools effectively, and explore real-world examples for DNS lookups, reverse lookups, mail server checks, and more. What Are dig and nslookup? dig, short for Domain Information Gopher, is a DNS lookup utility used to query DNS…
Numerous reports consistently show that companies do not pay enough attention to mobile application security. One of the most common vulnerabilities in mobile apps involves insecure network communications, which attackers can exploit to carry out man-in-the-middle attacks. Another major issue is misconfiguration, which can expose sensitive components or weaken app defenses. Perhaps most concerning, however, are cases where user data is stored in plaintext. In 2025, the threat landscape has evolved further, with cybercriminals increasingly using deepfake technology to steal biometric data, such as facial recognition profiles and voiceprints. These advanced tactics allow attackers to break into mobile apps from the…
The digital panorama is a dynamic and ever-moving entity. Applications are no longer monolithic giants dwelling on predictable servers. Instead, they are complex webs of microservices, ephemeral serverless capabilities and containerized workloads, all operating across dispersed, multi-cloud environments. While this complexity fuels innovation and scalability, it also presents a formidable challenge: how do you truly understand what’s happening inside these complex structures? For years, the solution has been “observability,” often described by its “three pillars”: Metrics, Logs and Traces. These pillars have served us well, offering important information about system health. However, as structures grow in scale and dynamism, the limitations…
SQL Saturday Baton Rouge is a great event hosted on LSU’s campus that has some of the best food, presenters, and attendees in the country! Had some incredible questions for my session and learned a ton throughout the conference. Thank you to all the sponsors and volunteers who make this event happen year after year (16 years running!). It’s one of the first events I ever spoke at (https://dataonwheels.wordpress.com/2022/08/23/sql-saturday-baton-rogue-recap/), and I’m so excited I was able to speak here again! Here’s a link to the event where you can find other incredible speakers and sessions! Pictured below are some of…
Python has long been the go-to language for machine learning. With the release of Python 3.13, the language brings improved performance and subtle changes that streamline ML workflows even further. Whether you’re just getting started or revisiting the fundamentals, this guide lays out the essentials of machine learning using Python’s latest version—with clarity, practicality, and a focus on real-world examples.What Is Machine Learning, Really?Machine learning is a method of teaching computers to recognize patterns and make decisions without being explicitly programmed. It relies on algorithms that learn from data, refine their output over time, and make predictions or classifications based…
A survey of 185 software development professionals who have adopted the Argo continuous delivery (CD) platform finds that 97% are now using it in production environments, with 60% running Argo for more than two years. Only 10% of respondents are still evaluating Argo.Conducted by the Cloud Native Computing Foundation (CNCF) that oversees the development of Argo, the survey finds 42% now oversee more than 500 applications per Argo CD instance, with 25% connecting those instances to more than 20 clusters. More than three-quarters of respondents are managing six or fewer instances of Argo, the survey finds.Originally developed by Intuit, Argo…
When I started building the CIAM Platform and scaling it to serve billions of users, our DevOps processes looked quite different from what’s possible today. We spent countless hours managing deployments, monitoring infrastructure and responding to incidents that could have been prevented with better predictive capabilities. Today, artificial intelligence (AI) is fundamentally changing how DevOps teams work, and I want to help you understand exactly how these changes can benefit your organization. Think of traditional DevOps as manually piloting an airplane. You need skilled engineers monitoring dozens of instruments, making constant adjustments and responding quickly when problems arise. AI-powered DevOps is…
The race to accelerate modernization across business units within an organization has led to an API explosion, but with little consideration for how AI is changing the way different software systems communicate with each other, share data and trigger actions. We’re seeing AI tools not only consume APIs at an unprecedented rate but also accelerate their creation, which in turn spurs uncontrolled proliferation and decentralized management that surfaces new challenges and risks, especially if the underlying API ecosystem isn’t well managed. The nature of how AI interacts with systems requires a new kind of API paradigm – one that’s more dynamic,…