Operations | Monitoring | ITSM | DevOps | Cloud

From GPUs to Futures: The Financialization of AI Compute

The decision by CME Group and Silicon Data to create computing-power futures may become one of the most important infrastructural developments in the current stage of the artificial intelligence industry. While Nasdaq futures reflect expectations for technology-heavy growth stocks, including AI-related names, computing-power futures would track a more fundamental input: the cost of the infrastructure on which AI companies increasingly depend. In effect, for the first time, the market is beginning to formalize computing resources as an independent financial asset, comparable in function to oil, electricity, or industrial metals.

Nano Banana Three-Model Showdown: Which One Actually Fits Your Needs?

Not every image generation task is the same - and neither is every Nano Banana model. If you've landed on Kimg AI looking for the right tool, this breakdown is for you. Banana AI brings together multiple Nano Banana versions under one roof, so the only question left is: which model should you reach for first?

The AI Productivity Paradox: We're Measuring the Gains and Missing the Costs | Harness Blog

For the past year, I've been hearing a version of the same thing from engineering leaders: AI tools are working, productivity is up, the business case is there. And yet, something about the picture still feels incomplete. So we decided to go find out how widespread that feeling actually is. We surveyed 700 engineers and managers across five countries, and published the results in the State of Engineering Excellence 2026.

AI DevOps in 2026: How AI Coding Tools Are Breaking Your CI/CD Pipeline (and How to Fix It)

AI coding tools turned every engineer into a 10x developer. Now your CI/CD pipeline is the bottleneck. Learn how to handle 10x more deploys per engineer with Qovery's dual deployment model. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Enhancing Your Search Skills with Liang Chen

What does it take to reinvent network visibility from the ground up? In this episode of Next-Gen Network Heroes, Bob sits down with Liang Chen, Senior Network Architect at Texas Children’s Hospital and creator of a next-generation network traffic analyzer built for real-time, packet-level visibility. Liang shares how he built a platform capable of analyzing traffic at up to 200Gbps with zero packet loss—unlocking deeper network forensics and faster troubleshooting in mission-critical environments.

True Visibility: How Liang Chen is Rethinking Network Monitoring

What happens when deep networking expertise meets low-level programming and a passion for invention? In this episode of Next-Gen Network Heroes, host Bob Slevin sits down with Liang Chen, Senior Network Architect at Texas Children's Hospital and a true innovator in network performance and visibility. With more than 25 years of experience in networking, plus advanced expertise in programming languages like C and Assembly, Liang has built his own next-generation traffic analysis platform from the ground up—designed to provide real-time, packet-level visibility at massive scale.

Total Economic Impact study finds LogicMonitor Edwin AI delivered a 313% ROI and payback in 6 months or less

Forrester Consulting’s Total Economic Impact study found that a composite organization based on interviewed customers achieved 313% ROI and payback in less than 6 months with LogicMonitor Edwin AI. AI for IT operations has a credibility problem. The market is crowded with claims about speed, automation, and intelligence, while buyers are left doing the harder work of separating measurable impact from vendor language.