Operations | Monitoring | ITSM | DevOps | Cloud

AI's False Efficiency Curve: How To Save And Protect Your Margins

The popular narrative around AI economics is changing. At one time, Moore’s Law conditioned us to expect that smarter, faster computing would steadily get cheaper. When it comes to AI, that expectation holds true at the unit level. Per-token costs are indeed declining. But the number of tokens consumed per task is growing exponentially, making total costs spike. The tension here is important: on paper, inference is getting cheaper.

Calico Whisker vs. Traditional Observability: Why Context Matters in Kubernetes Networking

Are you tired of digging through cryptic logs to understand your Kubernetes network? In today’s fast-paced cloud environments, clear, real-time visibility isn’t a luxury, it’s a necessity. Traditional logging and metrics often fall short, leaving you without the context needed to troubleshoot effectively. That’s precisely what Calico Whisker’s recent launch (with Calico v3.30) aims to solve. This tool provides clarity where logs alone fall short.

The Future of IT: Where Will AIOps Be in Less than 5 Years?

The future of IT: Where will AIOps be in less than 5 years? In this video, we dive deep into the evolution of Artificial Intelligence for IT Operations (AIOps) and what the next half-decade holds for businesses, IT teams, and technology leaders. AIOps is no longer just a buzzword—it’s becoming a critical part of IT operations, enabling predictive analytics, automated incident management, root cause analysis, and faster decision-making.

Top Node.js Application Challenges and How Monitoring Solves Them

Deploying a Node.js application may feel straightforward at first. Everything checks out in tests, staging runs smoothly, and early users run into no problems. But as real traffic ramps up, hidden problems start to appear in unexpected ways. Requests fail intermittently, latency spikes without warning, memory usage climbs silently, and logs are scattered across multiple processes making it nearly impossible to trace the root cause.

You Don't Need a Five-Year AI Plan. You Need a Five-Week One.

In my travels, I constantly hear about plans that promise to “unlock the full power of AI” down the road. The usual advice is to start small with a few pilots, then gradually scale up from there. It looks good on paper, but in practice, it becomes a months-long slog of one-off experiments that burn a lot of capital, but usually generate little impact on their own.