Operations | Monitoring | ITSM | DevOps | Cloud

In backend engineering, many days follow a familiar rhythm: coffee, code reviews, maybe deploying a new feature. But occasionally, the routine is interrupted by a message that signals a different kind of challenge, like a Slack notification from the security team: “Hey, we’ve identified a potential issue. Need to sync up.” This post details one such instance—our journey addressing CVE-2024-21626, a privilege escalation vulnerability reported in Rancher.

When your Docker container isn't behaving the way you expect, you need to get inside and see what's going on. Maybe your app is throwing errors, a service won't start, or you just need to check some configuration files. Getting into a running Docker container is simpler than you might think, but there are several ways to do it depending on your situation. This guide shows you exactly how to log into Docker containers, troubleshoot common issues, and debug your applications effectively.

The cloud gave us agility, but it also introduced fragmentation. And in most companies, no one’s fully owning the sprawl. One team deploys a new service in a hurry. Another forgets to shut down a dev environment. Meanwhile, batch jobs run 24/7 on oversized instances. And no one quite knows why your bill is $10K higher this month. The result? A growing source of cost overruns, performance headaches, and operational inefficiencies. This is exactly why cloud workload management is so crucial.

When most people picture a data centre, they might think of a bland industrial shell—cold, humming, and forgettable. But look closer, and you’ll find something far more profound. A data centre is a heavy, complex, and finely tuned space where an immense volume of information flows, transforms, and creates the digital world we rely on. In many ways, it feels like magic. And yet, so does nature. Both deserve respect.

Managing and deploying applications across multiple Kubernetes clusters presents significant challenges, especially as the number of clusters grows. Traditional methods, like manually applying Helm charts or manifests per cluster, become cumbersome, error-prone, and difficult to scale or maintain consistency for Day 2 operations. While Rancher allows managing Helm chart repositories and apps, this is done on a per-cluster basis via the UI.

AI spending continues to accelerate. In 2025, experts project that companies will collectively spend about $644 billion on generative AI alone — a whopping 76.4% increase from 2024. This puts it a mere $79 billion behind the public cloud as a whole, signaling the most seismic interval of new infrastructure investment since the dawn of the public cloud.

Lately, there has been a growing buzz around the concept of “Vibe Working,” where teams are leveraging AI to dynamically share, develop, test, and transform “fuzzy” ideas into something useful in real-time. I view this approach as one of the next significant evolutions in our professional and technological landscape. Reflecting on my own journey in technology, I’ve observed how the pace of innovation and collaboration continually reshapes our daily workflows.