Operations | Monitoring | ITSM | DevOps | Cloud

Kubernetes has quickly made itself known as the de facto platform for today’s applications and the most common way to build an infrastructure platform for application developers. Kubernetes offers immense flexibility and power, but it can introduce its own unique set of operational challenges. If you find yourself spending more time chasing down cluster issues than helping your developers work hassle-free, this guide is for you.

Cloud computing was already booming before 2020. But in the following two years, remote work flourished, and cloud adoption soared. The trend continues to accelerate — even faster now. Some companies have since returned to the office. Others are adopting hybrid models, balancing work-from-home and in-office. Yet, there’s more to the rise of cloud computing than remote working.

At IBM’s Think conference this week, the company made a bold announcement: 94% of its HR functions are now handled by AI, a shift they claim will generate $3.5 billion in savings over the next two years. These are staggering numbers. And while the cynic in me can’t ignore that this announcement was made at what is, effectively, a sales conference – especially one that coincided with the launch of IBM’s AI Agent Store – the scale of those numbers deserves attention.

We are standing at the threshold of one of the most transformative technological shifts in modern enterprise history. AI is no longer on the horizon – it’s here, it’s powerful, and it’s already reshaping the way businesses think about productivity, creativity, and competitive advantage. OpenAI’s recent report, ‘AI in the Enterprise‘, offers a concise and thoughtful roadmap for leaders seeking to implement AI within their organizations.

Let’s be honest, most AI (Artificial Intelligence) tools today are relatively smart but not always super useful. You ask them to explain something, write an email, maybe generate some code, but the moment you want them to do something real, like schedule a meeting, file a bug report, or move stuff across your tools, they just stare blankly. That’s where MCP comes in. MCP stands for Model Context Protocol.

SQL Server’s filtered index is one of the most effective features for improving query performance and reducing index maintenance. Whether you’re working with big tables that don’t have much data or queries that constantly filter by the same conditions, filtered indexes offer a smart way to focus only on the rows that matter most.

Monitoring doesn't always need to be complex. In this guide, we'll show you how to transform some raw logs into usable metrics using a lightweight, open-source setup. We'll also use the Telegraf agent to convert logs into Graphite metrics that you can easily visualize and alert on. This is ideal for system admins, DevOps beginners, or anyone interested in building more innovative monitoring pipelines from scratch.

You spin up a few test environments. Someone forgets to shut one down. A cost spike hits your Azure bill. And no one saw it coming. Does this sound familiar? Surprise cloud bills are still a thing today. For teams trying to balance innovation with financial discipline, the Azure Budget feature offers a first line of defence against surprise cloud costs.

When Solr performance degrades, everyone notices - except maybe your monitoring system. The right metrics can alert you to problems before your users start complaining. This guide walks through the essential Solr metrics that matter for production deployments.