Operations | Monitoring | ITSM | DevOps | Cloud

Microsoft Azure has become one of the most widely adopted cloud platforms for running business applications, databases, containers, analytics workloads, and enterprise services. Modern Azure environments now extend far beyond virtual machines, encompassing services such as Azure Kubernetes Service (AKS), Azure SQL Database, Azure Functions, storage accounts, networking services, and serverless applications.

Top tips is a weekly column where we highlight what's trending in the tech world and list practical ways to explore these trends. This week, we're looking at something we rarely think about until the end of the day: the tiny digital habits that quietly eat away at our time. Have you finished a workday feeling busy but strangely unaccomplished? You started with the best intentions.

Riya has managed IT operations at a mid-sized FinTech company for six years. She knows the infrastructure inside out: Every server, monitoring alert, and compliance requirement is owned by her team. So when Riya heard the engineering lead mention their new internal developer platform in a quarterly review, she assumed her team would be looped in eventually. This did not happen. Three months later, Riya's team was called in to investigate an outage.

Organizations are increasingly integrating GenAI capabilities into their applications to deliver richer, more contextual user experiences—from AI-powered customer support and enterprise search to content generation, virtual assistants, and automated workflows. To build and scale these GenAI-powered experiences, they are turning to platforms such as Amazon Bedrock, which provides access to foundation models that developers can integrate into their applications.

A friend who runs data engineering at a mid-sized logistics company once showed me something that made me laugh, and then made me a little sad. Her team spent four months building a chatbot that was supposed to answer simple questions like "how many shipments are delayed in the Chennai warehouse right now." The bot worked beautifully in the demo. Then someone asked it a real question, and it confidently returned a number that was off by almost a factor of ten. Not because the model was dumb.

Top tips is a weekly column where we highlight what's trending in the tech world and list practical ways to explore these trends. This week, we're talking about boreout, the lesser-known cousin of burnout, and how to stay engaged as AI takes on more of the routine work. There was a time when finishing your work early felt like winning. Now it somehow feels... suspicious. You glance at your inbox and nope, there are no new emails.

AI has moved to be a core part of enterprise infrastructure. GPUs are the engines behind that shift. Every training run, every inference request, and every fine-tuning job depends on GPU chipsets that are expensive and delicate. A GPU that overheats, runs out of memory, or sits idle for hours doesn't just slow a project down, it quietly drains the IT budget. Most monitoring tools weren't built with this hardware in mind. This leaves AI and DevOps teams blindsided when a job fails or a chipset degrades.

Billing has always been one of the parts of running an MSP that doesn't scale on its own. More endpoints, more tickets, and more monitors under management all mean more usage to track—and for most MSPs, that usage still gets tallied by hand before an invoice can go out. Not anymore. We're rolling out the MSP Central billing module, powered by our integration with Zoho Billing—and it's live with usage-based billing from day one.

The save for later button has quietly developed a bad reputation. It is associated with every overflowing bookmarks folder, every article we'll "definitely read this weekend", and every YouTube playlist titled Watch Later that's slowly turning into a historical archive. Somehow, the blame always lands on the same little button. It's become the internet's favorite accomplice for procrastination. I'd like to offer a defense.