Operations | Monitoring | ITSM | DevOps | Cloud

In a world where AI and automation are redefining enterprise IT, there’s one harsh truth that often gets overlooked: most automation initiatives fail before they begin. Not because the technology isn’t ready, but because the strategy isn’t. Too often, teams fall into well-worn traps—automation anti-patterns—that stall progress, waste resources, and fail to deliver meaningful impact. Let’s call them what they are: automation mistakes.

Google Cloud Platform (GCP) might not always be the loudest name in the cloud room. But it’s gradually become a powerhouse for organizations running data-intensive, AI/ML, and global-scale applications. We also can’t ignore that GCP offers a backbone powered by Google’s own infrastructure (the same one that runs YouTube, Gmail, and Search).

I’m excited to announce a new capability in Redgate Monitor Enterprise: the Sensitive Action Log. As infrastructure becomes more complex, it’s more critical than ever to maintain control over how your monitoring environment is configured and accessed. Whether you’re responding to internal compliance policies, preparing for audits, or simply tightening operational security, it’s key to understand who did what, when.

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.

The proliferation of Internet of Things (IoT) devices has transformed various sectors, offering enhanced efficiency and connectivity. However, this expansion also introduces significant security challenges. Implementing robust firewall monitoring is essential to protect these devices and the networks they inhabit.

The software supply chain has become the backbone of modern IT environments. It powers applications, underpins operational processes, and drives innovation within organizations across industries. Securing the software supply chain has moved from a peripheral concern to a central element of cybersecurity: The vast network of code, dependencies, integrations, and third-party tools that comprise the supply chain is increasingly under siege from cyber threats and at risk of exploitation.

As AI adoption increases, the race to real, durable AI value intensifies. Almost every organization that can use AI is using AI — but one of the most troubling trends I’ve observed revolves around talent. Right now, most organizations use AI to increase internal efficiencies — do quick research, write quick emails, start a new project at the 50% mark rather than the 0% mark, etc. But some executives I’ve talked to are taking a more aggressive approach.