Operations | Monitoring | ITSM | DevOps | Cloud

When was the last time you asked a developer if they actually use the platform you built for them, or whether they’ve found a faster way around it? We talk with companies every day who deal with this exact scenario. They spend months or even years building their IDP. Then a new project requires a stack or workflow that the IDP doesn’t support. The developer is under pressure to deliver, so they spin up their own solution. This is why most IDPs fail quietly.

AI promise and AI capabilities often diverge, with developers often reporting much faster code production, but not enough change in how incidents are handled. When the rate of change is faster than ever, but the rate of recovery from incidents isn’t moving, developers wind up stuck in firefighting mode. And, when these systems fail, it’s costly. According to PagerDuty’s State of AI-First Operations, over a third of surveyed companies report losing $500K per hour of downtime.

We’ll be rolling out new Slack capabilities to eliminate more manual toil from your incident workflow: click once to promote any alert to an incident, get dedicated channels created automatically, page responders without leaving Slack, and manage all your settings in one place. This is part of our path to autonomous operations: reducing toil, protecting your capacity, and letting you stay in flow. If you’re only using PagerDuty for on-call scheduling, you’re missing the full picture.

Lots of big companies lock down their IT infrastructure in the internal network, sometimes they even use only locally mirrored repositories. I totally understand this, especially since our CVE-2024-49369. Nowadays, when LLMs find security holes even in OpenBSD, you definitely shouldn’t expose any services to the public without need.

There’s a new question teams are asking. How can we prevent AI agents from deleting production. When Cursor deleted PocketOS’s entire production database in nine seconds, the agent wasn’t malfunctioning. It had full technical capability, but it was inferring operational authority from static code rather than live environment state. That gap between capability and context is the root cause. This article breaks down exactly how that happens, and what runtime visibility does to stop it.

Over the past decade, cloud computing has evolved from an emerging technology into the foundation of modern digital infrastructure. However, the latest industry research shows that the industry has now crossed a critical threshold. The conversation is no longer about whether to adopt cloud, cloud-native technologies, or AI. Instead, it has shifted toward operational efficiency, economic predictability, and infrastructure at scale.

SQL Prompt's April releases focused on SSMS 22.5 compatibility, a new AI transparency hub, and dark mode readability improvements.

Data Center Infrastructure Management (DCIM) software has matured considerably over the past decade. Deployments are faster, interfaces are easier to use, integrations are deeper, and organizations across industries are seeing real, measurable results. According to Gartner, DCIM software has reached a critical inflection point in the Hype Cycle: the Plateau of Productivity.

In the evening of May 5th, 2026, large parts of the German web briefly went dark. For a few hours, anyone trying to load a.de address through a major DNS resolver got errors instead of websites. Bahn.de, Amazon.de, and Spiegel.de were among the affected. Major brands like Telekom, DHL, and Sparkassen felt it too, along with hosting providers Hetzner, Strato, and Ionos.