Operations | Monitoring | ITSM | DevOps | Cloud

AI cost monitoring: what it is, how it works, and why real-time visibility matters

AI cost monitoring is the continuous tracking of AI and LLM spend in real time, broken down by the models, features, teams, and customers generating it. It is not the same as reading the monthly bill - done well, it shows spend as it happens, flags anomalies before they become invoices, and connects every dollar to an outcome so finance can protect AI ROI instead of explaining it after the fact.

4 Cloud-Native Challenges AI SRE Is Solving in 2026 and the 3 New Ones to Look Out For

AI SRE is making real strides in resolving some of the greatest pains related to incident response, troubleshooting, and complex root cause analysis. The on-call rotation, the war room, the week-long RCA, and the ticket queue that ate a third of every platform engineer’s week all look different now than they did two years ago.

The Technologies Shaping the Future of Work

Work is changing fast. The old nine-to-five grind feels outdated. People want flexibility. They want meaning. They want to avoid soul-crushing repetition. Technology drives this shift. New tools handle the boring stuff. They connect teams across continents. They make work more human, not less. The future workplace looks different than anyone predicted. It is more collaborative. It is more creative. It is powered by smart machines that amplify human potential. This transformation is already happening. Here is what it looks like.

Faster Construction Estimates Start With Better Takeoff Control

Estimating pressure has always been part of construction. Plans come in late, bid dates stay firm, and estimators are expected to move quickly without missing scope. The problem is not only speed. The real challenge is producing a number that can survive review, negotiation, award, and handoff to the project team.

GPU monitoring in OpManager: Full visibility for every AI workload

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.

Only 1 in 4 Employees Follow AI Policy: How to Fix It

AI is more than just a tool—it's a transformative experience for the modern workforce. But as employees "run fast" to adopt AI, a critical gap is forming between innovation and safety. In this video, Brooke Johnson, Ivanti’s Chief Legal Counsel and SVP of People and Security, discusses the "natural tension" between AI excitement and the necessity for responsible, secure implementation. With only 25% of employees reporting consistent policy adherence, the risk of "Shadow AI"—unsupervised tool use—has never been higher.