Operations | Monitoring | ITSM | DevOps | Cloud

In today’s complex IT environments, reliable monitoring isn’t optional — it’s essential. From critical infrastructure in Government & Defense to highly regulated sectors like Healthcare, Energy, and Finance, organizations worldwide trust NiCE to deliver secure, future-ready monitoring solutions.

AI-first observability addresses two of the most pressing troubleshooting challenges: complex IT environments and AI-generated code. But understanding how to implement AI in a way that brings ROI, requires cutting through the hype and maintaining realistic expectations, while keeping a forward-thinking vision. In this blog post, we bring practical tips for including AI in your next observability RFP. The article is based on a webinar held with Logz.io founders, CEO Tomer Levy and CTO Asaf Yigal.

We talked to 7 companies in August 2025 who were looking to switch from New Relic. One engineering director said they're paying $1,000 a month and only ingesting 10% of their traces. Teams are defaulting to aggressive sampling, some at 1%, others at 10%, to manage costs.

This could’ve been prevented. This should have been prevented. This too. We all hate getting tagged in PRs. The time, the blame for when you inevitably miss something, and constant “I wouldn’t have written it that way” feeling is just hard to shake. LLMs promised this would get easier. Promised they would do it for us. But as we’ve seen, we’re not there yet. But this is what Sentry does for a living. We catch bugs… in prod.

Application Performance Monitoring (APM) helps you understand how your software runs in production. When you track the right metrics, you see how requests move through your system, where slowdowns happen, and how resources are being used. With this knowledge, you can spot issues early and keep your applications reliable for your users. In this blog, we discuss the key APM metrics to monitor, grouped into categories, and why each one matters for performance and user experience.

The New Physics of IT has revealed its second law: resilience isn’t reactive. It is the architecture of leadership itself.

When we set a memory limit for a container, the expectation is simple: if the app leaks memory, the OOM killer steps in, the container dies, Kubernetes restarts it, done. But reality is messier. As a container gets close to its memory limit, allocations don’t just fail instantly. They get slower. The kernel tries to reclaim memory inside the cgroup, and that takes time. Instead of being killed right away, your app just crawls.