Operations | Monitoring | ITSM | DevOps | Cloud

5 ways agentic AI in ITOps will close the gap between alerts and action

Agentic AI in ITOps has emerged as a practical way to go beyond just detecting incidents. Modern IT teams have invested heavily in observability, yet the gap between detecting an issue and resolving it continues to widen. Three major challenges are driving this shift: This is where agentic AI makes a difference.

Claude outage on July 17, 2026: what happened and how StatusGator caught it early

Claude had a global outage on July 17, 2026, driven by “529 Overloaded” server errors that hit the API, Claude Code, the web app, and the desktop app. It lasted about 1 hour and 32 minutes. StatusGator detected it and sent an Early Warning Signal at 14:30 UTC, 27 minutes before Anthropic acknowledged it at 14:57 UTC.

The Two-Clock Trap: A CRO's Diagnosis of Why Enterprise AI Fails at the Sourcing Table

Every AI engagement runs on two clocks, and they no longer agree. The first is the intelligence clock, and it runs fast. The world it keeps time with re-renders every quarter. Models improve, inference costs fall, automation tightens, and the cost of producing a unit of work keeps dropping. This is the clock an enterprise believes it is buying when it invests in AI. The second is the contract clock, and it stopped years ago.

Why AI-Generated Code Needs Monitoring More Than Handwritten Code

Like it or not, vibe coding is here to stay. It’s too easy to just go away. Maybe if the per token cost rises too much at some point that it becomes cheaper to hire a junior… But until then, you’d better get used to it. For now, tools like Cursor, Copilot, and Claude let developers (and plenty of non-devs) ship full-stack apps faster than a junior is able to completely grasp the concept of the app they’re working on. And that’s pretty neat.

The True ROI of Cloud Migration: Modernization, and AI Unlock

For years, the cloud migration business case was framed around one comparison: “Will AWS be cheaper than our data center?” That question still matters, but it is no longer where the value is. The 2017-2024 wave of mass migration is largely complete. Most enterprise workloads are already in the cloud - often in a lift-and-shift state: oversized instances, commercial-OS BYOL, on-prem-shaped network designs, and legacy frameworks that block the next step.

What Is LLM Observability? A Complete Guide

If you run LLM features in production, your most dangerous failures are the ones your monitoring never flags. Your LLM feature passed every test, and the demo went great. Three weeks after launch, a support ticket lands: the chatbot quoted a refund policy that does not exist. The dashboards are all green, and the same prompt answers correctly when you retry it. This is the blind spot LLM observability exists to close. Your existing tools saw the request come back fast with a clean status code.

Shipped: Take your AI cost table straight into your own reports

A design partner told us the AI Explorer table needed a way to get data out so it could be saved and shared elsewhere. Now you export the whole view in one click, cost, tokens, cache, and model count all included. The values come through as clean numbers, not text you have to scrub. It’s the same pattern as Explorer, so there’s nothing new to learn.

Enterprise AI Governance Made Simple with Nexthink's AI Activation Hub

Over the past year, organizations have embraced AI at an extraordinary pace, and Nexthink AI Activation Hub powered by AI Drive has helped customers make sense of that transformation by helping organizations discover the growing wave of AI tools entering the workplace, rapidly triage and govern them, accelerate adoption of approved AI solutions, and measure the impact of AI across the enterprise.

Why Legitimate AI and Human Users are Getting Elbowed Out of Your Infrastructure

The internet has always been a bit of a noisy, crowded place, but lately it feels like a never-ending brawl in the aisles of some superstore that sells everything from penny candy to luxury jets. That is essentially what running an enterprise website or API endpoint feels like in 2026: brawl management. Automated scripts are now advanced, highly coordinated AI agents acting on behalf of competitors, scrapers, search engines, and sometimes actual buyers. They make eCommerce chaotic and urgent. It makes customers frustrated and fickle.