Operations | Monitoring | ITSM | DevOps | Cloud

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.

When Citrix introduced License Activation Service (LAS), customers transitioned from the traditional file-based licensing model to a new cloud-connected licensing architecture. For most administrators, the migration itself was straightforward. The biggest surprise came afterwards, when familiar licensing metrics such as licenses in use, licenses available, and peak license usage disappeared from the Citrix License Server. The answer is no.

We’re making it easier to organize your monitors from the moment you add them. Previously, clicking Add would immediately add a monitor to your board. If your board already contained one or more groups, new monitors were automatically placed in the Ungrouped section, requiring an extra step to move them into the correct group. Now, clicking Add opens a list of your monitor groups, allowing you to choose exactly where the monitor should be added.

See how Qovery's MCP server and AI skills turn vague production incidents into evidence-backed diagnoses while keeping engineers in control. Guillaume is a Staff Solutions Architect at Qovery. He helps customers troubleshoot production infrastructure and writes about Kubernetes operations, AI agents, and reliable cloud platforms.

AI agents are becoming a new persona in the org chart. Learn how Qovery enforces data control, limited access, and auditability at the network level. Romain is a staff engineer at Qovery working on the control plane and AI integrations. He writes about distributed systems, incident response, and MCP-based tooling.

Generative AI has quickly emerged as a distinct over-the-top (OTT) traffic category, yet service providers have lacked the visibility to track it. Kentik now identifies traffic from 35+ AI services across 28 providers, showing operators how it enters their networks, where it’s growing, and what it costs to deliver.

A developer on your team just told Claude Code to connect to a new MCP server, the protocol coding agents use to reach organizational tools and data. Nobody in security reviewed it. Nobody in security even knows it happened. For two-thirds of enterprises, the primary obstacle to scaling agentic development isn’t budget or headcount — it’s security risk.

Manual asset entry is the hidden drain on your data center’s productivity. That one missed update causes hours of chasing spreadsheets, hunting down equipment details, and doubting if your inventory matches reality. Hyperview’s agentless asset auto-discovery flips the script, delivering real-time asset data across IT, OT, and virtual environments without the manual hassle. Keep your records current effortlessly and focus on running your data center with confidence.

For 15 years, UptimeRobot has answered one question for millions of people: is my site up? Today we’re taking on a related question that’s become just as important: is everything my site depends on up? We’ve acquired IsDown, which tracks the status of more than 6,000 cloud and SaaS providers in one place. Here are the details on what it is, why we bought it, and what we’re building with it.