Operations | Monitoring | ITSM | DevOps | Cloud

True data sovereignty isn't about managing your own cloud accounts; it’s about where your data resides and how it is governed. By utilizing a unified configuration file to deploy on sovereign infrastructure like OVHcloud, Upsun provides standardized sovereignty without the complexity of “Bring Your Own Cloud”.

Claude Code costs $20–$200+/month depending on plan and usage. Compare Pro vs. Max vs. API pricing, see real-world cost estimates, and learn how to track AI spend at scale.

An honest coverage of the best AI governance tools for 2026 including CloudZero, Credo AI, OneTrust, Grip, IBM and more.

‍ When you're architecting an enterprise Java application, one decision quietly shapes everything downstream: runtime footprint, deployment pipelines, and how your platform team handles incidents at 3 a.m. For two decades, that decision was framed as Java SE vs Java EE. In 2026, that framing has quietly inverted.

Engineers have been shipping pieces of "the graph" for years. Service maps. Dependency graphs. Knowledge graphs. RDF triples. The newest entrant is the context graph, and the reason it shows up now is specific: software is increasingly executed by agents, and agents need a model of how work actually happens, not just an index of what exists.

Every so often, NVIDIA releases something that quietly changes the direction of the industry. CUDA did it. DGX did it. NVLink did it. Vera Rubin feels like one of those moments again. At first glance, Rubin looks like the natural successor to Blackwell. Faster GPUs, larger memory pools, and eye watering performance numbers. But the more you dig into the architecture, the clearer it becomes that NVIDIA is not simply shipping another accelerator generation.

Customers regularly come to us looking to solve their observability problem by connecting the dots from frontend to backend. It sounds straightforward in theory, but in practice it's one of the hardest problems in modern application monitoring. The frontend monitoring tools they already have in place tend to be proprietary or narrowly scoped to frontend needs, leaving them without the context-rich backend data that makes real triage possible.

Internal visibility isn’t enough for modern incident response. Your app team has three dashboards open and everything looks fine. CPU is healthy, memory is stable, the application servers are responding normally. But users are still complaining. The checkout page is slow. Logins are timing out. Support tickets are piling up. And your monitoring tools have nothing useful to say about why.

Today we’re launching Lightrun AI Skills, structured, repeatable investigation workflows built for AI coding agents. With Lightrun MCP, agents like Claude Code, Codex, and Cursor can already instrument live production services and reason over live runtime evidence without a redeployment. But AI agents remain non-deterministic by design, using the same tool differently every session.