Operations | Monitoring | ITSM | DevOps | Cloud

Upsun Dispatch is generally available to the public as of today. Our previous article explains what it is and why we built it. This round, we take you into the details of how it works, the primitives it consists of, and the functionality available right away. You'll also get a glimpse of our roadmap at the end of the article.

Table of Contents GPU sharing with NVIDIA hardware is becoming easier to adopt in Kubernetes but it hasn’t been easier to observe. Time-slicing lets multiple workloads share the same GPU. MPS allows CUDA workloads to execute concurrently. Schedulers like KAI make it easier to manage these shared environments. But sharing a GPU introduces a problem that is easy to underestimate.

Wondering what the big deal is with Black Friday? And why does every business on earth seem to be obsessed with the quasi-holiday? Or are you just looking for great deals? Black Friday has become a sort of global cultural institution. Everyone knows about it, some look forward to it, and a few go crazy for the big day. It may be hard to believe, but Black Friday hasn't always been a thing, and it's actually a relatively recent development.

Incident handling primer to help Google Cloud Platform customers design and practice reliability incident response and minimize business impact.

Most of what runs on a modern platform is built to stay up. Applications serve requests, workers process queues, and managed services keep databases and caches available around the clock. But a meaningful share of the real work does not fit that always-on shape.

For years, moving workloads to the cloud has been driven by scalability, flexibility and the desire to reduce the capital expenditure associated with running a data center. In 2026, however, there is another factor entering the conversation: the rising cost of buying and refreshing physical servers. The question is now whether rapidly increasing hardware prices are enough to push organizations that might previously have refreshed their on-premises infrastructure towards cloud alternatives.

Worldwide AI spending will reach $2.59 trillion in 2026, up 47% from 2025, according to Gartner. Yet only 37% of organizations report any earnings impact from AI, McKinsey finds. These AI statistics cover what companies spend, what AI costs to run, and the ROI they're actually getting. That gap between the two headline numbers is the story of AI in 2026.