Operations | Monitoring | ITSM | DevOps | Cloud

At 2:37am on a cold Oregon night, a fire alarm blared at a rural station. Seconds later, the call came in: a structure fire on the outskirts of Rogue Valley. But what if that alarm never reached the station? This isn't a hypothetical. For the IT team at Emergency Communications of Southern Oregon (ECSO 911), it’s the kind of emergency scenario they prepare for every day.

Data centers have become the beating heart of digital business. Everything from financial transactions to cloud-based collaboration tools depends on the seamless movement of information between these high-powered facilities. As demand for bandwidth grows and companies stretch their networks across cities, states, and continents, the ability to connect data centers securely and efficiently has taken on new urgency. But linking data centers isn’t as simple as laying fiber between buildings.

If you’re running AI, ML, or data-intensive workloads on GPUs, monitoring their performance is critical. Overheating, under-utilization, or memory bottlenecks can cost you thousands in cloud bills and potential downtime. This guide walks you through collecting real-time GPU telemetry using nvidia-smi, sending it to Cribl Edge, routing it through Cribl Stream, and using Cribl Search to analyze the data—step by step.