AI makes networking matter again

"For years, one of the cloud's biggest gifts was that vendors like AWS could take care of the "undifferentiated heavy lifting" of managing infrastructure for you. Need compute? Click a button. Need storage? Click another. Need a database? Let someone else worry about the details. The whole point of managed infrastructure was to save most enterprises from spending their days swimming in low-level systems engineering."

"AI is making that abstraction leak. As I've argued, the real enterprise AI challenge is no longer training. It's inference: applying models continuously to governed enterprise data, under real-world latency, security, and cost constraints. That shift matters because once inference becomes the steady-state workload of the enterprise, infrastructure that once seemed necessary but dull suddenly becomes strategic."

"For decades, networking was prized precisely because it was stable and uneventful. That was the point: No one wants exciting networking. Standards bodies moved slowly and kernel releases moved carefully because predictability was paramount. That conservatism made sense in a world where most enterprise workloads were relatively forgiving and the network's job was mostly to stay out of the way."

Cloud computing abstracted away infrastructure management, allowing developers to focus on applications rather than systems engineering. However, AI is changing this dynamic. The enterprise AI challenge has shifted from model training to continuous inference on governed data with real-world constraints around latency, security, and costs. This steady-state inference workload transforms previously routine infrastructure into strategic business concerns. Networking, historically stable and unexciting, is becoming strategically important again. Networking gained prominence during previous technology upheavals like the dot-com boom, broadband expansion, and cloud consolidation. AI represents another significant shift requiring renewed attention to network infrastructure and performance.

Read at InfoWorld