Load balancers have long handled traffic distribution for traditional web applications — ensuring high availability, spreading load, and keeping services responsive. But AI inference workloads are changing the shape of traffic itself.

Inference-heavy systems generate highly concurrent, bursty, and latency-sensitive traffic. Requests are no longer tied to human interaction patterns — they’re driven by autonomous systems that are making real-time decisions. In this environment, understanding how traffic behaves at the load balancer layer becomes critical.

Introducing Akamai Cloud Pulse metrics for NodeBalancers

We are excited to announce that Akamai Cloud Pulse metrics for NodeBalancers are now in limited availability across all core regions.…