Case Study: NielsenIQ cuts Kubernetes costs by 80% with CAST AI

NielsenIQ cuts Kubernetes costs by 80% with Cast AI automation

NielsenIQ, a global leader in data analytics and audience insights, was scaling its Kubernetes footprint across Azure but lacked enough process control around node provisioning and cluster management. As cloud costs grew, the team looked for a Kubernetes-focused solution and ultimately chose CAST AI after considering options like Karpenter and Kubecost.

With CAST AI’s automated node provisioning and workload optimization, NielsenIQ standardized cluster setup, increased use of spot VMs, and reduced the time engineers spent on manual capacity decisions. CAST AI delivered 60–80% savings on non-production deployments and 40–50% on production clusters, with ROI achieved in about two months.

NielsenIQ

James O’Hare

Principal Platform Engineer