200+ over-provisioned clusters with no time to fix them
A B2B SaaS company serving enterprise customers across 12 regions had grown to 200+ Kubernetes clusters over four years of rapid scaling. Each cluster was provisioned conservatively - engineers added buffer "just in case" - and nobody ever had time to go back and rightsize them.
The result was systematic over-provisioning. Average cluster utilization sat below 35%, but the engineering team was reluctant to change resource allocations in production without robust data and rollback mechanisms. Manual rightsizing meant a dedicated engineer spending 3 full days per month analyzing metrics, writing proposals, getting approvals, and carefully executing changes one cluster at a time.
At their growth rate, the problem was only going to get worse. They needed Kubernetes cost governance that could scale with their infrastructure - without adding headcount or introducing risk.
Continuous AI-driven rightsizing with safety guardrails
Nudgebee's AI-K8s Ops Assistant connected to all 200+ clusters through their existing Prometheus and Datadog observability stack. Within 48 hours, it had built baseline utilization profiles for every namespace, deployment, and node pool - identifying rightsizing opportunities with statistical confidence intervals to prevent under-provisioning.
For non-production clusters, Nudgebee executed rightsizing autonomously on a weekly schedule. For production clusters, it surfaced recommendations through the one-click approval workflow - giving engineers full control without requiring them to do the analysis themselves.
$1.2M saved. 3 days down to 15 minutes.
The B2B SaaS company now continuously optimizes all 200+ clusters without dedicating engineering time to it. The $1.2M in annual savings was reinvested into product engineering. The engineer who used to spend 3 days per month on cluster management now spends 15 minutes reviewing Nudgebee's weekly summary and approving the handful of production changes that required human sign-off.