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-K8sOps Persona Bee 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.