Kubernetes Resource Right-Sizing Automation
Kubernetes clusters waste 60-70% of provisioned resources because teams over-allocate CPU and memory out of fear of OOM kills. An automated right-sizing tool that recommends optimal resource requests based on actual usage patterns could save 40-60% on cluster costs.
Problem Statement
DevOps teams set Kubernetes resource requests conservatively (2x-5x actual usage) after experiencing OOM kills or CPU throttling. These requests are never revised downward because the risk of reducing them outweighs the cost savings nobody is tracking. As pod count grows, wasted resources compound. A 100-pod cluster wastes $50K+ annually on unused capacity.
The Idea
A Kubernetes resource optimization platform that analyzes actual pod resource consumption, recommends right-sized requests and limits, and automatically applies changes with safety guardrails to eliminate over-provisioning waste.
Why Now
Average Kubernetes cluster utilization is 30% (Datadog 2026 Container Report). Teams set resource requests high after one OOM kill and never revisit. Cloud bills grow linearly with pod count while utilization remains flat. Manual right-sizing requires per-pod analysis that nobody prioritizes. Automated optimization with safety checks fills this operational gap.
Target User
Platform engineers and FinOps teams managing Kubernetes clusters spending $10K+/month wanting cost optimization without stability risk
Target Market
Companies running Kubernetes clusters ($10K-500K/month cloud spend) where resource over-provisioning represents significant cost waste
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