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How Much Are You Wasting on Unused Kubernetes Resources?

Enter your cluster details and get an instant estimate of your annual orphaned resource waste — based on industry research.

Your Cluster Details

5
150
20
1200

Typical range: $50–$500/node/month

55% utilized = 45% headroom
20%90%

Spend Summary

Total monthly K8s compute spend$15,000
Orphaned waste (25% industry avg)$3,750/mo
Annual waste$45,000/yr

Estimated Annual Waste

You could be saving this every year

$45,000
Savings range: $36,000$63,000 per year (20–35% of spend)

Based on industry research: 20–35% of Kubernetes resources are unused (Datadog State of Containers)

Estimate based on industry averages. Actual savings depend on cluster configuration.

What the Data Says

25%
Avg orphaned resources
Industry benchmark across Kubernetes environments
35%
Teams never audit clusters
Of teams have never performed a resource audit
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To first scan with KorPro
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Frequently Asked Questions

About Kubernetes waste estimation

How accurate is this estimate?

The estimate is based on Datadog State of Containers and CNCF industry research showing 20–35% of Kubernetes resources are typically unused. Real savings depend on your specific cluster state, workload patterns, and how aggressively you've optimized before. KorPro gives you exact numbers by scanning your actual cluster data in 5 minutes.

What counts as an orphaned resource?

Orphaned resources are ConfigMaps, Secrets, PersistentVolumeClaims, Services, Deployments, StatefulSets, Roles, RoleBindings, and more that exist in your cluster but aren't referenced or used by any active workload. These accumulate over time as teams deploy, update, and decommission services without cleaning up associated resources.

How does KorPro calculate actual savings?

KorPro's Inspector scans your real cluster data using read-only access and maps actual resource costs based on your cloud provider's pricing (AWS, GCP, or Azure). Unlike this estimate which uses industry averages, KorPro shows you exactly which resources are unused, what they cost, and how confident the analysis is — before you delete anything.

Stop Estimating. Start Saving.

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