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Kubernetes Cost Optimization at Enterprise Scale.

You are paying for the cluster you requested, not the one you use, and the gap is enormous. This whitepaper shows where the waste lives and the proven levers that recover 30 to 45% of cluster spend, permanently.

In depth

You Are Billed for Requests, Not Usage, and the Gap Is the Bill.

01

Developers set requests high to avoid throttling, the cluster runs at roughly 13% CPU utilization, and 83% of container spend goes to idle resources nobody owns.

02

A system that keeps utilization high by default, through rightsizing, autoscaling, bin-packing, spot, and quotas, recovers the waste and stops it from creeping back.

The detail

The Three Disciplines Every Platform Team Needs.

Zone · 01

Right-size workloads to real usage

Most oversized-request waste, the 29% bucket, comes from pods asking for far more CPU and memory than they touch.

Zone · 02

Size the infrastructure to the workloads

Overprovisioned infrastructure is the larger 54% bucket: too many nodes, or nodes too large, for what runs on them.

Zone · 03

Make cost visible and owned

Lack of ownership is cited by 45% of practitioners as a top cost driver.

By the numbers

The figures that make it a board-level conversation.

83%
Of container costs go to idle resources, 54% overprovisioned infrastructure and 29% oversized requests (Datadog State of Cloud Costs)
13%
Of provisioned CPU is actually used in production clusters, with 99% of clusters overprovisioned (CAST AI 2025)
30-45%
Typical Kubernetes overspend the CNCF found across 65%+ of organizations
Inside the report

What you'll take away.

01

L0 Blind - Pay the bill, do not ask

Requests are set by guesswork, there is no per-team visibility, and utilization sits in the low teens.

02

L1 Visible - Cost allocated to owners

Deploy OpenCost or Kubecost so spend is attributed per namespace and team.

03

L2 Rightsized - Requests match usage

Rightsizing and the Vertical Pod Autoscaler bring requests down to observed usage, while the Horizontal Pod Autoscaler scales pod count to demand.

04

L3 Autonomous - Efficient by default

Node autoscaling, bin-packing, spot capacity, and namespace quotas keep utilization high automatically.

Questions

Frequently asked.

How much can we realistically save?
Why is utilization so low?
HPA or VPA?
What is the prerequisite for all of this?
Will the savings last?
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Next step

Stop Paying for the 87% You Do Not Use.

Talk through how this applies to your roadmap with our engineering leads - a working session, not a sales pitch.

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