What counts as an abandoned workload?

One whose CPU stays at or below 2% of its request over 14 days. Its whole cost counts as recoverable, and the proposal scales it down reversibly.

Will KubeOn delete our volumes?

No. For orphaned volumes it writes a snapshot-then-delete script that checks each volume is still available before touching it. Your team runs it.

Which environments get off-hours schedules?

Dev, test, QA and sandbox namespaces costing $200 or more a month, scaled down outside 07:00 to 20:00 on weekdays. Production is never scheduled.

Idle and waste cleanup

Find the workloads and volumes nobody uses

Abandoned deployments, orphaned and released volumes, oversized disks and idle node capacity, each priced per month and checked before anything is deleted.

Book a demo Platform overview

Savings

Data readyUpdated 12 min ago

Last 7 days▾

Savings

Filtered to Delete orphaned volumes. Billing is joined to PersistentVolumes and kubelet volume stats.

Savings available

$21,842.17/mo

$262,106.04 a year

Computed 12 min ago; refreshed every 30 minutes.

Up to $1,240.00/mo more in possible orphans, kept out of the total until someone checks them.

Where it comes from

Compute plan $20.1KStorage and unused workloads $1.79K

Right-size requests

$8,412.50

Consolidate nodes

$7,930.20

Abandoned workloads

$3,108.75

Delete orphaned volumes

$1,584.32

Pause outside working hours

$605.13

Reclaim released volumes

$201.27

Detailed recommendations

4 of 1,284

Resource	Scope	Issue	Current	Recommended	Savings
vol-0a8f3c21e4b7d9012111122223333 / us-east-1	111122223333 / us-east-1	Orphaned volume	500 GiB gp3, no PV	Snapshot, then delete	$612.40/mo
pvc-91be04d2prod-use1-a / catalog	prod-use1-a / catalog	Released volume	Released, Retain	Reclaim	$184.00/mo
data-postgres-0prod-euw1-a / search	prod-euw1-a / search	Over-provisioned volume	500 GiB, peak 118	180 GiB	$25.60/mo
fs-0c4e2b81444455556666 / us-east-2	444455556666 / us-east-2	Possible orphan	3 PVs, no pods	Check, then delete	$96.30/mo

What UnitVane brings to this job

Monthly savings, each with the rule that found it

Savings

Container requests are sized from p95 usage over 7 days, node groups from 14 days of peak requests. Orphaned volumes, abandoned workloads and off-hours schedules are priced per month and recomputed every 30 minutes.

Explore Savings

Savings

Data readyUpdated 12 min ago

Last 7 days▾

Savings

Opportunities derived from measured usage. Select a card to filter the recommendations.

Savings available

$21,842.17/mo

$262,106.04 a year

Computed 12 min ago; refreshed every 30 minutes.

Up to $1,240.00/mo more in possible orphans, kept out of the total until someone checks them.

Where it comes from

Compute plan $20.1KStorage and unused workloads $1.79K

Right-size requests

$8,412.50

Consolidate nodes

$7,930.20

Abandoned workloads

$3,108.75

Delete orphaned volumes

$1,584.32

Pause outside working hours

$605.13

Reclaim released volumes

$201.27

Detailed recommendations

1,284 total

Resource	Scope	Issue	Current	Recommended	Savings
generalprod-use1-a	prod-use1-a	Consolidate nodes	12 × m7i.4xlarge	16 × m7i.2xlarge	$3,184.40/mo
memoryprod-euw1-a	prod-euw1-a	Consolidate nodes	8 × r7i.2xlarge	6 × m7i.2xlarge	$1,702.15/mo
catalogdev-use2	dev-use2	Pause outside working hours	24 × 7	Weekdays 07:00–20:00	$605.13/mo
search-indexerprod-euw1-a / search	prod-euw1-a / search	Right-size requests	8 GiB per pod	3.2 GiB per pod	$488.10/mo
checkout-apiprod-use1-a / checkout	prod-use1-a / checkout	Right-size requests	2 cores per pod	0.6 cores per pod	$412.80/mo

Reviewable changes, shipped the way you choose

Change proposals

Every saving worth $25 or more a month becomes a proposal with current and proposed state, evidence, a risk level and a ready-to-apply patch. Ship it as a pull request, or let KubeOn apply it where you granted write access.

Explore Change proposals

Proposals

Right-size checkout-api requests in prod-use1-a

ProposedLow riskRight-size requests · prod-use1-a / checkout

$412.80/month

CPU requests are 4× the p95 usage across 6 replicas. Lowering them to 600m frees about 8.4 vCPU on the general node pool.Summary generated from the measurements below

Now

CPU per pod: 2 cores
Memory per pod: 4 GiB
Replicas: 6

Proposed

CPU per pod: 0.6 cores
Memory per pod: 2.5 GiB
Replicas: 6

Evidence

CPU: p95 0.50 cores per pod over 7 days of hourly samples, 25% of the request.
Memory: p95 2.08 GiB per pod; the highest hourly sample was 2.31 GiB.

Change to apply Copy

# charts/checkout/values-prod.yaml
checkout-api:
  resources:
    requests:
      cpu: 600m        # was 2
      memory: 2560Mi   # was 4Gi

On approval, KubeOn opens a pull request on acme/platform-config. Your CD deploys it; production always waits for a person to merge.

RejectApprove

The problem

Why it is hard today

Abandoned workloads and orphaned volumes, found and priced

Things outlive their owners:
Workloads and volumes stay running long after the project that created them ended.
Deleting feels risky:
Nobody wants to remove a volume without proof it is unused.
Idle capacity is invisible:
Nodes that are mostly empty look like normal cost on the bill.

How UnitVane handles it

What you get

Abandoned workloads

CPU at or below 2% of request for 14 days.

Orphaned volumes

Still billing a day after their PV disappeared.

Released volumes

PVs left in Released or Available that still bill.

Oversized disks

PVCs far larger than their 14-day peak.

Idle node capacity

Infrastructure idle reported separately from workload idle.

Check before delete

Scripts that snapshot first and touch only available volumes.

Outcomes

What changes for your team

A cleanup list with proof

Each item shows how long it has been unused and what it costs.

A way back

Scale-to-zero and snapshot-first deletes are reversible.

Your first weeks

What you see, and when

From the first agent run to findings that need a full usage history.

01
Within the first hour
The cluster, its nodes, namespaces and workloads appear in Diagnostics. Allocated cost per namespace, team and label follows as soon as billing data is in.
02
Once billing data is in
180 days of history are read and allocated, plus 30 days of per-pod split cost history where AWS split cost allocation data exists. A brand-new AWS export can take up to a day to deliver its first file. The allocated history is kept; the raw billing rows leave the hub after 90 days.
03
Within 30 minutes of the first allocation
Savings are computed, starting with findings that need no usage history, such as released volumes that still bill. Change proposals follow at the next daily regeneration.
04
After 7 days of usage
Container requests are right-sized from p95 usage over 7 days of hourly samples.
05
After 14 days
Node group sizing and abandoned workloads, which each need 14 days of data, and over-provisioned volumes, which also need Prometheus volume usage.

UnitVane works with your technology

Every major cloud, any Kubernetes, and the tools and model providers your teams already use.

All integrations

AWS

Microsoft Azure

Google Cloud

Cloud

Kubernetes

Red Hat OpenShift

Rancher

Tanzu

k3s

Helm

Terraform

Argo CD

Flux

Prometheus

OpenTelemetry

Okta

Slack

Microsoft Teams

OpenAI

Anthropic

Mistral AI

Your questions answered

Keep reading

Expert guides and related solutions

Article

Finding orphaned volumes without deleting the wrong one

Disks outlive the pods and nodes that created them, and keep billing every month. How volumes get orphaned in Kubernetes, how to tell an orphan from a disk someone still needs, and how to delete safely.

Article

Where Kubernetes spend goes: what the public data says

Independent surveys and billing data agree: most of what you pay for in a Kubernetes cluster is capacity no workload uses. Where it goes, why Kubernetes makes it worse, and the order to fix it in.

Solution by use case

Showback and chargeback

A bill for every team, idle and shared included

Solution by use case

Kubernetes rightsizing

Requests and nodes sized from measured usage

Solution by use case

Budgets and anomalies

Forecasts and spikes, sent to the owner

All resources

Ready to see it on your own data?

A 30-minute walkthrough on your own billing data, for your clouds, your clusters and your model providers.

Book a demo Plan an evaluation

Find the workloads and volumes nobody uses

What UnitVane brings to this job

Savings

Change proposals

Automation

Commitments and savings

Why it is hard today

Things outlive their owners:

Deleting feels risky:

Idle capacity is invisible:

What you get

Abandoned workloads

Orphaned volumes

Released volumes

Oversized disks

Idle node capacity

Check before delete

What changes for your team

A cleanup list with proof

A way back

What you see, and when

Within the first hour

Once billing data is in

Within 30 minutes of the first allocation

After 7 days of usage

After 14 days

Your questions answered

Expert guides and related solutions

Ready to see it on your own data?