Should we start with showback or chargeback?

Start with showback. Move to chargeback once team totals reconcile to the invoice and the unowned remainder is small enough to explain.

What happens to workloads without a team label?

Label selector and namespace mappings fill the gaps, then a cluster default. Anything still unowned is reported as unallocated with its resource IDs, never hidden in idle.

Showback and chargeback

A bill for every team, shared and idle included

Q: Who pays for idle and platform namespaces?

You decide with a policy: the platform team absorbs it, it is spread in proportion to each team's direct cost, or a hybrid of both. The policy is effective-dated like every mapping.

Allocate shared clusters to teams and cost centers from your labels, decide who pays for idle and platform namespaces, and send each owner a monthly statement that adds up to the invoice.

Book a demo Platform overview

Allocations

Data readyUpdated 12 min ago

Last 7 days▾

Allocations

Kubernetes cost by team · September 2026

Group byTeamFilter

ComputeSharedIdle

Idle and shared cost spread within each cluster

Team	Cost center	Direct	Shared	Idle	Cost
ML	CC-3301	$42,705.30	$4,130.25	$8,125.30	$54,960.85+11.6%
Payments	CC-1042	$41,890.40	$4,702.15	$2,618.10	$49,210.65+4.1%
Search	CC-2245	$39,604.85	$3,940.10	$2,835.35	$46,380.30+0.8%
Data	CC-2210	$27,410.60	$2,605.40	$3,104.40	$33,120.40-3.2%
Web	CC-1088	$26,330.15	$2,520.85	$2,356.70	$31,207.70-1.9%
No teamunlabeled or unmatched		$2,600.10			$2,600.10
Total					$217,480.00

Reconciled to invoice: 100.00%Ownership coverage: 98.8%Owners from team labels and namespace mappings

What UnitVane brings to this job

A business owner for every line of every bill

Business mappings

Ordered rules on any FOCUS field or tag set business unit, cost center, team, application and environment. Shared costs are split by policy, Kubernetes by namespace, and every month is reconciled to the invoice.

Explore Business mappings

Business mappings

Rules assign business units, cost centers, teams, applications and environments to every line. Shared costs are split by policy, Kubernetes by namespace.

Direct, September

66.7%

Kubernetes, September

22.1%

Shared, September

9.8%

Unallocated, September

1.4%

RulesShared costsHierarchyReconciliation

Sets business unit

2 rules, applied in priority order

#5

Commerce accounts

Account is one of 111122223333, payments-prod Digital Commerce

#10

Data and AI subscriptions

Subscription name contains “data” or “ml” Data and AI

Sets team

2 rules, applied in priority order

#1

Namespaces: payments

Kubernetes namespace is one of “payments, checkout” Payments

#20

Team tag

Every line value of tag “team”

Every pod, namespace and team, priced from the invoice

Cost allocation

Node cost is split across pods on max(request, usage) and reconciled to the billed cost of each cluster. Group by up to 5 dimensions plus any label, and drill from cluster to pod.

Explore Cost allocation

Allocations

Data readyUpdated 12 min ago

Last 7 days▾

Allocations

Kubernetes cost by namespace

Group byNamespaceFilter · prod

Kubernetes cost by namespace

prod clusters, 2026-10-03 to 2026-10-09

CPU
Memory
Volumes
Shared
Idle

Kubernetes cost by namespace

ComputeSharedIdle

SummaryBy resource

Namespace	Compute	Shared	Idle	Efficiency	Cost
searchprod-euw1-a	$5,070.55	$344.20	$512.30	66.2%	$5,927.05-2.4%
paymentsprod-use1-a	$3,660.42	$247.20	$302.40	58.3%	$4,423.86+4.2%
checkoutprod-use1-a	$2,790.47	$191.04	$253.10	41.6%	$3,704.37+9.8%
ml-inferenceprod-use1-a	$2,478.27	$168.96	$248.20	27.4%	$3,625.77+12.1%
data-pipelineprod-use1-a	$2,326.55	$138.60	$214.55	38.2%	$3,013.90+47.3%
catalogprod-euw1-a	$2,510.92	$170.10	$288.44	71.8%	$2,969.46-0.6%
Total, all prod namespaces				62.0%	$47,341.00

Showback reports that arrive on schedule

Reports

Save allocation, asset and cloud cost views with their grouping and filters. Deliver them daily, weekly or monthly by email or Slack, or pull the same data with CSV export and the REST API.

Explore Reports

Reports

Data readyUpdated 12 min ago

Last 7 days▾

Reports

Saved definitions you can run, share and schedule: grouped by any dimension or label, scoped by infrastructure or tags.

9 reports · 2 scheduled Filter reports

Report	Owner	Type	Grouped by	Window	Delivery	Last run
Monthly chargeback by teamEach team with its shared and idle cost, for finance	Default	Kubernetes allocation	team	Last month	Monthly · 2	10 d ago
Kubernetes cost by cost centreWeekly showback to cost-centre owners	Default	Kubernetes allocation	cost_center	30 days	Weekly · 1	3 d ago
Account spendEvery connected account, net of discounts	Built-in	Cloud bill	account	30 days	On demand	13 h ago
Idle costRequested and unrequested idle, by cluster	Built-in	Kubernetes allocation	cluster	30 days	On demand	never
Node spend by instance typeBilled node cost and capacity	Built-in	Infrastructure	instance type	30 days	On demand	never

AI spend with an owner, a budget and an alert

AI spend control

Attribute AI spend to product, team and tenant from tags and gateway keys, set budgets with alerts at an amount or a share of budget, and build drill-down reports across every cloud.

Explore AI spend control

Budgets

Data readyUpdated 12 min ago

Last 7 days▾

AI budgets and alerts

By product, team, tenant or deployment, at an amount or a share of budget

Scope	Budget	Spent	Status
Product: Customer supportSupport assistant	$60,000	30.4%	Forecast over
Team: SearchSearch	$45,000	24.5%	OK
Tenant: EU customersPlatform AI	$25,000	33.8%	Forecast over
Deployment: batch-extractDocument processing	15% of tenant	9%	OK

Alerts go to the owner by email, Microsoft Teams or Slack. Gateway keys can stop at 100%.

The problem

Why it is hard today

A bill for every team, idle and shared included

Shared nodes, shared bill:
Ten teams on one node group produce one line on the invoice.
Idle has to land somewhere:
Spread it silently and teams dispute the number. Leave it out and the totals do not reconcile.
Labels are inconsistent:
team, Team and TeamName all appear, and some workloads have none.

How UnitVane handles it

What you get

max(request, usage)

Teams pay for what they reserve or use, whichever is higher.

Idle and shared policies

Absorbed by the platform, proportional, or a hybrid.

Owner discovery

Teams and cost centers created from label values automatically.

Effective dating

Mappings change from a date you choose, and days before it keep their owners.

Monthly statements

Scheduled CSV and email per team or cost center.

Team-scoped access

Each team lead sees only their teams.

Outcomes

What changes for your team

Statements teams do not dispute

Each line shows direct, shared and idle cost and the rule behind it.

Totals that add up to the invoice

Unallocated spend is listed, never hidden in idle.

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

Chargeback that survives a reorganization

Chargeback works for a few months, then a reorganization silently rewrites every past month. How to give ownership a date, let labels do most of the work, and close each month on numbers that never move.

Article

Kubernetes cost allocation that reconciles to the bill

Allocations built from list prices drift away from the invoice, and finance stops trusting them. How to split node cost from billed, net amortized cost, charge pods fairly, and show what belongs to nobody.

Solution by use case

Kubernetes rightsizing

Requests and nodes sized from measured usage

Solution by use case

Idle and waste cleanup

Abandoned workloads and orphaned volumes, found and priced

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

A bill for every team, shared and idle included

What UnitVane brings to this job

Business mappings

Cost allocation

Reports

AI spend control

Why it is hard today

Shared nodes, shared bill:

Idle has to land somewhere:

Labels are inconsistent:

What you get

max(request, usage)

Idle and shared policies

Owner discovery

Effective dating

Monthly statements

Team-scoped access

What changes for your team

Statements teams do not dispute

Totals that add up to the invoice

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

Should we start with showback or chargeback?

Who pays for idle and platform namespaces?

What happens to workloads without a team label?

Expert guides and related solutions

Ready to see it on your own data?