Real-time
Refreshed every minute.
Run rate, MTD, daily, weekly, monthly — and an hourly resolution under 14 days. No batch jobs, no overnight delay.
$0/hr
current run rate
last hournow
Cost MonitoringLive · refreshed every minute
Seeeverydollar.Ateverylevel.
From a 5,000-pod fleet to a single container. Kubeadapt turns raw Kubernetes spend into a clean, drillable picture — CPU, RAM, GPU, storage, network, idle, and overhead, attributed honestly.
- 5-minute install
- Read-only RBAC
- Stays in your VPC
Seven levels · one mental model
Organization
All clusters
$48,210
mo · run rate
Cluster
prod-eu-1
$18,400
mo · 38% of org
Node Group
ng-general-large
$7,032
mo · 12 nodes
Node
ip-10-0-3-42
$586
mo · m5.4xlarge
Namespace
data-platform
$4,820
mo · 89 / 142 pods
Workload
analytics-worker
$2,140
mo · 12 replicas
Pod
78f9-3a1c
$180
mo · loaded total
Seven layers · one click each
From a five-thousand pod fleet to onerunningcontainer.
Click a tier. Each one is a fully-featured page with its own KPIs, trends, utilization charts, and breakdowns — not a static table behind a tooltip.
Now viewing · Organization
See the whole bill, all at once.
Run rate, MTD, savings opportunities, and resource efficiency across every cluster you operate. Rank clusters by spend, drill into the largest, find what changed since yesterday.
Org-wide KPIs
Run rate, MTD, identified savings, efficiency.
Cost by cluster
Ranked list with share, region, and pod count.
Spend by team
Labels and namespaces rolled up org-wide.
app.kubeadapt.io / dashboard
LIVEOrganization
Organization
All clusters · all teams · one bill.
Live · refreshed every minute5 clusters12 zones5,021 pods
Run Rate
$48,210
/mo · current pace
MTD
$23,640
15 days in
Identified Savings
$6,140
/mo · 13% of spend
Avg Efficiency
64%
cluster average
OverviewClustersWorkloadsRecommendationsBilling
Cost by Cluster
Ranked by /mo · 5 of 5
Last 30d
- prod-eu-1eu-west-11,840 pods↑ 4.1%$18,40038%
- prod-us-eastus-east-11,480 pods↓ 1.8%$14,82031%
- prod-us-westus-west-2820 pods↑ 4.1%$8,21017%
- stagingeu-west-1412 pods↓ 1.8%$4,1809%
- data-eu-1eu-central-1261 pods↓ 1.8%$2,6005%
Spend by Team
5 teams · period total
- data-eng38%
- platform22%
- ml-ops18%
- sre14%
- web8%
Cost Explorer · ad-hoc analysis
Or query it like adatawarehouse.
The drill-down covers the structured questions. Cost Explorer covers the rest. Pivot any of ten dimensions, chain filters across teams and labels, switch cost modes, save the view as a dashboard, export to CSV or PDF. No query language — just click.
10 group-by axes
Workload, Namespace, Controller Kind, Node, Pod, Container, Deployment, StatefulSet, DaemonSet, Instance Type — switch axis with one click.
Composable filters
Workload, node, and cluster axes — each with its own filter set. Pick label key=value, cluster, namespace, team, AZ, region, capacity type. Filters auto-prune when you change axis.
Two cost modes, one click
Fully Loaded for honest accounting (idle + overhead attributed). Workload Only for direct attribution. Toggle without re-running the query.
Save, share, export
Pin views as dashboards (private or shared with team). Export to CSV for finance, PDF for review. Daily, weekly, or monthly granularity.
app.kubeadapt.io / cost-explorer?tab=allocations&groupBy=workload&range=14d
LIVECost Explorer
14 days · grouped by workload · fully-loaded mode · 4 active filters
Cost Explorer
Interactive drill-down into Kubernetes cost by dimension, time, and tag.
Apr 1 – 14· 14dExport
Period Cost
$8,420
+12% vs prev98% coverage
Period Emissions
142.3 kg CO₂e
−4% vs prev
Scanned Resources
1,420
workloads · pods · containers
Cost over time
Apr 1 – Apr 14 · daily
by
Total$8,420
Avg/day$601
Peak dayApr 9 · $720
Series6 + Other
- CPU
- RAM
- GPU
Apr 1Apr 7Apr 14
Projected
Sort:Total Cost
| Workload | CPU Cost | RAM Cost | GPU Cost | Total | CO₂ | Eff |
|---|---|---|---|---|---|---|
analytics-workerdata-platform · prod-eu-1 | $420 | $190 | $840 | $1,540 | 92.4 kg | 71% |
batch-trainerdata-platform · prod-eu-1 | $180 | $92 | $1,120 | $1,394 | 125.5 kg | 84% |
feature-storedata-platform · prod-eu-1 | $220 | $320 | $0 | $546 | 32.8 kg | 64% |
ingest-pipelinedata-platform · prod-eu-1 | $310 | $180 | $0 | $498 | 42.7 kg | 58% |
cache-redisdata-platform · prod-eu-1 | $48 | $320 | $0 | $368 | 22.1 kg | 92% |
log-shipperdata-platform · prod-eu-1 | $78 | $24 | $0 | $102 | 8.4 kg | 38% |
Rows25·Showing 1–6 of 142·sorted by Total cost
Honest accounting · loaded cost
No hidden costs. Idleandoverhead,attributed.
Most tools show you the bill. We show you the truth. Every pod is charged its direct compute plus a fair share of the idle capacity it required and the cluster overhead it relied on. The number you see is the number to compare against revenue.
Workload bill
CPU, RAM, GPU consumed by the pod itself — the line item every cost tool shows.
Idle attribution
The pod’s allocated share of unused capacity on the node it landed on. Honest pro-rata.
Overhead share
Cluster system services, control plane, observability — spread across tenants.
Loaded total
The real number to compare against revenue, capacity, and unit economics.
Pod · analytics-worker-78f9-3a1c
How $49.60/mo is built up
Loaded total
$0.00
Cost buildup · stacked
$49.60 / mo
CPU
4.2 vCPU · us-east-1
$14.00
28.2%
RAM
24 GB
$7.00
14.1%
GPU
0.5 × A10G
$24.00
48.4%
Idle
Allocated share
$3.40
6.9%
Overhead
System / control plane
$1.20
2.4%
Why it matters
A pod that “costs $45” on paper actually costs $49.60 once you account for the idle node capacity it forces the autoscaler to keep, plus its share of cluster overhead. We compute that for you, on every pod, every minute.
Always live · always honest
Real-time, multi-dimensional, everyanglecovered.
Cost is not a number. It’s a shape across time, resource, behavior, and pricing model. We show you all of it — without a query language.
- Live
Multi-resource
CPU, RAM, GPU, storage, network.
Every cost component broken out per cluster, per namespace, per workload. No more “compute” lump sum.
Component split
5 dimensions
$48,210 / mo
- CPU38%
- Memory24%
- GPU22%
- Storage10%
- Network6%
Behavioral
Hour-of-day patterns.
See exactly when each workload peaks. Right-size your HPA bounds. Schedule batch into the cheap hours.
Last 7d avgHour-of-day pattern
14:00–17:00
peak window
0006121823Spot-aware
Spot savings, surfaced.
Coverage % at every level — cluster, node-group, namespace, workload. Find the gaps you can still close.
Spot coverage
0%
of compute hours
Saved
$0
/ mo
Spot72%On-demand28%
Live agent · install in 5 minutes
Stop paying for unused capacity.
Connect your first cluster in 5 minutes. The first 100 vCPU is on us, forever. Above it, the rate tiers from $1.99 down to $0.60 — same features, every plan.
Self-hosted agentFirst 100 vCPU freeNo credit card