The 3 Cloud Leaks Every Kubernetes Bill Hides
Your AWS invoice shows what you spent, never what you wasted. Here are the three Kubernetes cost leaks hiding in every EKS bill — and how to spot them.
Core 01 · Cluster Operations
Kubernetes cost intelligence — see every dollar, then cut it.
Most teams see one line item: "EKS — $82,400/mo." Atmosly breaks spend down to namespace, service, and team, finds the idle and oversized workloads, and turns real p95 usage into right-sizing the dev team can apply themselves. Across AWS, GCP, and Azure — not a spreadsheet.
- ✓ Namespace + service granularity
- ✓ Multi-cloud
- ✓ Apply right-sizing in a PR
$18,420 ↓ 31%
across all clusters · from $26,710 last month
AWS$13.3k
GCP$3.6k
Azure$1.5k
WorkloadTypeNowSave / mo
checkout-api
rightsizing
$1,240
↓ $610
analytics-spark
savings_plan
$2,980
↓ $890
ml-batch-pool
reserved_inst
$3,410
↓ $1,180
staging-* (idle)
idle
$740
↓ $740
How it works
See it, attribute it, cut it — without a FinOps team.
Cost Intelligence runs continuously on every connected cluster, powered by in-cluster cost telemetry. No tagging project, no quarterly spreadsheet — just signals your engineers can act on.
compute$88.2
EKS$65.0
data xfer$51.9
NAT gw$27.9
storage$24.0
01 — Attribute
Spend broken down to namespace, service & team
One bill becomes a map. See cost by account, by cluster, by namespace, and by service — instance type, load balancer, NAT gateway, data transfer, and storage, each on its own line. Then hand each team its own showback view.
- Per-account, per-cluster, per-namespace breakdown
- Compute, NAT, LB, data-transfer & storage line items
- Showback dashboards per team — no more shared mystery bill
Observed p95 (14d)
CPU 0.18 of 1.0 requested · Memory 412Mi of 1Gi requested.
APPLYRequest 1.0→0.35 CPU · 1Gi→512Mi
↓ $610 / moopens a PR
02 — Recommend
Right-sizing from real usage — not guesses
Atmosly reads each workload's p95 over time and proposes a concrete new request/limit, with the dollar impact attached. Reserved-instance and savings-plan opportunities surface the same way — ranked by monthly savings.
- Right-sizing, reserved instances & savings plans
- Every recommendation carries its savings_monthly
- Apply as a PR the owning team reviews — no central gatekeeper
budgetDaily spend exceeded $900 cap · #platform
forecastMonth-end estimate $19.1k · within budget
idle3 orphaned volumes flagged · $210/mo
03 — Stay ahead
Budgets, forecasts & idle detection that page you first
Set budgets and get notified the moment daily spend crosses the line. A monthly forecast tells you where you'll land. Idle workloads and orphaned volumes get flagged before they quietly bleed another month of spend.
- Daily-budget & monthly-estimate alerts
- Month-end cost forecast from current run-rate
- Idle-workload & orphaned-volume detection
What's inside
Everything finance and engineering both want
The numbers engineers trust because they come from the cluster — and finance trusts because they reconcile to the cloud bill.
Multi-cloud, one view
AWS, GCP, and Azure spend normalized into a single dashboard, with per-cloud and per-account totals reconciled to the bill.
Namespace & service granularity
Powered by in-cluster cost telemetry, so spend maps to the actual workloads — not just the cloud account.
Right-sizing from p95
Concrete request/limit changes from observed usage, each with its dollar impact, applied as a reviewable PR.
Commitment planning
Reserved-instance and savings-plan recommendations sized to your steady-state, ranked by monthly savings.
Showback by team
Give every team its own cost view so spend has an owner — without standing up a FinOps function.
Budgets & forecasts
Daily-budget and monthly-estimate alerts, plus a month-end forecast from your current run-rate.
The payoff
What teams find in the first month
−31%
average cluster spend after right-sizing*
5 min
to a full breakdown — no tagging project first
$0
FinOps headcount required to run it
3 clouds
AWS, GCP & Azure in one normalized view
*Representative of customer-reported outcomes. Your results depend on workload mix and current utilization.
Same control plane
Cost Intelligence is one of three cores
A deploy, an incident, a security finding, and a cost change are the same story — surfaced in one UI, with one audit trail.
Questions
What teams ask before connecting a cluster
How accurate are the numbers?
Spend is measured from in-cluster cost telemetry and reconciled to your actual cloud bill — per-account and per-cloud totals tie back to what AWS, GCP, and Azure invoice you. Engineers trust it because it maps to real workloads; finance trusts it because it reconciles.
Do I need to tag everything first?
No. Spend maps to namespaces and services automatically, so you get a full breakdown in about five minutes — no tagging project, no cost-allocation spreadsheet to maintain first.
Does it change my infrastructure?
No. Right-sizing and commitment recommendations apply as pull requests the owning team reviews. Nothing about your workloads or cloud account changes without an explicit, reversible approval.
Does it work across multiple clouds?
Yes. AWS, GCP, and Azure spend is normalized into one dashboard, with per-cloud and per-account totals — so a multi-cloud estate reads as a single, comparable view.
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What's hiding in your cluster spend?
Connect one cluster, read-only. The cost breakdown, idle workloads, and right-sizing recommendations show up on your dashboard in about five minutes. Free, no sales call.