EKS pricing: what to include in a realistic cost estimate

The easiest way to underestimate EKS cost is to model only nodes. Nodes are usually the biggest line item, but a realistic budget includes a fixed per-cluster fee, storage and snapshots, load balancers, networking transfer, and observability volume. Use this page as a checklist and a template for a first-pass estimate.

1) Control plane (fixed fee per cluster)

  • Estimate monthly control plane cost as clusters × $/hour × 730.
  • It matters most for many small clusters (dev/test/stage sprawl), not for one large production cluster.

Guide: EKS control plane cost

2) Nodes (compute + attached storage)

Most clusters are node-hour driven. Start from requests-based sizing and a utilization target, then convert to node count and node-hours.

  • Node-hours: node count × hours/month (and separate always-on vs scheduled groups if applicable).
  • Packing efficiency: topology constraints, DaemonSets, and pod caps reduce real utilization.
  • Attached storage: EBS root volumes and any node-local storage are separate line items.
Node sizing guide Node cost calculator

3) Load balancers and ingress

Load balancers are often a hidden baseline cost because they’re always-on. The drivers are “how many” and “how much traffic/capacity”.

  • Count the always-on LBs (one-per-service patterns can multiply quickly).
  • Model capacity units for typical and peak traffic windows.

Tool: load balancer cost calculator

4) Observability (logs and metrics)

For many teams, observability becomes the “surprise bill” after the cluster is stable. If you don’t model it, your estimate is fragile.

  • Logs: ingestion GB/day × retention (plus any scan/search costs).
  • Metrics: time series count grows with cardinality (labels) and scrape frequency.
Log cost Kubernetes observability Reduce logging costs

5) Networking: NAT, cross-AZ, and internet egress

Kubernetes often increases east-west traffic (service-to-service calls). If traffic crosses AZs or routes through NAT, costs can show up fast.

  • NAT: processed GB for private workloads calling public endpoints or AWS services without endpoints.
  • Cross-AZ: service chatter and load balancer routing can create steady transfer.
  • Internet egress: APIs, downloads, and CDN origin traffic.

Tool: VPC data transfer calculator

6) Storage and snapshots (PVs and backups)

  • PVs: GB-month for block storage and the growth rate over time.
  • Snapshots: snapshot GB-month and retention policy.

Related: EBS snapshot cost

First-pass estimate template (inputs to collect)

  • Cluster count (by environment and region)
  • Average node count + instance $/hour (or blended on-demand/spot mix)
  • Always-on load balancer count and rough traffic/capacity assumptions
  • Log ingestion GB/day and retention (days)
  • NAT processed GB/month and cross-AZ transfer assumptions
  • PV storage GB-month and snapshot retention

If you’re missing a number, write down an assumption and validate it after deployment instead of pretending it’s zero.

Common pitfalls

  • Budgeting from peak nodes (overestimates) or from perfect packing (underestimates) without headroom.
  • Cluster sprawl in non-prod making fixed per-cluster fees and add-ons balloon.
  • One load balancer per service creating a large always-on baseline.
  • Ignoring log/metric growth (cardinality) until the bill arrives.
  • Accidental NAT and cross-AZ traffic from “it just works” routing.

How to validate after the first month

  • Group EKS costs by service and usage type: confirm your top 3 drivers match your model.
  • Check node-hours vs the planned node count; investigate fragmentation if it’s higher than expected.
  • Review load balancer count and utilization; consolidate where appropriate.
  • Measure log ingestion GB/day and retention; tune verbosity and sampling intentionally.
  • Check NAT processed GB and cross-AZ transfer; adjust routing and endpoints if needed.

Related calculators

EKS cost Requests & limits LB cost Log cost

Sources

Related guides

ECS cost model beyond compute: the checklist that prevents surprise bills
A practical ECS cost model checklist beyond compute: load balancers, logs/metrics, NAT/egress, cross-AZ transfer, storage, and image registry behavior. Use it to avoid underestimating total ECS cost.
ECS vs EKS cost: a practical checklist (compute, overhead, and add-ons)
Compare ECS vs EKS cost with a consistent checklist: compute model, platform overhead, scaling behavior, and the line items that often dominate (load balancers, logs, data transfer).
Kubernetes cost model beyond nodes: the checklist most teams miss
A practical Kubernetes cost model checklist: control plane, load balancers, storage, logs/metrics, and egress - plus links to calculators to estimate each part.
Fargate vs EKS cost: what usually decides the winner
A practical Fargate vs EKS cost comparison: normalize workload assumptions, compare task-hours vs node-hours, include EKS fixed overhead (cluster fee + add-ons), and account for the line items that dominate both (LBs, logs, transfer).
API Gateway vs ALB vs CloudFront cost: what to compare (requests, transfer, add-ons)
A practical cost comparison of API Gateway, Application Load Balancer (ALB), and CloudFront. Compare request pricing, data transfer, caching impact, WAF, logs, and the hidden line items that change the answer.
AWS cross-AZ data transfer cost: causes and estimate steps
A practical guide to AWS cross-AZ data transfer costs: common causes (load balancers, databases, Kubernetes), how to estimate GB crossing zones, and how to reduce it safely.

Related calculators

Data Egress Cost Calculator
Estimate monthly egress spend from GB transferred and $/GB pricing.
API Response Size Transfer Calculator
Estimate monthly transfer from request volume and average response size.
VPC Data Transfer Cost Calculator
Estimate data transfer spend from GB/month and $/GB assumptions.
Cross-region Transfer Cost Calculator
Estimate monthly cross-region transfer cost from GB transferred and $/GB pricing.
Kubernetes Cost Calculator
Estimate cluster cost by sizing nodes from requests and pricing them.
Kubernetes Node Cost Calculator
Estimate cluster monthly cost from node count and per-node hourly pricing.

FAQ

What is the biggest EKS cost driver?
Usually node compute (node-hours). But for many real clusters, logs/metrics, load balancers, NAT gateways, and cross-AZ traffic can be meaningful.
Why do EKS estimates miss?
They model only nodes. A realistic estimate includes the control plane fee, storage/snapshots, networking transfer, and observability volume.
How should I size nodes for budgeting?
Start from pod requests, subtract overhead, reserve headroom, then convert to a node count. Validate against a representative week of metrics once you have them.
What should I validate after deploying?
Node-hours, load balancer count, NAT processed GB, cross-AZ transfer, and log ingestion GB/day are common surprises to check early.
Last updated: 2026-01-27