Kubernetes costs explained: nodes, egress, load balancers, and observability

Kubernetes bills are rarely just nodes. A planning-safe estimate includes: node baseline + network (egress/NAT) + load balancers + logs/metrics. This hub links the key guides and calculators to avoid thin compute-only models.

1) Nodes (the baseline)

Translate app demand into node-hours (CPU + memory), then apply headroom and allocatable percent.
Validate requests/limits and packing assumptions (waste is the common leak).
Tools: node cost, requests vs limits

2) Egress, NAT, and cross-AZ traffic (the surprise bucket)

Model internet egress and cross-zone/region transfer separately.
NAT/egress costs spike during deployments, image pulls, and incident retries.
Tools: egress, transfer

3) Load balancers and ingress

Include hourly baseline plus request/GB processed drivers where applicable.
Multi-AZ load balancer patterns can create persistent cross-zone traffic.
Tool: load balancer cost

4) Logs and metrics

Log GB/day x retention is often larger than teams expect.
Metrics cost is a cardinality problem: series count can explode with labels.
Tools: log costs, metrics series

More Kubernetes guides

Aurora Serverless v2 pricing: how to estimate ACUs and avoid surprise bills

A practical way to estimate Aurora Serverless v2 costs: ACU-hours, storage GB-month, backups/retention, and how to model peaks so your estimate survives real traffic.

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.

Azure Kubernetes Service (AKS) pricing: what to include

AKS cost is more than node VMs: include node pools, networking/egress, storage, and observability. Use this checklist-style model to estimate safely.

Azure Load Balancer pricing: L4 traffic and data processing model

A practical cost model for Azure Load Balancer: hours, data processed, and egress boundaries. Includes a workflow to estimate GB processed from RPS and payload size, plus a validation checklist for peaks and retries.

CloudFront cache hit rate: how it changes origin egress cost

Cache hit rate strongly influences origin requests and origin egress (cache fill). Learn a simple model, what breaks hit rate, and the practical levers to improve it safely.

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).

EKS control plane cost: how to model it and when it matters

A practical guide to modeling EKS control plane costs: fixed hourly fees, multi-cluster strategy, and how to keep dev/test clusters from inflating spend.

EKS node sizing: requests, overhead, and why packing is never perfect

A practical EKS node sizing guide: size from requests, reserve headroom, account for DaemonSets and max-pods limits, and understand why real scheduling often needs more nodes than the math minimum.

EKS pricing: what to include in a realistic cost estimate

A practical EKS pricing checklist: nodes, control plane, load balancers, storage, logs/metrics, and data transfer — with calculators to estimate each part.

EKS vs GKE vs AKS cost: a practical comparison checklist (beyond node price)

Compare managed Kubernetes costs across EKS, GKE, and AKS by modeling the same line items: nodes, control plane, load balancers, storage, observability, and egress. Includes a worksheet template and validation steps for baseline vs peak.

Estimate Secrets Manager API calls per month (GetSecretValue volume)

A practical workflow to estimate Secrets Manager API request volume (especially GetSecretValue): measure and scale when possible, model from runtime churn when not, and validate with CloudTrail so your budget survives peaks.

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).

Google Kubernetes Engine (GKE) pricing: nodes, networking, storage, and observability

GKE cost is not just nodes: include node pools, autoscaling, requests/limits (bin packing), load balancing/egress, storage, and logs/metrics. Includes a worked estimate template, pitfalls, and validation steps to keep clusters right-sized.

Kubernetes cost calculator (cluster pricing checklist)

A practical checklist for estimating Kubernetes costs: node compute, control plane, load balancers, storage, egress, and observability. Includes a fast workflow, calculator links, and common pitfalls.

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.

Kubernetes requests & limits: practical sizing (and cost impact)

How to size clusters from requests, choose allocatable headroom, and use limits to reason about burst risk - with a calculator, a worked template, and common pitfalls.

Kubernetes requests vs limits: why requests drive node count (and cost)

A practical explanation of Kubernetes requests vs limits for capacity planning and cost estimation, with common mistakes, a worked sizing workflow, and links to calculators.

Load balancer costs: what to include beyond node spend

A practical guide to load balancer costs: fixed hourly charges, usage-based capacity units (LCU/NLCU), and the architecture patterns that quietly increase spend in Kubernetes and web stacks.

A practical Kubernetes cost model checklist: control plane, load balancers, storage, logs/metrics, and egress - plus links to calculators to estimate each part.

Google Kubernetes Engine (GKE) pricing: nodes, networking, storage, and observability

EKS pricing: what to include in a realistic cost estimate

A practical EKS pricing checklist: nodes, control plane, load balancers, storage, logs/metrics, and data transfer — with calculators to estimate each part.

Kubernetes cost calculator (cluster pricing checklist)

EKS vs GKE vs AKS cost: a practical comparison checklist (beyond node price)

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.

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 usually drives Kubernetes cost?

Nodes (CPU/memory) are the anchor, but the surprises are usually egress/NAT, load balancers, and observability (logs + metrics). For managed Kubernetes, control plane and add-ons can matter in small clusters or many clusters.

How do I estimate quickly?

Start with node-hours from requests/limits and utilization, then add a network scenario (egress + NAT), a load balancer baseline, and an observability budget (log GB/day + metrics series).

What breaks estimates?

Over-allocating requests/limits, forgetting cross-AZ traffic patterns, ignoring NAT/egress, and letting metrics label cardinality explode.

Last updated: 2026-01-22