Kubernetes Cloud Costs: EKS vs AKS vs GKE Pricing Guide

The Kubernetes Cost Model

Managed Kubernetes costs are composed of several distinct layers: the control plane fee (charged by the provider for managing the Kubernetes API server, etcd, and scheduler), the worker node compute (the underlying VM instances that run your containers), persistent storage (volumes for stateful workloads), networking (load balancers, ingress controllers, egress), and observability (logging, metrics, tracing for the cluster).

Unlike traditional VM deployments, Kubernetes clusters have overhead beyond the raw compute cost. Kubernetes system components (kube-proxy, CNI, kubelet, kube-dns, metrics-server) consume approximately 5–15% of node capacity, effectively a "tax" on your compute resources. On small node sizes (2 vCPU / 8 GB), this overhead is proportionally higher, which is why using larger node instance types improves cluster efficiency.

AWS EKS Pricing

AWS EKS charges a flat $0.10/hr per cluster ($73/month) for the managed control plane, regardless of cluster size or number of nodes. Worker nodes run as standard EC2 instances and are billed at EC2 rates — on-demand, reserved, or spot pricing applies.

EKS Fargate offers serverless nodes where you pay only for the vCPU and memory consumed by running pods ($0.04048/vCPU-hr and $0.004445/GB-hr). Fargate is cost-effective for workloads that are highly variable or short-lived, but typically more expensive than managed node groups for steady-state workloads due to higher per-resource rates.

EKS Auto Mode (launched 2024) automatically manages node provisioning and right-sizing using Karpenter under the hood, typically reducing node costs 15–30% compared to manually configured node groups through better bin-packing efficiency.

Azure AKS Pricing

Azure AKS has a free control plane tier — no charge for the managed Kubernetes API server. This is a significant cost advantage over EKS and GKE for organizations running multiple clusters, as each additional cluster on AWS or GCP incurs $73/month in control plane fees.

However, Azure offers an optional Uptime SLA tier at $0.10/cluster/hr ($73/month) that provides a 99.95% API server uptime SLA (vs 99.9% on the free tier). For production clusters where Kubernetes API availability is critical, this is typically worth the cost. Virtual Machine Scale Sets (VMSS) are used for AKS node groups, priced at standard Azure VM rates.

Google GKE Pricing

GKE Standard mode charges $0.10/hr per cluster ($73/month) for the management fee. GKE Autopilot is a fully managed mode where Google handles node provisioning — pricing is per pod resource request ($0.0445/vCPU-hr, $0.004934/GB-hr) with a minimum of 0.25 vCPU and 0.5 GB per pod.

GKE benefits from GCP's Sustained Use Discounts on Standard mode nodes — nodes running 25%+ of a month receive automatic discounts without any commitment. Full-month nodes receive approximately 20–30% automatic discounts on top of list pricing, which partially or fully compensates for the control plane fee relative to AKS.

Worker Node Optimization

Selecting the right node instance type is the most impactful decision for Kubernetes cost optimization. Larger instances reduce per-unit overhead (DaemonSets and system pods consume a fixed amount regardless of node size) and improve bin-packing efficiency.

A common recommendation is to use m5.2xlarge or equivalent (8 vCPU / 32 GB) as your baseline node size for general workloads, rather than smaller instances. The overhead consumed by Kubernetes system components on an 8-vCPU node is proportionally lower than on a 2-vCPU node, giving your application workloads a larger fraction of the total capacity purchased.

Spot Node Groups for Cost Reduction

Running Kubernetes worker nodes on Spot/Preemptible instances can reduce compute costs by 60–80%. The key to making this work reliably is multi-AZ, multi-instance-type diversification. By using Karpenter (EKS) or node affinity rules to spread pods across multiple Spot pools, the probability of simultaneous interruption of all nodes is extremely low.

A recommended architecture: run critical system workloads (monitoring, logging, ingress controllers) on a small on-demand or reserved node group, while scheduling application workloads on a large Spot node group with 10+ instance type options across 3 AZs. Stateful workloads requiring persistent volumes should generally run on on-demand nodes to prevent volume attachment failures during interruptions.

Storage for Kubernetes Workloads

Persistent Volumes (PVs) in Kubernetes are provisioned as cloud block storage (EBS, Azure Managed Disks, GCE Persistent Disks). Key cost considerations: EBS gp3 volumes are the default StorageClass on EKS and offer 3,000 IOPS free at any size — more cost-effective than gp2 for most workloads. Volumes are provisioned at their declared size and billed accordingly, even if utilization is low. Kubernetes does not automatically resize volumes — right-size your PVC declarations.

Kubernetes Observability Costs

Production Kubernetes clusters generate substantial volumes of logs, metrics, and traces. CloudWatch Container Insights (EKS), Azure Monitor for Containers (AKS), and GKE Operations (GKE) provide managed observability, but at cost:

• CloudWatch Logs: $0.50/GB ingested + $0.03/GB/month stored. A cluster generating 10GB logs/day at 30-day retention = $153/month in logging costs alone.
• Azure Monitor: $2.30/GB ingested for Log Analytics. Lower volume but higher per-GB cost.
• GKE Operations: Free for GKE system metrics; application custom metrics at $0.18/million metrics/month.

Consider using open-source alternatives (Prometheus + Grafana + Loki) deployed within the cluster to reduce managed observability costs by 50–80% for clusters generating high log volumes.