EKS vs AKS vs GKE is really three comparisons in one: cost, networking, and day-2 operations. We have run production workloads on all three managed Kubernetes services — Amazon EKS, Azure AKS, and Google GKE — and they all pass conformance tests and run the same YAML. Yet the day-2 experience — the upgrades, the networking incidents, the 2am pages — is very different on each. This is the comparison we wish someone had written for us: no vendor marketing, just what matters when you are choosing where your clusters will live for the next five years.
TL;DR — GKE is the most polished and most automated: choose it if you are cloud-flexible and want the least toil. EKS is the least managed but sits inside the deepest cloud ecosystem: choose it if you are AWS-committed. AKS lands in the middle, with unbeatable Entra ID integration and a free control plane: choose it if you are a Microsoft enterprise. The Kubernetes API is the same everywhere. Everything around it is not.
EKS vs AKS vs GKE at a glance
| Question | Answer |
|---|---|
| Cheapest control plane | AKS — free standard tier (EKS ~$72/mo per cluster; GKE free tier, then similar fee) |
| Least operational toil | GKE — release channels, managed upgrades, Autopilot |
| Best node autoscaling | EKS — Karpenter (consolidation, per-pod instance selection, Spot) |
| Best for Microsoft enterprises | AKS — Entra ID, Azure RBAC on Kubernetes objects, Azure Policy |
| Deepest cloud ecosystem | EKS — IAM, RDS, SQS, MSK and the rest of AWS |
| Most Kubernetes-native experience | GKE — built-in Cilium dataplane, best-in-class networking defaults |
The short version
If you only read one paragraph, read this one. GKE is the most polished Kubernetes experience — Google created Kubernetes, and it shows in the upgrade automation, the networking, and Autopilot. EKS is the least managed of the three but sits inside the deepest cloud ecosystem, and if your organization is already all-in on AWS, that gravity usually wins. AKS lands in the middle: a genuinely good service that has improved enormously, with unbeatable Entra ID (Azure AD) integration for Microsoft-centric enterprises. The Kubernetes API is the same everywhere. Everything around it is not.
Control plane cost and what "managed" actually means
EKS bills you for the control plane — roughly $0.10 per hour per cluster, which works out to about $72 a month before you run a single pod. AKS's standard control plane is free; you pay only for nodes (there is a paid tier with an uptime SLA, worth it for production). GKE gives you a free-tier credit per billing account that covers one zonal or Autopilot cluster's management fee, then charges a similar per-cluster hourly rate beyond that. As of 2026 — always check current pricing — the pattern holds: EKS always charges, AKS never does by default, GKE charges past the free tier.
Here is the thing: control plane fees are noise. If $72 a month per cluster moves your decision, you have a cluster-sprawl problem, not a pricing problem. The real cost differences live in node efficiency, autoscaling behavior, and — above all — engineering hours spent on operations. A platform that saves your team two days a month on upgrade toil pays for a lot of control planes. On any of the three, the bill is dominated by how well you run the nodes — our Kubernetes cost optimization playbook covers the levers that matter.
Networking: where the real differences hide
Networking is where these services diverge the most, and where teams get hurt.
EKS: the VPC CNI and IP exhaustion
EKS uses the AWS VPC CNI by default. Every pod gets a real VPC IP address. This is great for observability and security-group integration — pods are first-class citizens on your network — but it means pod density is tied to instance ENI limits, and busy clusters can exhaust subnet IP space alarmingly fast. We have seen more than one team discover this in production. Mitigations exist (prefix delegation, custom networking, secondary CIDRs, or swapping in Cilium), but they are things you must know to do. Plan your CIDR ranges like they are load-bearing, because they are.
GKE: Dataplane V2 and native VPC routing
GKE's networking is the most complete out of the box. VPC-native clusters use alias IP ranges, and Dataplane V2 — GKE's built-in Cilium/eBPF dataplane — gives you network policy enforcement and policy logging without installing anything. Kubernetes NetworkPolicy just works, with logs. On the other two clouds, that sentence usually involves a Helm chart and a design review.
AKS: pick your CNI carefully
AKS offers several networking modes: the legacy kubenet path and Azure CNI in a few flavors, including an overlay mode that avoids the pod-IP-consumes-VNet-IP problem, plus a Cilium-powered dataplane option. The flexibility is real, but so is the decision fatigue — the mode you pick at cluster creation constrains you later, and the "right" answer has changed over the years. If you are creating an AKS cluster today, read the current CNI guidance before you commit; do not copy a two-year-old Terraform module.
Autoscaling and node management
All three support the standard Cluster Autoscaler. The interesting part is what each cloud built beyond it.
- EKS + Karpenter. Karpenter is the best thing AWS has done for Kubernetes. It provisions right-sized nodes directly from pending pods in seconds, bin-packs aggressively, consolidates underutilized nodes, and handles Spot interruption gracefully. If you run EKS without Karpenter in 2026, you are leaving real money on the table.
- GKE: node auto-provisioning and Autopilot. GKE Standard has node auto-provisioning that creates node pools to fit workloads. Autopilot goes further: no nodes to manage at all — you pay per pod resource request and Google owns the node lifecycle entirely. For teams that want the least infrastructure surface area, Autopilot is the strongest offering on any cloud.
- AKS: cluster autoscaler plus node autoprovisioning. AKS ships the cluster autoscaler and has added Karpenter-based node autoprovisioning. It works, and it is closing the gap, but it reached maturity later than the equivalents on AWS and GCP.
Upgrades: the day-2 tax
This is where we see teams underestimate the differences most.
GKE is the most automated. Release channels give you managed, staged rollouts of both control plane and nodes; maintenance windows and exclusions let you control timing; auto-upgrade of node pools is the default posture. Most GKE teams we work with barely think about version upgrades. That is the point.
EKS is the most manual. You upgrade the control plane, then each managed node group, then the cluster add-ons (VPC CNI, CoreDNS, kube-proxy) — each a separate step you own, roughly three times a year given the Kubernetes release cadence. Miss the window and you slide into extended support, which costs extra. Mature EKS shops automate all of this with Terraform and pipelines, but somebody has to build and maintain that automation. Budget for it honestly.
AKS sits in between: auto-upgrade channels, planned maintenance windows, and node-image upgrades exist and work well, but you will still make more upgrade decisions than on GKE.
Side-by-side
| Dimension | EKS | AKS | GKE |
|---|---|---|---|
| Control plane cost | Billed per cluster (~$0.10/hr) | Free (paid SLA tier optional) | Free tier per account, then per-cluster fee |
| Default networking | AWS VPC CNI; pods use VPC IPs, watch IP exhaustion | Azure CNI (incl. overlay) or kubenet; Cilium option | VPC-native; Dataplane V2 (Cilium/eBPF) built in |
| Autoscaling | Cluster Autoscaler; Karpenter (best-in-class) | Cluster Autoscaler; node autoprovisioning | Node auto-provisioning; Autopilot (fully managed nodes) |
| Upgrades | Most manual: control plane, node groups, add-ons separately | Auto-upgrade channels; moderate effort | Most automated: release channels, managed node upgrades |
| Day-2 toil | Highest — you own the glue | Moderate | Lowest |
| Standout strength | AWS ecosystem depth, IAM integration | Entra ID / Microsoft enterprise integration | Most Kubernetes-native; strongest managed experience |
Ecosystem and identity: the deciding factor nobody admits
In practice, most teams do not choose a Kubernetes service. They choose a cloud, and the Kubernetes service comes with it. That is not wrong — the integration surface matters more than the kubelet.
EKS's IAM Roles for Service Accounts (and the newer Pod Identity) make pod-to-AWS-service auth clean, and the surrounding ecosystem — RDS, SQS, MSK, everything — is the widest in the industry. AKS's integration with Entra ID, Azure RBAC on Kubernetes objects, and Azure Policy is genuinely the best identity story for a Microsoft enterprise; if your org lives in Entra groups, AKS access control feels native in a way the others cannot match. GKE's Workload Identity is elegant, and Google's operational tooling — logging, config sync, fleet management — reflects the fact that Google has run this exact software internally longer than anyone.
The Kubernetes conformance badge tells you your manifests will apply. It tells you nothing about who gets paged when a node pool fails to drain during an upgrade. Choose based on day 2, not day 1.
Which should you choose?
Our honest recommendations, having run all three:
- Choose EKS if you are AWS-committed. The ecosystem gravity is worth the extra operational work — but go in with eyes open: adopt Karpenter early, plan IP space carefully, and automate upgrades from day one, because AWS will not do it for you.
- Choose AKS if you are a Microsoft enterprise. Entra ID integration, Azure Policy, and the free control plane make it the pragmatic default when your identity, licensing, and compliance world is already Azure.
- Choose GKE if you want the least toil. If you are cloud-flexible and your goal is to spend engineering time on your product rather than on cluster plumbing, GKE — especially Autopilot — is the most managed, most Kubernetes-native option on the market.
And a caveat that applies to all three: a managed control plane does not mean a managed platform. Ingress, TLS, observability, secrets, cost controls, and deployment pipelines are still yours to design — budget for that gap no matter which logo is on the control plane.
There is no wrong answer among the three. There are only wrong expectations. Pick the platform that matches where your team already lives, staff the day-2 work it actually requires, and you will be fine on any of them.
Frequently asked questions
Which is cheapest — EKS, AKS or GKE?
AKS has the cheapest control plane: the standard tier is free, while EKS charges about $0.10/hour (~$72/month) per cluster and GKE charges a similar fee beyond one free zonal or Autopilot cluster per account. But control-plane fees are a rounding error — total cost is decided by node efficiency and engineering time. GKE often ends up cheapest to operate thanks to upgrade automation and Autopilot, and EKS can be cheapest on raw compute with Karpenter, Spot and Graviton.
Is EKS better than AKS?
Neither is universally better. EKS wins on ecosystem depth (IAM, RDS, SQS, the whole AWS surface) and has the best node autoscaling story via Karpenter, but it is the most manual of the three to upgrade and operate. AKS wins for Microsoft-centric enterprises — Entra ID integration, Azure RBAC on Kubernetes objects and a free control plane. If your organization is already committed to AWS, pick EKS; if it lives in Azure and Entra ID, pick AKS.
Is GKE better than EKS and AKS?
GKE is the most polished and most automated of the three — release-channel upgrades, built-in Cilium networking (Dataplane V2) and Autopilot, which removes node management entirely. Teams that are cloud-flexible and want minimum operational toil usually do best on GKE. EKS and AKS win instead when AWS ecosystem gravity or Microsoft identity integration matters more than day-2 automation.
This post first appeared on the Deplyra blog. We are a small DevOps and platform-engineering studio that builds and runs Kubernetes platforms on all three clouds — these are the notes we take between incidents. Questions or war stories? We read every reply.
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