EKS vs AKS in 2026: What Kubernetes Actually Costs on Each

Every EKS-vs-AKS cost comparison opens with the same headline: Azure’s control plane is free, AWS charges $0.10/hour. That’s true, and it’s also the least interesting part of the decision.

The control-plane gap is real but modest

AWS EKS bills roughly $73/month per cluster for the control plane. Azure AKS doesn’t charge for it — you pay only for the nodes underneath. For a single-cluster team, that’s a real but small gap. Multiply it across ten clusters spanning dev, staging, and multiple regions, and it starts to look like a meaningful line item rather than a rounding error, though still a small one relative to compute spend.

Compute is closer than the discount tables suggest

On-demand pricing for comparable instance types puts AWS around $121/month for a mid-size general-purpose instance, versus roughly $140/month for Azure’s equivalent — Azure runs a bit higher on list price for the same compute. But Azure’s long-term reserved pricing changes that picture: a 3-year reserved commitment can bring that same Azure instance down to around $55/month, a steeper discount curve than AWS typically offers at comparable commitment terms.

The practical read: if you’re running mostly on-demand or short-commitment infrastructure, AWS tends to be cheaper per core. If you can commit to multi-year terms on stable baseline capacity, Azure’s reserved discounts can flip that comparison.

Storage and the line items nobody benchmarks

Azure’s hot object storage runs a bit cheaper than AWS’s equivalent tier — a smaller gap than compute, but one that compounds across log retention, backup snapshots, and container image storage that most teams never audit line by line.

The number that actually determines your bill

Here’s what most EKS-vs-AKS comparisons skip entirely: the gap between either cloud’s list price is usually dwarfed by the gap between what you’re provisioned for and what you’re actually using. If your clusters run anywhere near the current industry average — 8% CPU utilization — the difference between EKS and AKS pricing is a rounding error next to the difference between requested and actual usage on your own workloads.

Put differently: migrating clouds to save on list price while running at single-digit utilization is optimizing the wrong variable. Fixing utilization first captures a larger number, on whichever cloud you’re already running.

What to check before a migration conversation starts

Before running a cloud-switch cost-benefit analysis, it’s worth answering a cheaper question first: on your current cloud, namespace by namespace, how much of what you’re paying for is actually being used. That number tells you whether the lever worth pulling is “switch clouds” or “right-size what’s already here” — and for most fleets, the second lever is bigger and doesn’t require a migration project.

Frequently asked questions

Is Azure AKS always cheaper than AWS EKS? Not universally — it depends heavily on commitment term and instance mix. Azure tends to win on control-plane cost and long-term reserved pricing; AWS is often more competitive on-demand and for short-commitment workloads.

Does GKE change this comparison? GKE has its own pricing structure (a free control plane on the Autopilot tier for standard clusters, similar mechanics to AKS on Standard) and is worth including if multi-cloud is genuinely on the table — but for teams already committed to AWS or Azure for other reasons, it’s rarely the deciding factor.

Should we migrate clouds to reduce our Kubernetes bill? Usually not as a first move. Cloud migrations are expensive and risky in ways that dwarf the pricing gap between EKS and AKS for most teams; fixing utilization on your current cloud almost always has a better cost-to-effort ratio.

How much does the free AKS control plane actually save at scale? At ten clusters, roughly $730/month versus EKS’s control-plane charge — real money, but typically smaller than what a single meaningfully over-provisioned namespace costs on either cloud.

Before comparing clouds, see what you’re actually using on the one you’re on — connect a cluster and get cost mapped to real utilization, not list-price estimates.