The three big managed Kubernetes services — Amazon EKS, Google GKE, and Azure AKS — converged on similar feature sets years ago. Picking between them in 2026 is less about "which has Kubernetes" and more about which fits your cloud, your team, and your specific operational preferences.
This post is the practical comparison: where each one shines, where each has rough edges, and the costs that are easy to miss.
The Quick Answer
- Already on AWS? EKS, almost always.
- Already on GCP? GKE, the most opinionated and polished.
- Already on Azure? AKS, the choice if Azure is the platform.
- Greenfield, no cloud preference? GKE has the best Kubernetes experience.
The cloud you are already on dominates the decision. Network costs, IAM integration, supporting services, and team familiarity all reinforce the existing choice.
For most teams, this is the answer. The rest of the post is for the cases where the choice is actually open.
Control Plane Pricing
All three charge for the control plane:
- EKS: $0.10/hour per cluster (~$73/month).
- GKE: $0.10/hour per cluster, with the first zonal cluster free per billing account.
- AKS: Free control plane.
For multiple clusters, GKE's free first cluster is meaningful. AKS's free control plane is meaningful at any cluster count. EKS is the most expensive at scale.
The pricing differences are small in absolute terms — a fraction of node costs for most clusters. They matter for teams running many small clusters.
Node Pricing
Once you add nodes, the differences shrink. All three charge for the underlying VMs at standard cloud prices.
The differences are in features:
- GKE Autopilot. A "serverless Kubernetes" mode where you pay for pod resources, not nodes. GCP manages the underlying nodes entirely.
- EKS Auto Mode. Released late 2024, integrates Karpenter for node autoscaling.
- AKS has similar autoscaling features without a distinct marketing name.
GKE Autopilot is the most opinionated — minimal node management, slightly higher per-pod cost. It is the right call for teams that want managed Kubernetes without managing nodes.
Upgrade Experience
How each handles version upgrades:
GKE: The most aggressive about upgrades. Default channels (Stable, Regular, Rapid) auto-upgrade based on release timing. Autopilot auto-upgrades aggressively.
EKS: Manual control plane upgrades, then node upgrades. No auto-upgrade for the control plane unless you opt in. Node group rollouts are deliberate.
AKS: Similar to EKS. Manual control plane upgrades by default, with auto-upgrade channels available.
For teams that want to stay current: GKE's auto-upgrade defaults reduce drift. For teams that need predictable upgrade timing: EKS or AKS with manual upgrades.
Networking
Native networking models differ:
EKS uses the AWS VPC CNI by default. Pods get real VPC IPs. AWS Security Groups apply to pods. Networking feels like AWS, which is fine if you live in AWS.
GKE uses GCP's networking. Pods can use Cloud DNS, Cloud NAT, Cloud Load Balancing — all integrated. The default Dataplane V2 is Cilium-based, with eBPF.
AKS offers Azure CNI (pods get VNet IPs) or Kubenet (overlay). Azure CNI is the default. Cilium-based Dataplane support is newer than GKE's.
For NetworkPolicy support: all three have it, with varying quality. GKE's Cilium-based default is the most feature-complete.
Identity Integration
How Kubernetes service accounts map to cloud IAM:
EKS: IRSA (IAM Roles for Service Accounts) is mature. Service accounts can assume IAM roles. Standard pattern.
GKE: Workload Identity is GCP's equivalent. Service accounts authenticate as GCP service accounts. Cleaner than IRSA in some ways.
AKS: Workload Identity (Azure AD-based). Newer than the alternatives but functional.
All three handle the basic "pod talks to cloud service" pattern. The implementations differ in elegance; functionality is comparable.
Storage
EKS: EBS CSI driver. Standard AWS storage features. Includes EFS for shared file storage.
GKE: Persistent Disk CSI driver. Includes Filestore for NFS-like sharing.
AKS: Azure Disk CSI driver, Azure Files for shared.
Storage classes work similarly. The interesting differences are in advanced features: GKE has the most integrated experience with regional disks and snapshots; EKS has the broadest range of options.
Observability
How each integrates with the cloud's observability platform:
EKS: Containers send logs to CloudWatch Logs. Container Insights for metrics. AWS Distro for OpenTelemetry for traces. Mature but verbose.
GKE: Cloud Logging and Cloud Monitoring integrate cleanly. The Operations Suite (formerly Stackdriver) shows cluster-aware data with minimal setup.
AKS: Azure Monitor integration. Container Insights for cluster-level data.
For teams using third-party observability (Datadog, New Relic, Honeycomb): all three work fine, with similar setup effort.
For cloud-native observability: GKE's integration is the smoothest.
Add-ons and Managed Services
Each cloud has managed services you might want alongside Kubernetes:
AWS: RDS, ElastiCache, MSK (Kafka), MQ (RabbitMQ), Athena, etc. Broadest catalog.
GCP: Cloud SQL, Memorystore, Pub/Sub, BigQuery. Excellent for data and analytics workloads.
Azure: Cosmos DB, Azure SQL, Service Bus, Synapse. Strong for enterprise integrations.
For a Kubernetes cluster that uses managed services for stateful workloads: the choice is shaped by which managed services you need. GCP has the most mature data/analytics stack; AWS has the broadest catalog; Azure has the best enterprise integrations.
Edge Cases
Specific scenarios that favor one over another:
Heavy data workloads: GKE with BigQuery, Dataflow, Pub/Sub. The integration is best on GCP.
Strong enterprise compliance: AKS in regulated industries that already use Azure. AAD integration is unmatched for Microsoft-centric organizations.
Highly available multi-region: All three can do this, but EKS has the broadest regional footprint for AWS-resident workloads.
Edge computing: GCP's Anthos and AWS Outposts both extend Kubernetes to edge. Azure Stack is the equivalent.
Bare metal: AKS Edge Essentials and Anthos Bare Metal are options. EKS does not have a strong bare-metal story.
Maturity Reality
All three are mature. None is a "this barely works" choice in 2026.
The rough differences in opinion:
- GKE is the most Kubernetes-native. It feels designed for Kubernetes; the rest of GCP wraps around it cleanly.
- EKS is the most "AWS service that happens to be Kubernetes." Feature-rich but with AWS-specific patterns.
- AKS is the most "Microsoft enterprise Kubernetes." Strong integrations with the Microsoft stack.
If you have no constraints and value the cleanest Kubernetes experience: GKE.
If you are on AWS or value the AWS ecosystem: EKS.
If you are in a Microsoft shop: AKS.
Hidden Costs
The costs that surprise teams:
EKS: Data transfer (NAT Gateway charges, cross-AZ traffic), CloudWatch logs at scale.
GKE: Cross-zone replication for regional clusters, network egress for multi-region.
AKS: Premium tier for production-grade SLAs, log analytics ingestion costs.
For all three: node costs dominate. Control plane costs are a footnote. Network and observability costs can grow surprisingly.
Migration Considerations
Migrating between managed Kubernetes services is a significant project. The Kubernetes manifests are mostly portable, but:
- Identity integration changes (IRSA vs Workload Identity)
- Storage class names and parameters differ
- Cloud-specific operators and tooling have to be replaced
- Observability needs reconfiguration
- Networking model differences may matter
A real migration is months of engineering work. Pick once with care.
Multi-Cloud Kubernetes
Some teams run on multiple clouds for redundancy or compliance. The reality:
- Kubernetes manifests can be portable
- Cloud-specific integrations cannot
- Observability has to span clouds
- IAM is per-cloud
Most "multi-cloud" deployments are really "primary cloud + lift-and-shift fallback." True multi-cloud where the same workloads run identically is expensive to maintain.
If multi-cloud is a real requirement: pick portable abstractions (Helm charts, Terraform with multi-cloud providers, observability that spans clouds). Otherwise: a single cloud is dramatically simpler.
A Practical Default
For teams starting fresh in 2026:
- GKE for the cleanest Kubernetes experience, especially for data-heavy workloads.
- EKS for AWS-resident workloads or teams with AWS expertise.
- AKS for Microsoft-aligned organizations.
For teams already on a cloud: stay on that cloud's managed Kubernetes. The integration benefits compound.
The differences are smaller than they were in 2020. Pick the one that fits the rest of your stack; spend your engineering energy on the application, not on choosing the platform.
Comparing managed Kubernetes options for a new project or evaluating a switch? We help teams pick based on the actual operational fit, not the cloud's pitch. scopeforged.com