Cloud Infrastructure

22 min read

EKS · AKS · GKE Compared

February 2026

Managed Kubernetes Services: Complete Comparison Guide 2026

Q: Should I choose managed Kubernetes or self-managed?

Choose managed Kubernetes if: your team has fewer than 3 dedicated platform engineers, you want to focus on applications rather than infrastructure, you need rapid time-to-production, or you require provider-backed SLAs. Choose self-managed if: you have strict data sovereignty requirements that prohibit cloud, you need deep control over every component (custom etcd tuning, custom schedulers), or you have a large platform team (5+) with deep Kubernetes expertise. For 90% of organizations in 2026, managed Kubernetes is the right choice.

EKS vs AKS vs GKE vs self-managed—compare across 15+ criteria including pricing, scaling, security, and ecosystem. Includes a production checklist and real-world migration case study.

Key Takeaways

Managed Kubernetes reduces operational overhead by 60-80% compared to self-managed clusters
GKE leads in features and maturity, EKS wins for AWS-native ecosystems, AKS is best for Microsoft shops
Compute costs (worker nodes) represent 70-85% of total spend—autoscaling is the biggest cost lever
A production-ready cluster requires 20+ configurations across security, monitoring, networking, and DR

What Are Managed Kubernetes Services?

Managed Kubernetes services are cloud provider offerings that abstract away the complexity of running the Kubernetes control plane. Instead of provisioning, patching, and scaling the API server, etcd database, scheduler, and controller manager yourself, the cloud provider handles all of it behind a managed endpoint. Your team focuses on deploying applications, configuring networking, and managing workloads.

The three dominant managed Kubernetes services in 2026 are Amazon EKS (Elastic Kubernetes Service), Azure AKS (Azure Kubernetes Service), and Google GKE (Google Kubernetes Engine). Each provides a fully managed control plane with provider-backed SLAs, integrated IAM, and native cloud service integrations. The differences lie in maturity, feature depth, pricing, and ecosystem.

Running Kubernetes in production requires expertise across networking (CNI, service mesh, ingress), security (RBAC, pod security, network policies), storage (CSI drivers, persistent volumes), observability (metrics, logs, traces), and upgrade management. Managed services handle the most critical and difficult component—the control plane—while providing managed node pools, auto-upgrades, and integrated monitoring to simplify the rest.

Managed Kubernetes Comparison: EKS vs AKS vs GKE vs Self-Managed

Below is a comprehensive comparison across 15+ criteria that matter most for production Kubernetes deployments.

Criteria	AWS EKS	Azure AKS	Google GKE	Self-Managed
Control Plane Cost	$0.10/hr ($73/mo)	Free (paid SLA: $0.10/hr)	$0.10/hr ($73/mo)	Your infra + ops time
Control Plane SLA	99.95%	99.95% (paid tier)	99.95% (Regional)	Depends on your setup
Serverless Nodes	Fargate profiles	ACI virtual nodes	Autopilot mode	Not available
Autoscaling	Karpenter (native)	KEDA + Cluster Autoscaler	GKE Autopilot / NAP	Cluster Autoscaler
Max Nodes/Cluster	5,000	5,000	15,000	5,000 (recommended)
K8s Version Lag	~2-3 months	~1-2 months	~1-2 weeks	Immediate
Default CNI	VPC CNI (AWS-native)	Azure CNI / kubenet	GKE Dataplane V2 (Cilium)	Calico / Cilium / Flannel
Service Mesh	App Mesh / Istio add-on	Istio add-on (managed)	Anthos Service Mesh	Manual install
GitOps Integration	ArgoCD / Flux (manual)	Flux (built-in extension)	Config Sync (native)	ArgoCD / Flux (manual)
IAM Integration	IRSA / Pod Identity	Workload Identity (AAD)	Workload Identity (GCP)	Manual OIDC setup
Managed Add-ons	CoreDNS, kube-proxy, VPC CNI	Monitoring, policy, mesh	20+ managed add-ons	None
GPU Support	P4/P5 instances, Inf2	NC/ND-series VMs	A2/A3, TPU pods	Manual driver setup
Multi-Cluster	EKS Connector	Azure Arc	GKE Fleet / Anthos	Rancher / Cluster API
Backup/DR	Velero + EBS snapshots	AKS backup (preview)	GKE backup for GKE	Velero (manual)
Learning Curve	Medium-High	Medium	Low-Medium	Very High
Best For	AWS-native orgs	Microsoft/Azure shops	K8s-first teams	Air-gapped / full control

Pricing Deep Dive: What Managed Kubernetes Really Costs

The control plane fee is just the tip of the iceberg. Real-world Kubernetes costs are dominated by compute (worker nodes), storage (persistent volumes, snapshots), networking (load balancers, NAT gateways, inter-AZ traffic), and observability (log ingestion, metrics storage). Here is a realistic breakdown for a mid-size production cluster.

AWS EKS — Typical Monthly Cost

20-node cluster, mixed on-demand + spot, us-east-1

EKS Control Plane	$73
EC2 Compute (12x m6i.xlarge on-demand)	$2,764
EC2 Compute (8x m6i.xlarge spot @ ~60% savings)	$737
EBS gp3 Storage (2 TB total)	$160
ALB Ingress (2x Application LB)	$50
NAT Gateway (3 AZs, 500 GB/mo)	$225
ECR (container registry, 100 GB)	$10
CloudWatch (metrics + logs)	$180
Total Estimated	~$4,199/mo

Azure AKS — Typical Monthly Cost

20-node cluster, mixed on-demand + spot, East US

AKS Control Plane (with SLA)	$73
VMs (12x D4s_v5 on-demand)	$2,650
VMs (8x D4s_v5 spot @ ~65% savings)	$620
Managed Disks (2 TB Premium SSD)	$153
Azure Load Balancer (Standard)	$40
NAT Gateway + bandwidth	$195
ACR (container registry, 100 GB)	$15
Azure Monitor (metrics + logs)	$200
Total Estimated	~$3,946/mo

Google GKE — Typical Monthly Cost

20-node Standard cluster, mixed on-demand + spot, us-central1

GKE Management Fee	$73
GCE Instances (12x e2-standard-4 on-demand)	$2,320
GCE Instances (8x e2-standard-4 spot @ ~70% savings)	$465
Persistent Disks (2 TB SSD)	$340
Cloud Load Balancing	$35
Cloud NAT (500 GB/mo)	$50
Artifact Registry (100 GB)	$10
Cloud Monitoring + Logging	$150
Total Estimated	~$3,443/mo

Key takeaway: The control plane is less than 2% of total cost. The real savings come from right-sizing instances, using spot/preemptible nodes, and implementing autoscaling with tools like Karpenter (EKS) or GKE Autopilot. Organizations that implement FinOps practices for Kubernetes typically reduce compute spend by 30-50%.

When to Choose Managed vs Self-Managed Kubernetes

The managed vs self-managed decision is not purely technical—it is an organizational capacity question. Here is a framework for making the right choice.

Choose Managed Kubernetes When:

Your platform/DevOps team has fewer than 3 dedicated engineers
You want production clusters running within days, not months
You need provider-backed SLAs (99.95%+) for compliance or customer contracts
You prefer your team to focus on application delivery rather than K8s internals
You want managed upgrades and security patching without downtime

Choose Self-Managed Kubernetes When:

Data sovereignty laws prohibit cloud provider control plane access
You require air-gapped or on-premises deployment (government, defense)
You need custom etcd tuning, custom schedulers, or non-standard API server configurations
You have 5+ platform engineers with deep Kubernetes expertise
You want to avoid any vendor lock-in to a specific cloud provider

For the vast majority of organizations in 2026, managed Kubernetes is the correct choice. The operational cost of maintaining a self-managed control plane—including on-call rotations, upgrade planning, etcd backup/restore, and security patching—is equivalent to 1-2 full-time senior engineers ($200-400K/year). Managed services provide this for $73/month per cluster.

Add-ons and Ecosystem: Istio, Karpenter, Cilium, ArgoCD

A managed Kubernetes cluster is a starting point—production readiness requires a curated set of add-ons for networking, autoscaling, security, and deployment. Here are the four most impactful ecosystem tools in 2026.

Karpenter — Intelligent Node Autoscaling

Karpenter replaces the legacy Cluster Autoscaler with a fundamentally better approach. Instead of scaling pre-defined node groups, Karpenter provisions the optimal instance type, size, and purchase option (on-demand, spot, reserved) based on pending pod requirements in real-time. It typically reduces compute costs by 30-40% while improving scheduling latency from minutes to seconds. Originally AWS-only, Karpenter now supports Azure (preview) and has growing multi-cloud adoption.

Cilium — eBPF-Powered Networking and Security

Cilium is the leading CNI for Kubernetes, using eBPF (extended Berkeley Packet Filter) to provide high-performance networking, transparent encryption, and identity-based network policies without the overhead of iptables. GKE adopted Cilium as its default dataplane (GKE Dataplane V2). Cilium also provides Hubble for network observability, giving teams real-time visibility into service-to-service traffic without sidecar proxies.

Istio — Service Mesh for Traffic Management

Istio provides advanced traffic management (canary deployments, traffic splitting, circuit breaking), mutual TLS encryption between services, and detailed telemetry. The Istio Ambient Mesh mode (GA in 2025) eliminates sidecar proxies, reducing resource overhead by 50-70%. All three major providers now offer managed Istio: GKE has Anthos Service Mesh, AKS has Istio add-on, and EKS supports App Mesh or self-managed Istio.

ArgoCD — GitOps-Native Continuous Deployment

ArgoCD is the de-facto standard for Kubernetes deployments via GitOps. It watches Git repositories containing Kubernetes manifests (Helm charts, Kustomize overlays, raw YAML) and automatically syncs them to your clusters. Benefits include declarative deployments, automatic drift detection, instant rollback via Git revert, and a complete audit trail. ArgoCD supports multi-cluster management, making it essential for organizations running workloads across multiple managed K8s clusters.

Production Checklist for Managed Kubernetes

Launching a managed Kubernetes cluster is day one. Making it production-ready requires careful configuration across security, monitoring, networking, and disaster recovery. Use this checklist to validate your setup.

Security Hardening

RBAC configured with least-privilege roles (no cluster-admin for developers)
Pod Security Standards enforced (restricted or baseline profiles)
Network policies restricting pod-to-pod communication (deny-all default)
Workload Identity configured (no static cloud credentials in pods)
Secrets encrypted at rest and managed via external store (Vault, AWS Secrets Manager)
Container images scanned and signed (Trivy + Cosign)
API server endpoint restricted (private endpoint or IP allowlist)

Monitoring and Observability

Metrics collection with Prometheus or cloud-native monitoring (Datadog, Grafana Cloud)
Log aggregation with Loki, CloudWatch, or Elasticsearch
Distributed tracing with OpenTelemetry (Jaeger or Tempo backend)
Alerting configured for cluster health, node pressure, and pod restarts
SLO-based monitoring with burn rate alerts for key services

Backup and Disaster Recovery

Velero or provider-native backup (GKE Backup) configured with daily schedule
etcd snapshots stored in cross-region bucket (for self-managed)
Persistent Volume snapshots automated with VolumeSnapshot CRDs
DR cluster in secondary region with GitOps-based replication
Restore procedure tested quarterly (actual restore, not just documentation)
RTO and RPO targets defined and validated for tier-1 services

Case Study: Migrating from Self-Managed to EKS

Company: B2B SaaS platform, 60 engineers, 35 microservices running on self-managed Kubernetes (kubeadm) across 3 bare-metal clusters in a co-location facility.

Before: A 4-person platform team spent 60% of their time on K8s operations—etcd backups, version upgrades (3-day processes with maintenance windows), node replacements, and certificate rotations. Cluster upgrades were so painful that they were 4 versions behind upstream. Incidents averaged 3 per month related to infrastructure, with an MTTR of 2.5 hours.

Migration approach: Provisioned EKS clusters with Terraform using a modular architecture (VPC, EKS, add-ons as separate modules). Migrated services incrementally using ArgoCD—both old and new clusters ran in parallel for 8 weeks. Implemented Karpenter for autoscaling and Cilium for networking. Built a comprehensive monitoring stack with Prometheus, Grafana, and PagerDuty.

After (4 months):

Infrastructure incidents: 3/month → 0.3/month (90% reduction)
K8s upgrades: 3-day process → 2-hour rolling update (zero downtime)
Platform team capacity: 60% ops → 15% ops (freed 3 engineers for product work)
Compute costs: $18,000/month (colo) → $11,200/month EKS (38% savings with Karpenter + spot)
Time to provision new cluster: 2 weeks → 25 minutes (Terraform)

"The biggest surprise was how much time self-managed K8s was silently stealing from the team. Moving to EKS didn't just reduce incidents—it gave us three engineers back to build platform features our developers had been asking for." — Head of Platform Engineering

Choosing the Right Managed Kubernetes Service

The managed Kubernetes landscape in 2026 is mature and competitive. All three major providers deliver reliable, production-grade control planes. Your decision should be driven by your existing cloud ecosystem, team expertise, and specific workload requirements rather than raw feature comparisons.

If you are already on AWS, EKS with Karpenter is the natural choice—deep IAM integration, VPC-native networking, and Karpenter's intelligent autoscaling deliver the best cost-performance ratio. If you prioritize the most Kubernetes-native experience with the latest features first, GKE is unmatched—Autopilot mode, Dataplane V2, and Config Sync provide a fully managed, opinionated platform. If your organization runs on Microsoft technologies, AKS integrates seamlessly with Azure AD, Azure DevOps, and the broader Microsoft ecosystem.

Regardless of provider, invest in the ecosystem layer: Karpenter or Autopilot for autoscaling, Cilium for networking, ArgoCD for GitOps deployments, and a comprehensive monitoring stack. The managed control plane gives you a foundation—the add-ons and operational practices you build on top determine whether your Kubernetes platform enables developer velocity or becomes a maintenance burden.

Frequently Asked Questions

What are managed Kubernetes services?

Managed Kubernetes services are cloud provider offerings that handle the Kubernetes control plane (API server, etcd, scheduler, controller manager) so your team can focus on deploying and managing workloads. Providers like AWS (EKS), Azure (AKS), and Google (GKE) handle control plane upgrades, patching, high availability, and scaling. You still manage worker nodes (or use managed node pools/Fargate/Autopilot), application deployments, and cluster add-ons. Managed services reduce operational overhead by 60-80% compared to self-managed Kubernetes.

How much do managed Kubernetes services cost?

Pricing varies by provider: AWS EKS charges $0.10/hour ($73/month) per cluster for the control plane plus compute costs. Azure AKS offers free control plane with paid uptime SLA ($0.10/hour for 99.95% SLA). Google GKE charges $0.10/hour per cluster (Autopilot is free for control plane, pay per pod). The major cost driver is compute—worker node instances typically represent 70-85% of total K8s spend. For a production cluster running 20 nodes, expect $2,000-$8,000/month total depending on instance types and region.

Should I choose managed Kubernetes or self-managed?

Choose managed Kubernetes if your team has fewer than 3 dedicated platform engineers, you want to focus on applications rather than infrastructure, you need rapid time-to-production, or you require provider-backed SLAs. Choose self-managed if you have strict data sovereignty requirements that prohibit cloud, you need deep control over every component, or you have a large platform team (5+) with deep Kubernetes expertise. For 90% of organizations in 2026, managed Kubernetes is the right choice.

Which managed Kubernetes service is best for production workloads?

The best choice depends on your cloud ecosystem: AWS EKS is best if you're already on AWS—deep integration with IAM, ALB, EBS, and Karpenter for autoscaling. Google GKE is the most mature and feature-rich, with Autopilot mode, Config Sync for GitOps, and the best Kubernetes-native experience. Azure AKS is ideal for Microsoft-centric organizations with strong Active Directory and Azure DevOps integration. For multi-cloud strategies, GKE Anthos or Rancher provide consistent management across providers.

How long does it take to migrate to managed Kubernetes?

Migration timelines: containerizing a simple application takes 1-2 weeks. Migrating a containerized application to managed K8s takes 2-4 weeks including networking, storage, and security configuration. A full platform migration (10+ services, CI/CD, monitoring, security) takes 8-16 weeks. Key phases: (1) Assessment and architecture design, (2) Infrastructure provisioning with IaC, (3) Application migration and testing, (4) Cutover and optimization. Using Terraform for infrastructure and ArgoCD for deployments accelerates the process significantly.