EKS vs. AKS: choosing the right managed Kubernetes for enterprise scale

Key Points:

• Compliance Parity: Maintaining SOC2, ISO, and PCI-DSS standards across AWS and Azure environments.
• Identity Management: Navigating the critical differences between AWS IAM (IRSA) and Microsoft Entra ID.
• Multi-Cloud Fleet Management: Using an agentic control plane to prevent configuration drift and vendor lock-in at scale.

Both AKS and EKS are mature, production-grade managed Kubernetes solutions. However, for enterprise leadership, the choice is defined by identity ecosystems, compliance requirements, and Day-2 scaling limits.

While both handle initial deployments flawlessly, managing either at a scale of 1,000+ clusters creates immense operational debt without an agentic management layer to abstract the underlying cloud provider.

While Kubernetes is the industry standard for container orchestration, its inherent complexity often forces senior engineering teams into a "DIY management trap." For enterprise fleets, every hour spent on cluster maintenance acts as a tax on innovation, diverting resources away from core business logic.

Managed services like Amazon EKS and Azure AKS provide the necessary infrastructure foundation, but choosing between them requires a strategic evaluation of control plane pricing, version support cycles, and critical Day-2 operational features. This guide analyzes these trade-offs to help platform architects and CTOs standardize their global fleet management and protect engineering velocity.

Core platform details: Kubernetes versions & runtime support

When it comes to supporting the latest Kubernetes versions and underlying container runtimes, EKS and AKS have distinct approaches.

Amazon Elastic Kubernetes Service (eks)

• Kubernetes Versions: Prioritizes stability. Doesn't support the latest upstream immediately; default cluster versions are typically a couple of months older than upstream.
• Container Runtime: Since the deprecation of Dockershim, EKS primarily relies on containerd as its default container runtime.

Azure Kubernetes Service (AKS)

• Kubernetes Versions: Supports a rapid stream of new versions, with older versions being deprecated more quickly. Highly suited for teams requiring cutting-edge upstream features.
• Container Runtime: AKS also standardizes on containerd, adopting newer runtime standards rapidly.

You can track the development of containerd here for EKS.

Scalability limits & resource quotas

Understanding the maximum capacities and resource quotas is crucial for determining if your workloads are a fit for each environment.

Amazon Elastic Kubernetes Service (EKS)

• Maximum Number of Clusters per Region: Up to 100 clusters (can be increased by contacting AWS).
• Maximum Nodes per Cluster: Limited to 450 nodes per Node Group, with up to 30 Node Groups, totaling a maximum of 13,500 nodes.
• Maximum Pods per Node: Strictly dependent on the underlying Elastic Network Interfaces (ENIs) allowance. Platform engineers calculate this using: # of ENI * (# of IPv4 per ENI - 1) + 2.

Azure Kubernetes Service (AKS)

• Maximum Number of Clusters per Region: Sets 1,000 as the maximum number of clusters for a user account.
• Maximum Nodes per Cluster: Limited to 1,000 nodes across all node pools natively.
• Maximum Pods per Node: Supports a maximum of 250 pods per node; each node is allocated a subnet of 254 hosts (/24) providing 250 IP addresses.

You can read more about the numbers in this file from AWS and calculate it using the following formula:

Mapping is calculated from AWS EC2 API using the following formula:
 * First IP on each ENI is not used for pods
 * +2 for the pods that use host-networking (AWS CNI and kube-proxy)

  # of ENI * (# of IPv4 per ENI - 1) + 2

Pricing models & cost optimization

Pricing for managed Kubernetes includes two main components: the control plane and the underlying hardware.

Amazon Elastic Kubernetes Service (EKS)

• Control Plane Cost: Charges $0.10 per hour per control plane (~$72 per month for a cluster).
• Hardware Cost: Standard EC2 compute, EBS storage, and bandwidth pricing apply.
• Optimization: Demands strict usage of AWS Savings Plans, Reserved Instances, and intent-based Spot Instance scaling for Day-2 efficiency.

Azure Kubernetes Service (AKS)

• Control Plane Cost: Does not charge for the standard control plane itself.
• Uptime SLA Cost: For production workloads, the optional Uptime SLA costs $0.10 per hour per cluster (~$72 per month).
• VM Requirements: AKS requires nodes to use VMs with more than two CPUs for sufficient compute resources.

Cluster management & operational ease

Amazon Elastic Kubernetes Service (EKS)

• Host OS Support: Supports Amazon Linux 2, Ubuntu, Bottlerocket (a purpose-built container OS), and Windows.
• Upgrades: Node group upgrades require coordinated draining and AMI updates, often executed via eksctl or Terraform.
• Auto-Repair: Does not natively support automated node repair out-of-the-box.

Azure Kubernetes Service (AKS)

• Host OS Support: Supports Ubuntu and Windows Server for node creation.
• Upgrades: Provides highly streamlined, automated cluster and node pool upgrade paths.
• Auto-Repair: Automatically scans and repairs unhealthy nodes—a major Day-2 operational advantage.

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High availability & uptime guarantees (slas)

Amazon Elastic Kubernetes Service (EKS)

• SLA: Offers a 99.90% uptime SLA (maximum of 3.65 days of downtime per year).

Azure Kubernetes Service (AKS)

• SLA: Standard tier offers a 99.9% SLA.
• Enhanced SLA: The Paid tier provides a 99.95% SLA (maximum 4.38 hours of downtime per year) in specific Azure regions utilizing Availability Zones.

Networking & connectivity

Networking configurations define how pods communicate and how traffic enters the cluster. The abstraction drift here is significant.

Amazon EKS Networking

‍Primarily uses the Amazon VPC CNI plugin, which assigns pods IP addresses directly from the AWS VPC subnet. For internal ingress, platform teams must use AWS-specific annotations:

# AWS EKS Internal Load Balancer Annotation
apiVersion: v1
kind: Service
metadata:
  name: enterprise-api
  annotations:
    service.beta.kubernetes.io/aws-load-balancer-internal: "true"
    service.beta.kubernetes.io/aws-load-balancer-type: "nlb"

Azure AKS Networking

‍Offers Azure CNI (Traditional or Overlay) and Kubenet. Azure CNI assigns pod IPs directly from the VNet. Exposing services internally requires a completely different manifest:

# Azure AKS Internal Load Balancer Annotation
apiVersion: v1
kind: Service
metadata:
  name: enterprise-api
  annotations:
    service.beta.kubernetes.io/azure-load-balancer-internal: "true"

Storage options & persistent volumes

Applications requiring state must map persistent volumes to the cloud provider's underlying block storage.

Amazon EKS storage

‍Defaults to Amazon EBS via the EBS CSI driver.

# AWS EKS StorageClass
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: standard
provisioner: ebs.csi.aws.com
volumeBindingMode: WaitForFirstConsumer

Azure AKS storage

‍Defaults to Azure Managed Disks (AMDs).

# Azure AKS StorageClass
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: default
provisioner: disk.csi.azure.com
volumeBindingMode: WaitForFirstConsumer

Identity & access management (IAM)

Managing secure pod-to-cloud-resource communication creates the highest degree of configuration drift between the two providers.

Amazon EKS (irsa)

‍EKS uses IAM Roles for Service Accounts (IRSA). Developers must annotate Kubernetes Service Accounts with specific AWS ARNs to grant pods access to services like S3 or DynamoDB:

metadata:
  annotations:
    eks.amazonaws.com/role-arn: arn:aws:iam::123456789012:role/s3-reader-role

Azure AKS (workload identity)

‍AKS utilizes Microsoft Entra ID (formerly AAD) Workload Identity. The configuration requires federated credentials and completely different annotations:

metadata:
  annotations:
    azure.workload.identity/client-id: 1234abcd-12ab-34cd-56ef-1234567890ab

The 1,000-cluster reality: the multi-cloud abstraction gap

Comparing EKS and AKS feature-by-feature is a crucial Day-0 exercise. But for a Platform Architect or CTO, the Day-2 reality is that massive enterprises rarely stick to a single cloud. Due to redundancy requirements, regulatory data residency, or acquisitions, you will likely run both.

When your fleet scales beyond 10, 50, or 1,000 clusters, the YAML drift shown above (LoadBalancers, StorageClasses, IAM roles) becomes a massive operational liability.

• The Configuration Drift Problem: Managing IRSA for EKS and Entra ID for AKS simultaneously requires maintaining two completely separate sets of infrastructure-as-code (IaC).
• The Toil Multiplier: Upgrading 500 EKS clusters and 500 AKS clusters requires completely different API calls and validation checks.

To survive at enterprise scale, you must bridge the abstraction gap. Instead of hiring siloed AWS and Azure experts to manage disparate Terraform modules, leading organizations rely on an intent-based control plane.

You define your requirements once, and the platform autonomously translates that intent into the correct EKS or AKS configurations; maintaining perfect compliance across your entire fleet.

🚀 Real-world proof

Nextools utilized Qovery as a single abstraction layer to manage high-performance e-commerce apps across AWS and GCP simultaneously.

⭐ The result: Reduced new cluster deployment time from days to 30 minutes and removed the requirement for specialized cloud infrastructure experts. Read the full Nextools case study here.

Choosing your path and simplifying Kubernetes management

Both Amazon EKS and Azure AKS are phenomenal, production-ready foundations. If you are deeply embedded in the Microsoft ecosystem, AKS provides the path of least resistance. If you require massive scale and deep AWS integration, EKS is the industry heavyweight.

However, the ultimate winner in modern cloud architecture isn't the cloud provider; it's the team that can orchestrate them efficiently.

Stop treating clusters as unique environments with cloud-specific quirks. By unifying your infrastructure under Qovery, you eliminate Day-2 configuration drift, enforce global security, and manage your entire 1,000+ cluster fleet through a single pane of glass.

Automate Day 2 for your entire fleet

Managing 1 or 1,000 clusters shouldn't feel different. Qovery’s agentic platform eliminates toil and handles configuration drift automatically so you can focus on scale, not maintenance.

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FAQs:

What are the main differences between EKS and AKS?

Amazon EKS offers deep integration into the AWS ecosystem, highly stable upstream releases, and massive node scalability limits (13,500 nodes per cluster). Azure AKS provides rapid upstream updates, a free tier for the control plane (without the Uptime SLA), and built-in automated node repair out of the box.

How are pod limits calculated in Amazon EKS vs. Azure AKS?

In EKS using the native AWS-CNI, maximum pod density is strictly limited by the number of Elastic Network Interfaces (ENIs) and IP addresses available on the specific EC2 instance type. In AKS, nodes are allocated a /24 subnet by default, supporting a hard maximum of 250 pods per node.

How do enterprises manage fleets across both EKS and AKS?

Managing multi-cloud Kubernetes fleets natively causes configuration drift, as Terraform modules, RBAC policies, and Identity Access Management (IRSA vs. Entra ID) differ completely between AWS and Azure. Enterprises resolve this by implementing an agentic control plane that abstracts provider-specific configuration, allowing teams to declare global intent that deploys identically across both platforms.