Kubernetes Production Topologies: EKS vs GKE vs AKS

Kubernetes has become the backbone of modern infrastructure, but the way you architect it, especially in production, determines whether you're building a resilient platform or a ticking time bomb. The managed services offered by AWS (EKS), Google Cloud (GKE), and Azure (AKS) differ significantly in their defaults, assumptions, and operational models. Understanding these nuances is critical for making the right design choices early.

Let’s walk through the key factors that shape a production-grade Kubernetes topology and how the three major providers approach them.

Control Plane Availability¶

AWS takes a strong position here. Every EKS cluster comes with a highly available, multi-master control plane spread across three Availability Zones. There’s no need to opt in, pay more, or configure anything. You get a 99.95% SLA by default.

GKE offers more flexibility. You can choose zonal clusters for simplicity, but that gives you a single-master setup with a 99.5% SLA and a clear risk of control plane downtime. The better choice is a regional cluster or Autopilot mode, both of which provision redundant masters across multiple zones and offer a 99.95% SLA.

Azure hides more behind service tiers. On the Free tier, AKS does not guarantee uptime at all. Only when you move to the Standard or Premium tiers and explicitly deploy across Availability Zones, do you get a comparable 99.95% control plane SLA. In short, high availability on AKS is opt-in and paywalled.

Worker Node Strategy¶

The differences in philosophy become even more apparent at the node layer. EKS gives you complete control and very little automation. You are expected to manually create node groups in different AZs and design your own failure domains. This suits teams that want deep control but raises the risk of misconfiguration.

GKE offers both manual and automated paths. In Standard mode, you manage node pools directly and can choose between zonal, multi-zonal, or regional deployments. In Autopilot mode, GKE abstracts all of this. You don’t create or manage nodes. Google handles placement, scaling, and recovery automatically, ensuring your workloads are distributed across zones without effort.

AKS sits in the middle. It supports both zone-spanning node pools (which distribute nodes automatically) and zone-aligned node pools (which you manage per zone). However, AKS defaults are not very opinionated, and if you don’t explicitly configure zones, your nodes could all end up in a single AZ. That makes it easy to get this wrong if you’re not careful.

Regional High Availability¶

All three platforms support highly available deployments within a single region, but the defaults vary. EKS makes the control plane HA by default, but you must architect node groups across zones and implement scheduling rules yourself. If all your nodes end up in one AZ, your workloads will go down during a zone failure, even if the API server stays online.

GKE regional clusters distribute both control plane and worker nodes across zones automatically. Combined with features like surge upgrades and Pod Disruption Budget-aware orchestration, this provides a strong out-of-the-box resilience story. In Autopilot, it’s even harder to get it wrong, multi-zone placement is built in.

AKS provides comparable resilience but requires manual configuration. Standard or Premium tier clusters deployed with Availability Zones can match the SLA and operational guarantees of EKS and GKE. However, if you don’t select zones explicitly or you remain on the Free tier, your cluster’s survivability will suffer.

Upgrade Strategy¶

EKS puts you in the driver’s seat. Control plane upgrades are initiated by the user and rolled out gradually behind the scenes. Worker node upgrades are also user-controlled, though Managed Node Groups simplify this by automating draining and replacement. It’s a hands-on model that gives you precision, but also demands diligence.

GKE is more prescriptive. You can use release channels to define how aggressively you want upgrades, and Google will handle control plane upgrades accordingly. For node upgrades, you can opt into auto-upgrade or control the process manually. In Autopilot, everything is handled for you, including maintenance windows and surge settings.

AKS blends the two. Control plane upgrades can be scheduled or automated based on channel selection. Node pools support surge upgrades, and the Premium tier offers extended support for older Kubernetes versions. The choice of tier influences how much automation and support you get.

Multi-Region Topologies¶

No provider allows a single Kubernetes cluster to span regions. Multi-region resilience requires running separate clusters and coordinating them via traffic routing and configuration sync.

In AWS, you’ll need to deploy a separate EKS cluster per region and use tools like Route 53 or Global Accelerator for failover. Configuration sync is left to you, typically via GitOps or Terraform. AWS provides the primitives but expects you to build the architecture.

GKE offers the most polished multi-cluster experience. Global Load Balancing is integrated natively. Multi-Cluster Ingress and Multi-Cluster Services allow seamless failover between clusters. Anthos Config Management adds GitOps-style syncing and policy enforcement across fleets. It’s a more cohesive and opinionated stack, but the best features live behind Anthos, which comes at a premium.

AKS uses Azure Front Door or Traffic Manager to handle global routing. You can create paired-region clusters and route traffic accordingly. Azure Fleet Manager helps manage configuration sync across regions, though it’s still evolving. As with AWS, you’re responsible for much of the orchestration, though Azure does provide structured guidance.

SLA Guarantees and Real-World Implications¶

EKS, GKE (regional or Autopilot), and AKS (Standard/Premium with zones) all offer a 99.95% SLA on control plane uptime. But these SLAs apply only to the API server, not to your applications, workloads, or persistent volumes. A well-architected cluster needs multi-zone node placement, replica distribution, disruption budgets, and zone-tolerant storage.

In practice, uptime is not determined by the SLA document. It’s defined by your architecture. The provider keeps the control plane alive. Everything else is your responsibility.

Operational Ownership Models¶

EKS leans toward full control. You decide how to run nodes, when to upgrade, how to autoscale, and which features to adopt. AWS gives you powerful primitives but won’t stop you from making dangerous choices.

GKE draws a clear line. If you want control, Standard mode lets you configure every detail. If you want a hands-off experience, Autopilot delivers a secure and scalable platform with minimal effort. Both modes are production-ready; the choice depends on your team’s maturity and preferences.

AKS provides a layered abstraction. You can start with full control and gradually opt into features like auto-upgrades and autoscaling. The upcoming “AKS Automatic” mode will likely compete directly with Autopilot. AKS’s pricing tiers (Free, Standard, Premium) also allow you to match cluster features and support to workload criticality.

Final Thoughts¶

Across all three providers, production-readiness is achievable, but never automatic. You need to make the right topology choices, enforce good architectural hygiene, and understand the trade-offs of your chosen platform.

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