Notes / tag / multi-cluster

#multi-cluster

8 notes

1 — AKS

AKS makes the control plane free specifically so Azure can win on node-hour billing, which is why the real cost and design battle moves to node pool sizing, availability zones, and Azure CNI IP exhaustion.

kubernetes multi-cluster book

2 — EKS

EKS charges for the control plane yet still leaves CoreDNS, kube-proxy, and the CNI as self-managed add-ons, proving that 'managed Kubernetes' is a spectrum of responsibility rather than a single guarantee.

kubernetes multi-cluster book

3 — GKE

GKE Autopilot bills per-pod resource request rather than per-node, which inverts the usual capacity-planning problem by making the scheduler itself the thing you optimize for cost, not the node pool.

kubernetes multi-cluster book

4 — Cluster API

Cluster API models a whole cluster's lifecycle (bootstrap, upgrade, scale, teardown) as Kubernetes custom resources, turning fleet management into just another reconciliation loop instead of a bespoke provisioning script.

kubernetes multi-cluster book

5 — Federation

KubeFed's decline in favor of GitOps-pushed manifests showed that replicating API objects across clusters is the wrong abstraction — the failure mode isn't the sync mechanism, it's treating clusters as one logical API server.

kubernetes multi-cluster book

6 — Multi-Cluster Networking

Flat pod-to-pod routing across clusters (Submariner, Cilium ClusterMesh) is the easy part; the hard part is keeping service identity and mTLS trust consistent once two clusters' CAs and DNS zones have to agree.

kubernetes multi-cluster book

7 — Multi-Region Architecture

Active-active multi-region Kubernetes trades away a single source of truth for lower latency, so the design question stops being 'how do we replicate' and becomes 'how do we resolve conflicting writes during a partition.'

kubernetes multi-cluster book

8 — Hybrid Kubernetes

Hybrid Kubernetes (Anthos, Azure Arc) only holds together when the control plane's API surface is identical on-prem and in cloud; the moment it diverges, workloads behave differently depending on where they land.

kubernetes multi-cluster book