A Kubernetes cluster is the full Kubernetes environment: a control plane that stores desired state and makes scheduling decisions, plus a group of worker nodes that run your pods. You send desired state to the API server, and the cluster works continuously to make reality match it.
Why it matters
The cluster is the boundary within which workloads share networking, scheduling and access control. Teams decide how many clusters to run: one per environment, one per team, or one per region. More clusters improve isolation and limit the blast radius of mistakes, but add operating cost. Managed services such as EKS, AKS and GKE run the control plane for you, so you mainly manage nodes and workloads.
Example
Typical components:
Control plane: API server, etcd, scheduler, controller manager
Worker nodes: kubelet, container runtime, kube-proxy
Workloads: pods grouped by namespaces (prod, staging)Namespaces divide one cluster logically, but they are not a hard security boundary on their own.
Common mistakes
- Putting production and experiments in the same namespace with shared permissions.
- Running a single-node control plane for a service that must stay available.
- Not backing up etcd or the manifests that rebuild the cluster.
- Leaving the API server exposed to the whole internet.
Related
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