Kubernetes Control Plane and Data Plane Concepts
Internal
Cluster
A Kubernetes cluster consists of a set of nodes. Of those, a small number are master nodes, which are collectively known as the control plane, and a potentially relatively larger number of worker nodes, which run the cluster's workload.
Node
A node is a Linux host that can run as a VM, a bare-metal device or an instance in a private or public cloud. A node can be a master or worker. In most cases, the term "node" means worker node.
kubelet
Each node runs an agent called kubelet, which is responsible with the node's registration with the cluster. Once a node is registered, its CPU, RAM and storage are pooled into the wider cluster pools of corresponding resources. The kubelet is watching the API server for work (pod) assignments and attempts to run them. If it is not successful for any reason, it reports the condition back to the API server. The task of actually running the pods is delegated to the local container runtime.
Container Runtime
Node Controller
The controller manager includes a node controller.
Control Plane
The control plane is the cluster's set of master nodes. The control plane exposes the API via the API Server and contains the cluster store, controller manager, scheduler and other management components. The control plane makes workload scheduling decisions, performs monitoring and responds to external and internal events.
Master Node
A master node is a collection of system services that manage the Kubernetes cluster. The master nodes are sometimes called heads or head nodes, and most often simply masters. Collectively, they represent the control plane. While it is possible to execute user workloads on the master node, this is generally not recommended. This approach frees up the master nodes' resources to be exclusively used for cluster management activities.
HA Master Nodes
The recommended configuration includes 3 or 5 replicated masters.
Control Plane System Services
API Server
The API server is the control plane front-end service. All components (internal system components and external user components) communicate exclusively via the API Server and use the same API. The most common operation is to POST a manifest as part of a REST API invocation - once the invocation is authenticated and authorized, the manifest content is validated, then persisted into the cluster store and various controllers kick in to insure that the cluster state matches the desired state expressed in the manifest.
Cluster Store
The cluster store is the service that persistently stores the entire configuration and state of the cluster. The cluster store is the only stateful part of the control plane, and the single source of truth for the cluster. The current implementation is based on etcd. Productions deployments run in a HA configuration, with 3 - 5 replicas. etcd prefers consistence over availability, and it will halt updates to the cluster in split brain situations to maintain consistency. However, if etcd becomes unavailable, the applications running on the cluster will continue to work.
Controller Manager
The controller manager implements multiple specialized and independent control loops that monitor the state of the cluster and respond to events, insured that the current state of the cluster matches the desired state, as declared to the API server, thus implementing the declarative approach to operations. The controller manager is shipped as a monolithic binary. The controller manager is a "controller of controllers", including a node controller, an endpoints controller, a replicaset controller, etc.
The logic implemented by each control loop consists of obtaining the desired state, observing the current state, determining differences and, if differences exist, reconciling differences. The terms "control loop" are used interchangeably with "watch loop" and "reconciliation loop".
Scheduler
The scheduler is a system service whose job is to distribute pods to nodes for execution. An individual pod can be scheduled on one node and one node only, and the target node is chosen by the scheduler as result of the evaluation of a set of predicates (affinity and anti-affinity rules, resource availability, etc.), followed by ranking according to criteria such as whether the node has the image or not, how many pods are already running, etc. The highest ranking node is chosen to run the pod. If the scheduler cannot find a suitable node, the pod goes into a "Pending" state.
Cloud Controller Manager
The cloud controller manager is a system service that manages integration with the underlying cloud technology and services such as storage and load balancers. It is only present if Kubernetes runs on a cloud like AWS, Azure or GCP.
Data Plane
The data plane is the cluster's set of worker nodes.
Worker Node
A worker node, most often referred simply as "node" (as opposite to master), is where the application services run. Collectively, the worker nodes make up the data plane. A worker node constantly watches for new work assignments.