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Kubernetes Components |
concept |
A Kubernetes cluster consists of the components that represent the control plane and a set of machines called nodes.
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When you deploy Kubernetes, you get a cluster. {{< glossary_definition term_id="cluster" length="all" prepend="A Kubernetes cluster consists of">}}
This document outlines the various components you need to have a complete and working Kubernetes cluster.
Here's the diagram of a Kubernetes cluster with all the components tied together.
The control plane's components make global decisions about the cluster (for example, scheduling), as well as detecting and responding to cluster events (for example, starting up a new {{< glossary_tooltip text="pod" term_id="pod">}} when a deployment's replicas field is unsatisfied).
Control plane components can be run on any machine in the cluster. However, for simplicity, set up scripts typically start all control plane components on the same machine, and do not run user containers on this machine. See Creating Highly Available clusters with kubeadm for an example control plane setup that runs across multiple VMs.
{{< glossary_definition term_id="kube-apiserver" length="all" >}}
{{< glossary_definition term_id="etcd" length="all" >}}
{{< glossary_definition term_id="kube-scheduler" length="all" >}}
{{< glossary_definition term_id="kube-controller-manager" length="all" >}}
These controllers include:
- Node controller: Responsible for noticing and responding when nodes go down.
- Replication controller: Responsible for maintaining the correct number of pods for every replication controller object in the system.
- Endpoints controller: Populates the Endpoints object (that is, joins Services & Pods).
- Service Account & Token controllers: Create default accounts and API access tokens for new namespaces.
{{< glossary_definition term_id="cloud-controller-manager" length="short" >}}
The cloud-controller-manager only runs controllers that are specific to your cloud provider. If you are running Kubernetes on your own premises, or in a learning environment inside your own PC, the cluster does not have a cloud controller manager.
As with the kube-controller-manager, the cloud-controller-manager combines several logically independent control loops into a single binary that you run as a single process. You can scale horizontally (run more than one copy) to improve performance or to help tolerate failures.
The following controllers can have cloud provider dependencies:
- Node controller: For checking the cloud provider to determine if a node has been deleted in the cloud after it stops responding
- Route controller: For setting up routes in the underlying cloud infrastructure
- Service controller: For creating, updating and deleting cloud provider load balancers
Node components run on every node, maintaining running pods and providing the Kubernetes runtime environment.
{{< glossary_definition term_id="kubelet" length="all" >}}
{{< glossary_definition term_id="kube-proxy" length="all" >}}
{{< glossary_definition term_id="container-runtime" length="all" >}}
Addons use Kubernetes resources ({{< glossary_tooltip term_id="daemonset" >}},
{{< glossary_tooltip term_id="deployment" >}}, etc)
to implement cluster features. Because these are providing cluster-level features, namespaced resources
for addons belong within the kube-system namespace.
Selected addons are described below; for an extended list of available addons, please see Addons.
While the other addons are not strictly required, all Kubernetes clusters should have cluster DNS, as many examples rely on it.
Cluster DNS is a DNS server, in addition to the other DNS server(s) in your environment, which serves DNS records for Kubernetes services.
Containers started by Kubernetes automatically include this DNS server in their DNS searches.
Dashboard is a general purpose, web-based UI for Kubernetes clusters. It allows users to manage and troubleshoot applications running in the cluster, as well as the cluster itself.
Container Resource Monitoring records generic time-series metrics about containers in a central database, and provides a UI for browsing that data.
A cluster-level logging mechanism is responsible for saving container logs to a central log store with search/browsing interface.
- Learn about Nodes
- Learn about Controllers
- Learn about kube-scheduler
- Read etcd's official documentation