What is a Kubernetes cluster?

A Kubernetes cluster is a set of node machines for running containerized applications. If you’re running Kubernetes, you’re running a cluster.

At a minimum, a cluster contains a control plane and one or more compute machines, or nodes. The control plane is responsible for maintaining the desired state of the cluster, such as which applications are running and which container images they use. Nodes actually run the applications and workloads.

The cluster is the heart of Kubernetes’ key advantage: the ability to schedule and run containers across a group of machines, be they physical or virtual, on premises or in the cloud. Kubernetes containers aren’t tied to individual machines. Rather, they’re abstracted across the cluster.


How do you work with a Kubernetes cluster?

A Kubernetes cluster has a desired state, which defines which applications or other workloads should be running, along with which images they use, which resources should be made available for them, and other such configuration details.

A desired state is defined by configuration files made up of manifests, which are JSON or YAML files that declare the type of application to run and how many replicas are required to run a healthy system.

The cluster’s desired state is defined with the Kubernetes API. This can be done from the command line (using kubectl) or by using the API to interact with the cluster to set or modify your desired state.

Kubernetes will automatically manage your cluster to match the desired state. As a simple example, suppose you deploy an application with a desired state of "3," meaning 3 replicas of the application should be running. If 1 of those containers crashes, Kubernetes will see that only 2 replicas are running, so it will add 1 more to satisfy the desired state.

You can also use Kubernetes patterns to manage the scale of your cluster automatically based on load. 


How does a cluster relate to a node, a pod, and other Kubernetes terms?

We’ve defined a cluster as a set of nodes. Let’s look at a few other Kubernetes terms that are helpful to understanding what a cluster does. Control plane: The collection of processes that control Kubernetes nodes. This is where all task assignments originate. Nodes: These machines perform the requested tasks assigned by the control plane. Pod: A set of 1 or more containers deployed to a single node. A pod is the smallest and simplest Kubernetes object. Service: A way to expose an application running on a set of pods as a network service. This decouples work definitions from the pods. Volume: A directory containing data, accessible to the containers in a pod. A Kubernetes volume has the same lifetime as the pod that encloses it. A volume outlives any containers that run within the pod, and data is preserved when a container restarts. Namespace: A virtual cluster. Namespaces allow Kubernetes to manage multiple clusters (for multiple teams or projects) within the same physical cluster.


Why is Kubernetes cluster management important?

Since current Kubernetes environments require management at an individual cluster level, the cost of managing these across an enterprise can quickly increase based on the number of clusters. 


Each cluster has to be individually deployed, upgraded, and configured for security. In addition, if applications need to be deployed across environments, deployment has to be done manually or outside the Kubernetes environment control.


Management of day 2 operations such as patching and upgrading at the individual cluster level is also time-consuming and error prone.


What is Kubernetes cluster management?


Kubernetes cluster management is how an IT team manages a group of Kubernetes clusters. 

With modern cloud-native applications, Kubernetes environments are becoming highly distributed. They can be deployed across multiple datacenters on-premise, in the public cloud, and at the edge.


Organizations that want to use Kubernetes at scale or in production will have multiple clusters, such as for development, testing, and production, distributed across environments and need to be able to manage them effectively.


Benefits of a multi-cluster Kubernetes deployment:

  • Improve application availability

  • Reduce latency

  • Improve disaster recovery

  • Deploy legacy and cloud-native applications across environments

Learn how Kubernetes can help your organization build applications and manage containers on site and across hybrid cloud environments. 

With modern cloud-native applications, Kubernetes environments are becoming highly distributed. They can be deployed across multiple datacenters on-premise, in the public cloud, and at the edge.

Organizations that want to use Kubernetes at scale or in production will have multiple clusters, such as for development, testing, and production, distributed across environments and need to be able to manage them effectively.

Kubernetes cluster management is how an IT team manages a group of Kubernetes clusters.  Learn more about managing Kubernetes clusters


Life cycle management of a Kubernetes cluster includes:

  • Creating a new cluster

  • Removing a cluster

  • Updating the control plane and compute nodes

  • Maintenance and updates to the node

  • Upgrading the Kubernetes API version

  • Securing the cluster

  • Upgrading the cluster, which may also be provider-dependant 

Developers want it to be easy to get access to new clusters as they need them. For operations teams and site reliability engineers (SREs), new clusters need to be configured correctly so that apps will be available in production. Ops and SREs also want to monitor the health of clusters in your environment.


Kubernetes cluster management addresses the common challenges administrators and site reliability engineers face as they work across a range of environments that run Kubernetes clusters.