FEATURE STATE: Kubernetes v1.26 [alpha] Dynamic resource allocation is an API for requesting and sharing resources between pods and containers inside a pod. It is a generalization of the persistent volumes API for generic resources. Third-party resource drivers are responsible for tracking and allocating resources, with additional support provided by Kubernetes via structured parameters (introduced in Kubernetes 1.30). When a driver uses structured parameters, Kubernetes handles scheduling and resource allocation without having to communicate with the driver.

The dockershim component of Kubernetes allows the use of Docker as a Kubernetes's container runtime. Kubernetes' built-in dockershim component was removed in release v1.24. This page explains how your cluster could be using Docker as a container runtime, provides details on the role that dockershim plays when in use, and shows steps you can take to check whether any workloads could be affected by dockershim removal. Finding if your app has a dependencies on Docker If you are using Docker for building your application containers, you can still run these containers on any container runtime.

In Kubernetes, scheduling refers to making sure that Pods are matched to Nodes so that Kubelet can run them. Scheduling overview A scheduler watches for newly created Pods that have no Node assigned. For every Pod that the scheduler discovers, the scheduler becomes responsible for finding the best Node for that Pod to run on. The scheduler reaches this placement decision taking into account the scheduling principles described below.

Kubernetes supports nodes that run Microsoft Windows.

This page explains how to add versioning information to CustomResourceDefinitions, to indicate the stability level of your CustomResourceDefinitions or advance your API to a new version with conversion between API representations. It also describes how to upgrade an object from one version to another. Before you begin You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts.

This page shows how to perform a rolling update on a DaemonSet. Before you begin You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:

Learn how to configure networking for your cluster.

This document shares how to validate IPv4/IPv6 dual-stack enabled Kubernetes clusters. Before you begin Provider support for dual-stack networking (Cloud provider or otherwise must be able to provide Kubernetes nodes with routable IPv4/IPv6 network interfaces) A network plugin that supports dual-stack networking. Dual-stack enabled cluster Your Kubernetes server must be at or later than version v1.23. To check the version, enter kubectl version. Note: While you can validate with an earlier version, the feature is only GA and officially supported since v1.

Every node in a Kubernetes cluster runs a kube-proxy (unless you have deployed your own alternative component in place of kube-proxy). The kube-proxy component is responsible for implementing a virtual IP mechanism for Services of type other than ExternalName. Each instance of kube-proxy watches the Kubernetes control plane for the addition and removal of Service and EndpointSlice objects. For each Service, kube-proxy calls appropriate APIs (depending on the kube-proxy mode) to configure the node to capture traffic to the Service's clusterIP and port, and redirect that traffic to one of the Service's endpoints (usually a Pod, but possibly an arbitrary user-provided IP address).

Synopsis Set the latest last-applied-configuration annotations by setting it to match the contents of a file. This results in the last-applied-configuration being updated as though 'kubectl apply -f<file> ' was run, without updating any other parts of the object. kubectl apply set-last-applied -f FILENAME Examples # Set the last-applied-configuration of a resource to match the contents of a file kubectl apply set-last-applied -f deploy.yaml # Execute set-last-applied against each configuration file in a directory kubectl apply set-last-applied -f path/ # Set the last-applied-configuration of a resource to match the contents of a file; will create the annotation if it does not already exist kubectl apply set-last-applied -f deploy.