This page shows how to configure a Key Management Service (KMS) provider and plugin to enable secret data encryption. In Kubernetes 1.34 there are two versions of KMS at-rest encryption. You should use KMS v2 if feasible because KMS v1 is deprecated (since Kubernetes v1.28) and disabled by default (since Kubernetes v1.29). KMS v2 offers significantly better performance characteristics than KMS v1. Caution:This documentation is for the generally available implementation of KMS v2 (and for the deprecated version 1 implementation).

This page shows how to change the access mode on an existing PersistentVolume to use ReadWriteOncePod. 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:

Monitoring kubernetes system components.

FEATURE STATE: Kubernetes v1.34 [stable](enabled by default) This page shows you how to configure dynamic resource allocation (DRA) in a Kubernetes cluster by enabling API groups and configuring classes of devices. These instructions are for cluster administrators. About DRA A Kubernetes feature that lets you request and share resources among Pods. These resources are often attached devices like hardware accelerators. With DRA, device drivers and cluster admins define device classes that are available to claim in workloads.

This page shows how to create an external load balancer. When creating a Service, you have the option of automatically creating a cloud load balancer. This provides an externally-accessible IP address that sends traffic to the correct port on your cluster nodes, provided your cluster runs in a supported environment and is configured with the correct cloud load balancer provider package. You can also use an Ingress in place of Service.

This task demonstrates running multiple Jobs based on a common template. You can use this approach to process batches of work in parallel. For this example there are only three items: apple, banana, and cherry. The sample Jobs process each item by printing a string then pausing. See using Jobs in real workloads to learn about how this pattern fits more realistic use cases. Before you begin You should be familiar with the basic, non-parallel, use of Job.

Node Conformance Test Node conformance test is a containerized test framework that provides a system verification and functionality test for a node. The test validates whether the node meets the minimum requirements for Kubernetes; a node that passes the test is qualified to join a Kubernetes cluster. Node Prerequisite To run node conformance test, a node must satisfy the same prerequisites as a standard Kubernetes node. At a minimum, the node should have the following daemons installed:

The architectural concepts behind Kubernetes.

Before you begin You must use a kubectl version that is within one minor version difference of your cluster. For example, a v1.34 client can communicate with v1.33, v1.34, and v1.35 control planes. Using the latest compatible version of kubectl helps avoid unforeseen issues. Install kubectl on macOS The following methods exist for installing kubectl on macOS: Install kubectl on macOS Install kubectl binary with curl on macOS Install with Homebrew on macOS Install with Macports on macOS Verify kubectl configuration Optional kubectl configurations and plugins Enable shell autocompletion Install kubectl convert plugin Install kubectl binary with curl on macOS Download the latest release:

This page guides you through configuring Node overprovisioning in your Kubernetes cluster. Node overprovisioning is a strategy that proactively reserves a portion of your cluster's compute resources. This reservation helps reduce the time required to schedule new pods during scaling events, enhancing your cluster's responsiveness to sudden spikes in traffic or workload demands. By maintaining some unused capacity, you ensure that resources are immediately available when new pods are created, preventing them from entering a pending state while the cluster scales up.