Role-based access control (RBAC) is a method of regulating access to computer or network resources based on the roles of individual users within your organization. RBAC authorization uses the rbac.authorization.k8s.io API group to drive authorization decisions, allowing you to dynamically configure policies through the Kubernetes API. To enable RBAC, start the API server with the --authorization-config flag set to a file that includes the RBAC authorizer; for example: apiVersion: apiserver.

This page shows how to configure access to multiple clusters by using configuration files. After your clusters, users, and contexts are defined in one or more configuration files, you can quickly switch between clusters by using the kubectl config use-context command. Note:A file that is used to configure access to a cluster is sometimes called a kubeconfig file. This is a generic way of referring to configuration files. It does not mean that there is a file named kubeconfig.

The Kubernetes model for connecting containers Now that you have a continuously running, replicated application you can expose it on a network. Kubernetes assumes that pods can communicate with other pods, regardless of which host they land on. Kubernetes gives every pod its own cluster-private IP address, so you do not need to explicitly create links between pods or map container ports to host ports. This means that containers within a Pod can all reach each other's ports on localhost, and all pods in a cluster can see each other without NAT.

This page provides an overview of admission controllers. An admission controller is a piece of code that intercepts requests to the Kubernetes API server prior to persistence of the resource, but after the request is authenticated and authorized. Several important features of Kubernetes require an admission controller to be enabled in order to properly support the feature. As a result, a Kubernetes API server that is not properly configured with the right set of admission controllers is an incomplete server that will not support all the features you expect.

FEATURE STATE: Kubernetes v1.30 [stable] This page provides an overview of Validating Admission Policy. What is Validating Admission Policy? Validating admission policies offer a declarative, in-process alternative to validating admission webhooks. Validating admission policies use the Common Expression Language (CEL) to declare the validation rules of a policy. Validation admission policies are highly configurable, enabling policy authors to define policies that can be parameterized and scoped to resources as needed by cluster administrators.

This page provides a step-by-step example of updating configuration within a Pod via a ConfigMap and builds upon the Configure a Pod to Use a ConfigMap task. At the end of this tutorial, you will understand how to change the configuration for a running application. This tutorial uses the alpine and nginx images as examples. Before you begin You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster.

An issue that comes up rather frequently for new installations of Kubernetes is that a Service is not working properly. You've run your Pods through a Deployment (or other workload controller) and created a Service, but you get no response when you try to access it. This document will hopefully help you to figure out what's going wrong. Running commands in a Pod For many steps here you will want to see what a Pod running in the cluster sees.

In Kubernetes, a HorizontalPodAutoscaler automatically updates a workload resource (such as a Deployment or StatefulSet), with the aim of automatically scaling the workload to match demand. Horizontal scaling means that the response to increased load is to deploy more Pods. This is different from vertical scaling, which for Kubernetes would mean assigning more resources (for example: memory or CPU) to the Pods that are already running for the workload.

This page explains how to debug Pods running (or crashing) on a Node. Before you begin Your Pod should already be scheduled and running. If your Pod is not yet running, start with Debugging Pods. For some of the advanced debugging steps you need to know on which Node the Pod is running and have shell access to run commands on that Node. You don't need that access to run the standard debug steps that use kubectl.

A HorizontalPodAutoscaler (HPA for short) automatically updates a workload resource (such as a Deployment or StatefulSet), with the aim of automatically scaling the workload to match demand. Horizontal scaling means that the response to increased load is to deploy more Pods. This is different from vertical scaling, which for Kubernetes would mean assigning more resources (for example: memory or CPU) to the Pods that are already running for the workload.