Skip to main content Back to top Ctrl + K Choose version GitHub Index Symbols | _ | A | B | C | D | E | F | G | H | I...

This page shows how to view, work in, and delete namespaces. The page also shows how to use Kubernetes namespaces to subdivide your cluster. Before you begin Have an existing Kubernetes cluster. You have a basic understanding of Kubernetes Pods, Services, and Deployments. Viewing namespaces List the current namespaces in a cluster using: kubectl get namespaces NAME STATUS AGE default Active 11d kube-node-lease Active 11d kube-public Active 11d kube-system Active 11d Kubernetes starts with four initial namespaces:

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.

Kubernetes provides a certificates.k8s.io API, which lets you provision TLS certificates signed by a Certificate Authority (CA) that you control. These CA and certificates can be used by your workloads to establish trust. certificates.k8s.io API uses a protocol that is similar to the ACME draft. Note:Certificates created using the certificates.k8s.io API are signed by a dedicated CA. It is possible to configure your cluster to use the cluster root CA for this purpose, but you should never rely on this.

In this example, you will run a Kubernetes Job that runs multiple parallel tasks as worker processes, each running as a separate Pod. In this example, as each pod is created, it picks up one unit of work from a task queue, processes it, and repeats until the end of the queue is reached. Here is an overview of the steps in this example: Start a storage service to hold the work queue.

Creating Secret objects using resource configuration file.

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.

Resource Types CloudControllerManagerConfiguration LeaderMigrationConfiguration KubeControllerManagerConfiguration ClientConnectionConfiguration Appears in: KubeSchedulerConfiguration GenericControllerManagerConfiguration ClientConnectionConfiguration contains details for constructing a client. FieldDescription kubeconfig [Required] string kubeconfig is the path to a KubeConfig file. acceptContentTypes [Required] string acceptContentTypes defines the Accept header sent by clients when connecting to a server, overriding the default value of 'application/json'. This field will control all connections to the server used by a particular client. contentType [Required] string contentType is the content type used when sending data to the server from this client.

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.