This page shows how to use kubectl port-forward to connect to a MongoDB server running in a Kubernetes cluster. This type of connection can be useful for database debugging. 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.

Specify configuration and other data for the Pods that run your workload.

kubeadm upgrade is a user-friendly command that wraps complex upgrading logic behind one command, with support for both planning an upgrade and actually performing it. kubeadm upgrade guidance The steps for performing an upgrade using kubeadm are outlined in this document. For older versions of kubeadm, please refer to older documentation sets of the Kubernetes website. You can use kubeadm upgrade diff to see the changes that would be applied to static pod manifests.

This command initializes a Kubernetes worker node and joins it to the cluster. Run this on any machine you wish to join an existing cluster Synopsis When joining a kubeadm initialized cluster, we need to establish bidirectional trust. This is split into discovery (having the Node trust the Kubernetes Control Plane) and TLS bootstrap (having the Kubernetes Control Plane trust the Node). There are 2 main schemes for discovery. The first is to use a shared token along with the IP address of the API server.

kubeadm join phase enables you to invoke atomic steps of the join process. Hence, you can let kubeadm do some of the work and you can fill in the gaps if you wish to apply customization. kubeadm join phase is consistent with the kubeadm join workflow, and behind the scene both use the same code. kubeadm join phase phase Use this command to invoke single phase of the join workflow

Synopsis Update the annotations on one or more resources. All Kubernetes objects support the ability to store additional data with the object as annotations. Annotations are key/value pairs that can be larger than labels and include arbitrary string values such as structured JSON. Tools and system extensions may use annotations to store their own data. Attempting to set an annotation that already exists will fail unless --overwrite is set. If --resource-version is specified and does not match the current resource version on the server the command will fail.

Synopsis Experimental: Wait for a specific condition on one or many resources. The command takes multiple resources and waits until the specified condition is seen in the Status field of every given resource. Alternatively, the command can wait for the given set of resources to be deleted by providing the "delete" keyword as the value to the --for flag. A successful message will be printed to stdout indicating when the specified condition has been met.

This page contains an overview of the various feature gates an administrator can specify on different Kubernetes components. See feature stages for an explanation of the stages for a feature. Overview Feature gates are a set of key=value pairs that describe Kubernetes features. You can turn these features on or off using the --feature-gates command line flag on each Kubernetes component. Each Kubernetes component lets you enable or disable a set of feature gates that are relevant to that component.

Synopsis Mark the provided resource as paused. Paused resources will not be reconciled by a controller. Use "kubectl rollout resume" to resume a paused resource. Currently only deployments support being paused. kubectl rollout pause RESOURCE Examples # Mark the nginx deployment as paused # Any current state of the deployment will continue its function; new updates # to the deployment will not have an effect as long as the deployment is paused kubectl rollout pause deployment/nginx Options --allow-missing-template-keys     Default: true If true, ignore any errors in templates when a field or map key is missing in the template.

You can use topology spread constraints to control how Pods are spread across your cluster among failure-domains such as regions, zones, nodes, and other user-defined topology domains. This can help to achieve high availability as well as efficient resource utilization. You can set cluster-level constraints as a default, or configure topology spread constraints for individual workloads. Motivation Imagine that you have a cluster of up to twenty nodes, and you want to run a workload that automatically scales how many replicas it uses.