The status of a node in Kubernetes is a critical aspect of managing a Kubernetes cluster. In this article, we'll cover the basics of monitoring and maintaining node status to ensure a healthy and stable cluster. Node status fields A Node's status contains the following information: Addresses Conditions Capacity and Allocatable Info You can use kubectl to view a Node's status and other details: kubectl describe node <insert-node-name-here> Each section of the output is described below.

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.

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.

By default, containers run with unbounded compute resources on a Kubernetes cluster. Using Kubernetes resource quotas, administrators (also termed cluster operators) can restrict consumption and creation of cluster resources (such as CPU time, memory, and persistent storage) within a specified namespace. Within a namespace, a Pod can consume as much CPU and memory as is allowed by the ResourceQuotas that apply to that namespace. As a cluster operator, or as a namespace-level administrator, you might also be concerned about making sure that a single object cannot monopolize all available resources within a namespace.

FEATURE STATE: Kubernetes v1.14 [stable] Pods can have priority. Priority indicates the importance of a Pod relative to other Pods. If a Pod cannot be scheduled, the scheduler tries to preempt (evict) lower priority Pods to make scheduling of the pending Pod possible. Warning:In a cluster where not all users are trusted, a malicious user could create Pods at the highest possible priorities, causing other Pods to be evicted/not get scheduled.

This page shows how to configure liveness, readiness and startup probes for containers. For more information about probes, see Liveness, Readiness and Startup Probes The kubelet uses liveness probes to know when to restart a container. For example, liveness probes could catch a deadlock, where an application is running, but unable to make progress. Restarting a container in such a state can help to make the application more available despite bugs.

Set up monitoring and logging to troubleshoot a cluster, or debug a containerized application.

This page shows how to configure a Pod to use a Volume for storage. A Container's file system lives only as long as the Container does. So when a Container terminates and restarts, filesystem changes are lost. For more consistent storage that is independent of the Container, you can use a Volume. This is especially important for stateful applications, such as key-value stores (such as Redis) and databases. Before you begin You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster.

This page shows how to use a projected Volume to mount several existing volume sources into the same directory. Currently, secret, configMap, downwardAPI, and serviceAccountToken volumes can be projected. Note:serviceAccountToken is not a volume type. 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 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.