Node-pressure eviction is the process by which the kubelet proactively terminates pods to reclaim resource on nodes. The kubelet monitors resources like memory, disk space, and filesystem inodes on your cluster's nodes. When one or more of these resources reach specific consumption levels, the kubelet can proactively fail one or more pods on the node to reclaim resources and prevent starvation. During a node-pressure eviction, the kubelet sets the phase for the selected pods to Failed, and terminates the Pod.

In Kubernetes, scheduling refers to making sure that Pods are matched to Nodes so that Kubelet can run them. Scheduling overview A scheduler watches for newly created Pods that have no Node assigned. For every Pod that the scheduler discovers, the scheduler becomes responsible for finding the best Node for that Pod to run on. The scheduler reaches this placement decision taking into account the scheduling principles described below.

A time-to-live mechanism to clean up old Jobs that have finished execution.

Each object in your cluster has a Name that is unique for that type of resource. Every Kubernetes object also has a UID that is unique across your whole cluster. For example, you can only have one Pod named myapp-1234 within the same namespace, but you can have one Pod and one Deployment that are each named myapp-1234. For non-unique user-provided attributes, Kubernetes provides labels and annotations. Names A client-provided string that refers to an object in a resource URL, such as /api/v1/pods/some-name.

This document highlights and consolidates configuration best practices that are introduced throughout the user guide, Getting Started documentation, and examples. This is a living document. If you think of something that is not on this list but might be useful to others, please don't hesitate to file an issue or submit a PR. General Configuration Tips When defining configurations, specify the latest stable API version. Configuration files should be stored in version control before being pushed to the cluster.

With autoscaling, you can automatically update your workloads in one way or another. This allows your cluster to react to changes in resource demand more elastically and efficiently.

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:

Finalizers are namespaced keys that tell Kubernetes to wait until specific conditions are met before it fully deletes resources that are marked for deletion. Finalizers alert controllers to clean up resources the deleted object owned. When you tell Kubernetes to delete an object that has finalizers specified for it, the Kubernetes API marks the object for deletion by populating .metadata.deletionTimestamp, and returns a 202 status code (HTTP "Accepted"). The target object remains in a terminating state while the control plane, or other components, take the actions defined by the finalizers.

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.

A detailed look at the different policy levels defined in the Pod Security Standards.