When several users or teams share a cluster with a fixed number of nodes, there is a concern that one team could use more than its fair share of resources. Resource quotas are a tool for administrators to address this concern. A resource quota, defined by a ResourceQuota object, provides constraints that limit aggregate resource consumption per namespace. A ResourceQuota can also limit the quantity of objects that can be created in a namespace by API kind, as well as the total amount of infrastructure resources that may be consumed by API objects found in that namespace.

Device plugins let you configure your cluster with support for devices or resources that require vendor-specific setup, such as GPUs, NICs, FPGAs, or non-volatile main memory.

Kubernetes volumes provide a way for containers in a pod to access and share data via the filesystem. There are different kinds of volume that you can use for different purposes, such as: populating a configuration file based on a ConfigMap or a Secret providing some temporary scratch space for a pod sharing a filesystem between two different containers in the same pod sharing a filesystem between two different pods (even if those Pods run on different nodes) durably storing data so that it stays available even if the Pod restarts or is replaced passing configuration information to an app running in a container, based on details of the Pod the container is in (for example: telling a sidecar container what namespace the Pod is running in) providing read-only access to data in a different container image Data sharing can be between different local processes within a container, or between different containers, or between Pods.

Define a range of valid memory resource limits for a namespace, so that every new Pod in that namespace falls within the range you configure.

Node affinity is a property of Pods that attracts them to a set of nodes (either as a preference or a hard requirement). Taints are the opposite -- they allow a node to repel a set of pods. Tolerations are applied to pods. Tolerations allow the scheduler to schedule pods with matching taints. Tolerations allow scheduling but don't guarantee scheduling: the scheduler also evaluates other parameters as part of its function.

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.

Resource Types DefaultPreemptionArgs DynamicResourcesArgs InterPodAffinityArgs KubeSchedulerConfiguration NodeAffinityArgs NodeResourcesBalancedAllocationArgs NodeResourcesFitArgs PodTopologySpreadArgs VolumeBindingArgs ClientConnectionConfiguration Appears in: KubeSchedulerConfiguration 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.

This guide shows you how to create, edit and share diagrams using the Mermaid JavaScript library. Mermaid.js allows you to generate diagrams using a simple markdown-like syntax inside Markdown files. You can also use Mermaid to generate .svg or .png image files that you can add to your documentation. The target audience for this guide is anybody wishing to learn about Mermaid and/or how to create and add diagrams to Kubernetes documentation.

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.

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.