A container image represents binary data that encapsulates an application and all its software dependencies. Container images are executable software bundles that can run standalone and that make very well-defined assumptions about their runtime environment. You typically create a container image of your application and push it to a registry before referring to it in a Pod. This page provides an outline of the container image concept. Note:If you are looking for the container images for a Kubernetes release (such as v1.

Technology for packaging an application along with its runtime dependencies.

Kubernetes supports nodes that run Microsoft Windows.

In the scheduling-plugin NodeResourcesFit of kube-scheduler, there are two scoring strategies that support the bin packing of resources: MostAllocated and RequestedToCapacityRatio. Enabling bin packing using MostAllocated strategy The MostAllocated strategy scores the nodes based on the utilization of resources, favoring the ones with higher allocation. For each resource type, you can set a weight to modify its influence in the node score. To set the MostAllocated strategy for the NodeResourcesFit plugin, use a scheduler configuration similar to the following:

kube-state-metrics, an add-on agent to generate and expose cluster-level metrics.

Set up Kubernetes tools on your computer.

FEATURE STATE: Kubernetes v1.34 [stable](enabled by default) This page describes dynamic resource allocation (DRA) in Kubernetes. About DRA DRA is a Kubernetes feature that lets you request and share resources among Pods. These resources are often attached devices like hardware accelerators. With DRA, device drivers and cluster admins define device classes that are available to claim in workloads. Kubernetes allocates matching devices to specific claims and places the corresponding Pods on nodes that can access the allocated devices.

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.

Many applications rely on configuration which is used during either application initialization or runtime. Most times, there is a requirement to adjust values assigned to configuration parameters. ConfigMaps are a Kubernetes mechanism that let you inject configuration data into application pods. The ConfigMap concept allow you to decouple configuration artifacts from image content to keep containerized applications portable. For example, you can download and run the same container image to spin up containers for the purposes of local development, system test, or running a live end-user workload.

Before you begin Some steps in this page use the jq tool. If you don't have jq, you can install it via your operating system's software sources, or fetch it from https://jqlang.github.io/jq/. Some steps also involve installing curl, which can be installed via your operating system's software sources. A subset of the kubelet's configuration parameters may be set via an on-disk config file, as a substitute for command-line flags. Providing parameters via a config file is the recommended approach because it simplifies node deployment and configuration management.