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

FEATURE STATE: Kubernetes v1.32 [beta] (enabled by default: false) Dynamic resource allocation is an API for requesting and sharing resources between pods and containers inside a pod. It is a generalization of the persistent volumes API for generic resources. Typically those resources are devices like GPUs. Third-party resource drivers are responsible for tracking and preparing resources, with allocation of resources handled by Kubernetes via structured parameters (introduced in Kubernetes 1.

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.

FEATURE STATE: Kubernetes v1.27 [beta] System component traces record the latency of and relationships between operations in the cluster. Kubernetes components emit traces using the OpenTelemetry Protocol with the gRPC exporter and can be collected and routed to tracing backends using an OpenTelemetry Collector. Trace Collection Kubernetes components have built-in gRPC exporters for OTLP to export traces, either with an OpenTelemetry Collector, or without an OpenTelemetry Collector. For a complete guide to collecting traces and using the collector, see Getting Started with the OpenTelemetry Collector.

Recommendations for designing and deploying admission webhooks in Kubernetes.

Application logs can help you understand what is happening inside your application. The logs are particularly useful for debugging problems and monitoring cluster activity. Most modern applications have some kind of logging mechanism. Likewise, container engines are designed to support logging. The easiest and most adopted logging method for containerized applications is writing to standard output and standard error streams. However, the native functionality provided by a container engine or runtime is usually not enough for a complete logging solution.

Set up Kubernetes tools on your computer.

This page explains how to enable a package repository for the desired Kubernetes minor release upon upgrading a cluster. This is only needed for users of the community-owned package repositories hosted at pkgs.k8s.io. Unlike the legacy package repositories, the community-owned package repositories are structured in a way that there's a dedicated package repository for each Kubernetes minor version. Note:This guide only covers a part of the Kubernetes upgrade process. Please see the upgrade guide for more information about upgrading Kubernetes clusters.

Before you begin You must use a kubectl version that is within one minor version difference of your cluster. For example, a v1.32 client can communicate with v1.31, v1.32, and v1.33 control planes. Using the latest compatible version of kubectl helps avoid unforeseen issues. Install kubectl on Windows The following methods exist for installing kubectl on Windows: Install kubectl binary on Windows (via direct download or curl) Install on Windows using Chocolatey, Scoop, or winget Install kubectl binary on Windows (via direct download or curl) You have two options for installing kubectl on your Windows device

The dockershim component of Kubernetes allows the use of Docker as a Kubernetes's container runtime. Kubernetes' built-in dockershim component was removed in release v1.24. This page explains how your cluster could be using Docker as a container runtime, provides details on the role that dockershim plays when in use, and shows steps you can take to check whether any workloads could be affected by dockershim removal. Finding if your app has a dependencies on Docker If you are using Docker for building your application containers, you can still run these containers on any container runtime.