Using kubeadm, you can create a minimum viable Kubernetes cluster that conforms to best practices. In fact, you can use kubeadm to set up a cluster that will pass the Kubernetes Conformance tests. kubeadm also supports other cluster lifecycle functions, such as bootstrap tokens and cluster upgrades. The kubeadm tool is good if you need: A simple way for you to try out Kubernetes, possibly for the first time. A way for existing users to automate setting up a cluster and test their application.

A ConfigMap is an API object used to store non-confidential data in key-value pairs. Pods can consume ConfigMaps as environment variables, command-line arguments, or as configuration files in a volume. A ConfigMap allows you to decouple environment-specific configuration from your container images, so that your applications are easily portable. Caution:ConfigMap does not provide secrecy or encryption. If the data you want to store are confidential, use a Secret rather than a ConfigMap, or use additional (third party) tools to keep your data private.

Labels are key/value pairs that are attached to objects such as Pods. Labels are intended to be used to specify identifying attributes of objects that are meaningful and relevant to users, but do not directly imply semantics to the core system. Labels can be used to organize and to select subsets of objects. Labels can be attached to objects at creation time and subsequently added and modified at any time.

FEATURE STATE: Kubernetes v1.20 [stable] This page describes the RuntimeClass resource and runtime selection mechanism. RuntimeClass is a feature for selecting the container runtime configuration. The container runtime configuration is used to run a Pod's containers. Motivation You can set a different RuntimeClass between different Pods to provide a balance of performance versus security. For example, if part of your workload deserves a high level of information security assurance, you might choose to schedule those Pods so that they run in a container runtime that uses hardware virtualization.

FEATURE STATE: Kubernetes v1.24 [stable] When you run a Pod on a Node, the Pod itself takes an amount of system resources. These resources are additional to the resources needed to run the container(s) inside the Pod. In Kubernetes, Pod Overhead is a way to account for the resources consumed by the Pod infrastructure on top of the container requests & limits. In Kubernetes, the Pod's overhead is set at admission time according to the overhead associated with the Pod's RuntimeClass.

Storage capacity is limited and may vary depending on the node on which a pod runs: network-attached storage might not be accessible by all nodes, or storage is local to a node to begin with. FEATURE STATE: Kubernetes v1.24 [stable] This page describes how Kubernetes keeps track of storage capacity and how the scheduler uses that information to schedule Pods onto nodes that have access to enough storage capacity for the remaining missing volumes.

In order to support latency-critical and high-throughput workloads, Kubernetes offers a suite of Resource Managers. The managers aim to co-ordinate and optimise node's resources alignment for pods configured with a specific requirement for CPUs, devices, and memory (hugepages) resources. The main manager, the Topology Manager, is a Kubelet component that co-ordinates the overall resource management process through its policy. The configuration of individual managers is elaborated in dedicated documents:

FastAPI framework, high performance, easy to learn, fast to code, ready for production

FastAPI framework, high performance, easy to learn, fast to code, ready for production

FastAPI framework, high performance, easy to learn, fast to code, ready for production