- Rename `AllowlistEntry.Name` to `AllowlistEntry.Command` in the credential plugin allowlist ([#137272](https://github.com/kubernetes/kubernetes/pull/137272), [@pmengelbert](https://github.com/pmengelbert)) [SIG API Machinery, Auth, CLI and Testing]

### API Change

- Extended `core/v1` `Toleration` to support numeric comparison operators (`Gt`,`Lt`). ([#134665](https://github.com/kubernetes/kubernetes/pull/134665), [@helayoty](https://github.com/helayoty)) [SIG API Machinery, Apps, Node, Scheduling, Testing and Windows]

- Fixed an issue in register-gen where imports for k8s.io/apimachinery/pkg/runtime and k8s.io/apimachinery/pkg/runtime/schema were missing. ([#130392](https://github.com/kubernetes/kubernetes/pull/130392), [@mrIncompetent](https://github.com/mrIncompetent)) [SIG API Machinery]

Les conteneurs Linux s'exécutent en utilisant le même noyau Linux que l'hôte (machine, machine virtuelle, serveur cloud, etc.). Cela signifie simplement qu'ils sont très légers (comparés à des machines virtuelles complètes émulant un système d'exploitation entier).

Ainsi, les conteneurs consomment **peu de ressources**, une quantité comparable à l'exécution directe des processus (alors qu'une machine virtuelle consommerait beaucoup plus).

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## HTML "dfn" elements { #html-dfn-elements }

* <dfn title="A group of machines that are configured to be connected and work together in some way.">cluster</dfn>
* <dfn title="A method of machine learning that uses artificial neural networks with numerous hidden layers between input and output layers, thereby developing a comprehensive internal structure">Deep Learning</dfn>

Voir la section `### HTML abbr elements` dans l’invite générale dans `scripts/translate.py`.

////

## Éléments HTML « dfn » { #html-dfn-elements }

* <dfn title="Un groupe de machines configurées pour être connectées et travailler ensemble d’une certaine manière.">grappe</dfn>

## Machine serveur et programme serveur { #server-machine-and-server-program }

Il y a un petit détail sur les noms à garder à l'esprit. 💡

Le mot « serveur » est couramment utilisé pour désigner à la fois l'ordinateur distant/cloud (la machine physique ou virtuelle) et également le programme qui s'exécute sur cette machine (par exemple, Uvicorn).

  Remove-Item $zulu_zip; \
  $env:PATH = [Environment]::GetEnvironmentVariable(\"PATH\", \"Machine\") + \";${zulu_root}\\bin\"; \
  [Environment]::SetEnvironmentVariable(\"PATH\", $env:PATH, \"Machine\"); \
  $env:JAVA_HOME = $zulu_root; \
  [Environment]::SetEnvironmentVariable(\"JAVA_HOME\", $env:JAVA_HOME, \"Machine\")

# Point to the LLVM installation.
# The Bazel Windows guide claims it can find LLVM automatically,

Dolayısıyla genel olarak "server" dendiğinde, bu iki şeyden birini kast ediyor olabilir.

Uzak makineden bahsederken genelde **server** denir; ayrıca **machine**, **VM** (virtual machine), **node** ifadeleri de kullanılır. Bunların hepsi, genellikle Linux çalıştıran ve üzerinde programlarınızı çalıştırdığınız bir tür uzak makineyi ifade eder.

## Sunucu Programını Yükleyin { #install-the-server-program }

## Kullanım Senaryosu { #use-case }

Önce bir **kullanım senaryosu** örneğiyle başlayalım, sonra bunu bununla nasıl çözeceğimize bakalım.

Request’leri işlemek için kullanmak istediğiniz bazı **machine learning modelleriniz** olduğunu hayal edelim. 🤖