den **verfügbaren Maschinen** zu replizieren, wobei die von diesen benötigte Speichermenge und die auf den Maschinen im Cluster verfügbare Menge berücksichtigt werden.

Wenn Ihre Anwendung **einfach** ist, wird dies wahrscheinlich **kein Problem darstellen** und Sie müssen möglicherweise keine festen Speichergrenzen angeben. Wenn Sie jedoch **viel Speicher verbrauchen** (z. B. bei **Modellen für maschinelles Lernen**), sollten Sie überprüfen, wie viel Speicher Sie verbrauchen, und die **Anzahl...

		// considered as Delete marker true to avoid listing such objects by
		// regular ListObjects() calls. However for delete replication this
		// ends up being a problem because "upon" a successful delete this
		// ends up creating a new delete marker that is spurious and unnecessary.
		//
		// Regression introduced by #14555 was reintroduced in #15564
		if versionFound {

- Terminated Pods on a node will not be re-admitted on kubelet restart. This fixes the problem of Completed Pods awaiting for the finalizer marked as Failed after the kubelet restart. ([#127207](https://github.com/kubernetes/kubernetes/pull/127207), [@SergeyKanzhelev](https://github.com/SergeyKanzhelev)) [SIG Node and Testing]

Néanmoins, si vous utilisez simplement `pip` directement, les packages seraient installés dans votre environnement Python global (l’installation globale de Python).

### Le problème { #the-problem }

Alors, quel est le problème d’installer des packages dans l’environnement Python global ?

		// call will report top level prefixes in deleted state, whereas spark/hadoop interpret this as non-empty
		// and throw a 404 exception. This is especially a problem for spark jobs overwriting the same partition
		// repeatedly. This workaround recursively lists the top 3 entries including delete markers to reflect the
		// correct state of the directory in the list results.

Тем не менее, если просто использовать `pip` напрямую, пакеты будут установлены в **глобальное окружение Python** (глобально установленный Python).

### Проблема { #the-problem }

Так в чём проблема установки пакетов в глобальное окружение Python?

Sin embargo, si solo usas `pip` directamente, los paquetes se instalarían en tu **entorno global de Python** (la instalación global de Python).

### El Problema { #the-problem }

Entonces, ¿cuál es el problema de instalar paquetes en el entorno global de Python?

* Fixed parsing of fsType in AWS StorageClass parameters ([#75944](https://github.com/kubernetes/kubernetes/pull/75944), [@jsafrane](https://github.com/jsafrane))
* Node-Problem-Detector configuration is now decoupled from the Kubernetes release on GKE/GCE. ([#73288](https://github.com/kubernetes/kubernetes/pull/73288), [@wangzhen127](https://github.com/wangzhen127))

- Revised the logic for DaemonSet rolling update to exclude nodes if scheduling constraints are not met.
  This eliminates the problem of rolling updates to a DaemonSet getting stuck around tolerations. ([#120792](https://github.com/kubernetes/kubernetes/pull/120792), [@mochizuki875](https://github.com/mochizuki875)) [SIG Apps and Testing]

No entanto, se você usar `pip` diretamente, os pacotes serão instalados no seu **ambiente Python global** (a instalação global do Python).

### O Problema { #the-problem }

Então, qual é o problema em instalar pacotes no ambiente global do Python?