Linux containers run using the same Linux kernel of the host (machine, virtual machine, cloud server, etc). This just means that they are very lightweight (compared to full virtual machines emulating an entire operating system).

This way, containers consume **little resources**, an amount comparable to running the processes directly (a virtual machine would consume much more).

                                    + now
                                    + ", lastUpdated = " + lastUpdated + "). Please verify that the clocks of all"
                                    + " deploying machines are reasonably synchronized.");
                    versioning.setLastUpdated(now);
                    changed = true;
                }
            }
        }

        if (changed) {

### Server Memory

For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**.

And if your remote server or virtual machine only has 3 GB of RAM, trying to load more than 4 GB of RAM will cause problems. 🚨

🍵 ⚙️ 📦, ⚒ 🈸 🏃 🔛 🕴 & ⏮️ ⏏ 💪 ⚠ & ⚠. ✋️ 🕐❔ **👷 ⏮️ 📦** 🌅 💼 👈 🛠️ 🔌 🔢. 👶

## 🧬 - 🔢 🛠️

🚥 👆 ✔️ <abbr title="A group of machines that are configured to be connected and work together in some way.">🌑</abbr> 🎰 ⏮️ **☁**, ☁ 🐝 📳, 🖖, ⚖️ ➕1️⃣ 🎏 🏗 ⚙️ 🛠️ 📎 📦 🔛 💗 🎰, ⤴️ 👆 🔜 🎲 💚 **🍵 🧬** **🌑 🎚** ↩️ ⚙️ **🛠️ 👨‍💼** (💖 🐁 ⏮️ 👨‍🏭) 🔠 📦.

컨테이너를 사용하지 않고서는, 어플리케이션을 구동하고 재시작하는 것이 매우 번거롭고 어려울 수 있습니다. 하지만 **컨테이너를 사용한다면** 대부분의 경우에 이런 기능은 기본적으로 포함되어 있습니다. ✨

## 복제 - 프로세스 개수

만약 여러분이 **쿠버네티스**와 머신 <abbr title="A group of machines that are configured to be connected and work together in some way.">클러스터</abbr>, 도커 스왐 모드, 노마드, 또는 다른 여러 머신 위에 분산 컨테이너를 관리하는 복잡한 시스템을 다루고 있다면, 여러분은 각 컨테이너에서 (워커와 함께 사용하는 Gunicorn 같은) **프로세스 매니저** 대신 **클러스터 레벨**에서 **복제를 다루**고 싶을 것입니다.

- Kube-apiserver now reports metrics for authorization decisions in the `apiserver_authorization_decisions_total` metric, labeled by authorizer type, name, and decision. ([#123333](https://github.com/kubernetes/kubernetes/pull/123333), [@liggitt](https://github.com/liggitt)) [SIG API Machinery, Auth and Testing]

### Other (Cleanup or Flake)

- Build etcd image v3.5.12 ([#123069](https://github.com/kubernetes/kubernetes/pull/123069), [@bzsuni](https://github.com/bzsuni)) [SIG API Machinery and Etcd]

## Dependencies

### Added
_Nothing has changed._

* **Machine Learning**: normalmente requiere muchas multiplicaciones de "matrices" y "vectores". Imagina en una enorme hoja de cálculo con números y tener que multiplicarlos todos al mismo tiempo.

## Use Case

Let's start with an example **use case** and then see how to solve it with this.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

- Restore --verify-only function in code generation wrappers. ([#123261](https://github.com/kubernetes/kubernetes/pull/123261), [@skitt](https://github.com/skitt)) [SIG API Machinery]