- Restore --verify-only function in code generation wrappers. ([#123261](https://github.com/kubernetes/kubernetes/pull/123261), [@skitt](https://github.com/skitt)) [SIG API Machinery]
- Sample-apiserver manifest example will have correct RBAC ([#123479](https://github.com/kubernetes/kubernetes/pull/123479), [@Jefftree](https://github.com/Jefftree)) [SIG API Machinery 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._

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

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

- Mark Job onPodConditions as optional in pod failure policy ([#120210](https://github.com/kubernetes/kubernetes/pull/120210), [@mimowo](https://github.com/mimowo)) [SIG API Machinery and Apps]

### Feature

The ambient CNI agent is the only place where ambient network config and pod redirection machinery happens.

	@bin/check_samples.sh
	@testlinter
	@envvarlinter istioctl pilot security

# Allow-list:
# (k8s) Machinery, utils, klog
# (proto) Istio API non-CRDs, MeshConfig and ProxyConfig
# (proto) Envoy TLS proto for SDS
# (proto) Envoy Wasm filters for wasm xDS proxy
# (proto) xDS discovery service for xDS proxy

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).

### 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. 🚨

When referring to the remote machine, it's common to call it **server**, but also **machine**, **VM** (virtual machine), **node**. Those all refer to some type of remote machine, normally running Linux, where you run programs.

## Install the Server Program

When you install FastAPI, it comes with a production server, Uvicorn, and you can start it with the `fastapi run` command.

But you can also install an ASGI server manually:

=== "Uvicorn"