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,

- 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]

- Added machine readable output options (JSON & YAML) to `kubectl api-resources`. ([#132604](https://github.com/kubernetes/kubernetes/pull/132604), [@dharmit](https://github.com/dharmit)) [SIG Apps, CLI and Network]

# The RBE machine itself has older kernel mode driver, and it requires
# nvidia driver to be installed.
nvidia-driver-580-open
# TODO(b/445248346): The Docker image shouldn't have cuda-compat installed.
# However, hermetic CUDA forward-compatibility mode is still missing some
# libraries.

- Fixed incorrect "v1 Binding is deprecated in v1.6+" warning in kube-scheduler log. ([#125540](https://github.com/kubernetes/kubernetes/pull/125540), [@pohly](https://github.com/pohly)) [SIG API Machinery]
- Fixed the comment for the Job's managedBy field. ([#124793](https://github.com/kubernetes/kubernetes/pull/124793), [@mimowo](https://github.com/mimowo)) [SIG API Machinery and Apps]

- Kube-apiserver: fixes a 1.27+ regression watching a single namespace via the deprecated /api/v1/watch/namespaces/$name endpoint where watch events were not delivered after the watch was established ([#126150](https://github.com/kubernetes/kubernetes/pull/126150), [@xyz-li](https://github.com/xyz-li)) [SIG API Machinery and Testing]

## Use Case { #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. 🤖

## Caso de uso { #use-case }

Vamos começar com um exemplo de **caso de uso** e então ver como resolvê-lo com isso.

Vamos imaginar que você tem alguns **modelos de machine learning** que deseja usar para lidar com as requisições. 🤖

## Caso de Uso { #use-case }

Empecemos con un ejemplo de **caso de uso** y luego veamos cómo resolverlo con esto.

Imaginemos que tienes algunos **modelos de machine learning** que quieres usar para manejar requests. 🤖

		}
	}

	return host, port, nil
}

// isLocalHost - checks if the given parameter
// correspond to one of the local IP of the
// current machine
func isLocalHost(host string, port string, localPort string) (bool, error) {
	hostIPs, err := getHostIP(host)
	if err != nil {
		return false, err
	}

	nonInterIPV4s := mustGetLocalIP4().Intersection(hostIPs)