| Path                        | Description                                        |
|-----------------------------|----------------------------------------------------|
| `/system/cpu`               | Metrics about CPUs on the system.                  |
| `/system/drive`             | Metrics about drives on the system.                |
| `/system/network/internode` | Metrics about internode requests made by the node. |

///

## Utilização de recursos

Seu(s) servidor(es) é(são) um **recurso** que você pode consumir ou **utilizar**, com seus programas, o tempo de computação nas CPUs e a memória RAM disponível.

Quanto dos recursos do sistema você quer consumir/utilizar? Pode ser fácil pensar "não muito", mas, na realidade, você provavelmente vai querer consumir **o máximo possível sem travar**.

- When the kubelet fails to assign CPUs to a Pod because there less available CPUs than the Pod requests, the error message changed from

	return resp.ValueOrZero(), err
}

// GetCPUs - fetch CPU information for a remote node.
func (client *peerRESTClient) GetCPUs(ctx context.Context) (info madmin.CPUs, err error) {
	resp, err := getCPUsHandler.Call(ctx, client.gridConn(), grid.NewMSS())
	return resp.ValueOrZero(), err
}

// GetNetInfo - fetch network information for a remote node.

- A new kubelet command line option, `--reserved-cpus`, is introduced to explicitly define the CPU list that will be reserved for system. For example, if `--reserved-cpus=0,1,2,3` is specified, then cpu 0,1,2,3 will be reserved for the system.  On a system with 24 CPUs, the user may specify `isolcpus=4-23` for the kernel option and use CPU 4-23 for the user containers. ([#83592](https://github.com/kubernet...

</p>

<p>
Note that the prohibition on introducing data races
does not apply if the compiler can prove that the races
do not affect correct execution on the target platform.
For example, on essentially all CPUs, it is valid to rewrite
</p>

<pre>
n := 0
for i := 0; i < m; i++ {
	n += *shared
}
</pre>

into:

<pre>
n := 0
local := *shared
for i := 0; i < m; i++ {
	n += local

    *   **Linux x86 packages:**
        *   oneDNN optimizations are *enabled by default* on CPUs with
            neural-network-focused hardware features such as AVX512_VNNI,
            AVX512_BF16, AMX, etc.
            ([Intel Cascade Lake](https://www.intel.com/content/www/us/en/products/platforms/details/cascade-lake.html)
            and newer CPUs.)

# gRPC on MacOS requires this #define
build:macos --copt=-DGRPC_BAZEL_BUILD

# Avoid hitting command line argument limit
build:macos --features=archive_param_file

# Settings for MacOS on ARM CPUs.
build:macos_arm64 --cpu=darwin_arm64
build:macos_arm64 --macos_minimum_os=11.0

# iOS configs for each architecture and the fat binary builds.
build:ios --apple_platform_type=ios

- Add a new `distribute-cpus-across-numa` option to the static `CPUManager` policy. When enabled, this will trigger the `CPUManager` to evenly distribute CPUs across NUMA nodes in cases where more than one NUMA node is required to satisfy the allocation. ([#105631](https://github.com/kubernetes/kubernetes/pull/105631), [@klueska](https://github.com/klueska))...

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