erasureLockOwner string

	// List of endpoints provided on the command line.
	endpoints PoolEndpoints

	// String version of all the endpoints, an optimization
	// to avoid url.String() conversion taking CPU on
	// large disk setups.
	endpointStrings []string

	// Total number of sets and the number of disks per set.
	setCount, setDriveCount int
	defaultParityCount      int

	poolIndex int

- Fixed a bug in kubelet that will saturate CPU utilization after containerd got restarted. ([#97174](https://github.com/kubernetes/kubernetes/pull/97174), [@hanlins](https://github.com/hanlins)) [SIG Node]

Uvicorn process running your FastAPI application). They would all be **identical containers**, running the same thing, but each with its own process, memory, etc. That way you would take advantage of **parallelization** in **different cores** of the CPU, or even in **different machines**.

And the distributed container system with the **load balancer** would **distribute the requests** to each one of the containers with your app **in turns**. So, each request could be handled by one of the...

	}
}

func getMinIOProcessCPUTime() MetricDescription {
	return MetricDescription{
		Namespace: nodeMetricNamespace,
		Subsystem: processSubsystem,
		Name:      cpu,
		Help:      "Total user and system CPU time spent in seconds",
		Type:      counterMetric,
	}
}

func getMinioProcMetrics() *MetricsGroupV2 {
	mg := &MetricsGroupV2{
		cacheInterval: 10 * time.Second,
	}

		// Run the data scanner in a loop
		for {
			runDataScanner(ctx, objAPI)
			duration := max(time.Duration(r.Float64()*float64(scannerCycle.Load())),
				// Make sure to sleep at least a second to avoid high CPU ticks.
				time.Second)
			time.Sleep(duration)
		}
	}()
}

func getCycleScanMode(currentCycle, bitrotStartCycle uint64, bitrotStartTime time.Time) madmin.HealScanMode {

un proceso Uvicorn ejecutando tu aplicación FastAPI). Todos serían **contenedores idénticos**, ejecutando lo mismo, pero cada uno con su propio proceso, memoria, etc. De esa forma, aprovecharías la **paralelización** en **diferentes núcleos** de la CPU, o incluso en **diferentes máquinas**.

Y el sistema de contenedores distribuido con el **load balancer** **distribuiría las requests** a cada uno de los contenedores **replicados** que ejecutan tu aplicación **en turnos**. Así, cada request...

- Fixes an issue calculating total CPU usage reported for Windows nodes ([#122999](https://github.com/kubernetes/kubernetes/pull/122999), [@marosset](https://github.com/marosset)) [SIG Node and Windows]

* Free up CPU and memory requested but unused by Metrics Server Pod Nanny. ([#57252](https://github.com/kubernetes/kubernetes/pull/57252), [@kawych](https://github.com/kawych))

- Fixed a bug whereby the allocation of reusable CPUs and devices was not being honored when the TopologyManager was enabled ([#93189](https://github.com/kubernetes/kubernetes/pull/93189), [@klueska](https://github.com/klueska)) [SIG Node]

  * There are known bugs that result in errors when querying Kubelet's stats summary API. We expect to fix them in v1.8.1.

#### kubelet

* [alpha] Kubelet now supports alternative container-level CPU affinity policies by using the new CPU manager. ([#375](https://github.com/kubernetes/enhancements/issues/375), [@sjenning](https://github.com/sjenning), [@ConnorDoyle](https://github.com/ConnorDoyle))