# Number of threads for hot thread monitoring.
crawler.hotthread.threads=3
# Timeout for hot thread monitoring (e.g., 30s).
crawler.hotthread.timeout=30s
# Type of hot thread monitoring (e.g., cpu).
crawler.hotthread.type=cpu
# Metadata fields to exclude from document content.
crawler.metadata.content.excludes=resourceName,X-Parsed-By,Content-Encoding.*,Content-Type.*,X-TIKA.*,X-FESS.*
# Mapping for document metadata names.

обычно имеет **только один процесс** (например, процесс Uvicorn с вашим приложением FastAPI). Все они — **одинаковые контейнеры**, запускающие одно и то же, но у каждого свой процесс, память и т.п. Так вы используете **параллелизм** по **разным ядрам** CPU или даже **разным машинам**.

Система распределённых контейнеров с **балансировщиком нагрузки** будет **распределять запросы** между контейнерами с вашим приложением **по очереди**. То есть каждый запрос может обрабатываться одним из нескольких...

- Added support for `--cpu`, `--memory` flag to `kubectl autoscale`, started deprecating `--cpu-precent`. ([#129373](https://github.com/kubernetes/kubernetes/pull/129373), [@googs1025](https://github.com/googs1025))

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 con tu aplicación **en turnos**. Así, cada request podría ser manejada por...

* Fix the DOCKER_OPTS appending bug. ([#33163](https://github.com/kubernetes/kubernetes/pull/33163), [@DjangoPeng](https://github.com/DjangoPeng))
* Remove cpu limits for dns pod to avoid CPU starvation ([#33227](https://github.com/kubernetes/kubernetes/pull/33227), [@vishh](https://github.com/vishh))

</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

	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

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...

- 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]

  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteGraph(graph);
  TF_DeleteStatus(s);
}

// If `device` is non-empty, run Min op on that device.
// Otherwise run it on the default device (CPU).
void RunMinTest(const string& device, bool use_XLA) {
  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Make a placeholder operation.
  TF_Operation* feed = Placeholder(graph, s);