}
}

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,
	}

          "interval": "",
          "legendFormat": "{{server}}",
          "range": true,
          "refId": "A"
        }
      ],
      "title": "CPU Usage",
      "type": "gauge"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },

pkg debug/elf, method (R_RISCV) GoString() string
pkg debug/elf, method (R_RISCV) String() string
pkg debug/elf, type R_RISCV int
pkg debug/macho, const CpuArm64 = 16777228
pkg debug/macho, const CpuArm64 Cpu
pkg debug/pe, const IMAGE_DIRECTORY_ENTRY_ARCHITECTURE = 7
pkg debug/pe, const IMAGE_DIRECTORY_ENTRY_ARCHITECTURE ideal-int
pkg debug/pe, const IMAGE_DIRECTORY_ENTRY_BASERELOC = 5

making compression the default for everyone starting with this release candidate.

Please be considerate of your servers and their operators as you roll out this release. Compression
saves bandwidth but it costs CPU and memory! If you run into a problem you may need to adjust or
disable the `permessage-deflate` compression settings on your server.

Note that OkHttp won't use compression when sending messages smaller than 1 KiB.

FastAPI-Anwendung ausführt). Es wären alles **identische Container**, die das Gleiche ausführen, welche aber jeweils über einen eigenen Prozess, Speicher, usw. verfügen. Auf diese Weise würden Sie die **Parallelisierung** in **verschiedenen Kernen** der CPU nutzen. Oder sogar in **verschiedenen Maschinen**.

Und das verteilte Containersystem mit dem **Load Balancer** würde **die Requests abwechselnd** an jeden einzelnen Container mit Ihrer Anwendung verteilen. Jeder Request könnte also von einem...

  * Create clusters with GPUs in GCE by specifying `type=<gpu-type>,count=<gpu-count>` to NODE_ACCELERATORS environment variable. ([#45130](https://github.com/kubernetes/kubernetes/pull/45130), [@vishh](https://github.com/vishh))

    * List of available GPUs - [https://cloud.google.com/compute/docs/gpus/#introduction](https://cloud.google.com/compute/docs/gpus/#introduction)

# 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.

* Fixed a bug in the single-numa-node policy of the TopologyManager.  Previously, pods that only requested CPU resources and did not request any third-party devices would fail to launch with a TopologyAffinity error. Now they will launch successfully. ([#83697](https://github.com/kubernetes/kubernetes/pull/83697), [@klueska](https://github.com/klueska))

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))