// sleep for some time and try again.
			duration := time.Duration(r.Float64() * float64(globalCallhomeConfig.FrequencyDur()))
			if duration < time.Second {
				// Make sure to sleep at least a second to avoid high CPU ticks.
				duration = time.Second
			}
			time.Sleep(duration)
		}
	}()
}

func runCallhome(ctx context.Context, objAPI ObjectLayer) bool {
	// Make sure only 1 callhome is running on the cluster.

 * java.util.LinkedHashMap}. Generally speaking, this class reduces object allocation and memory
 * consumption at the price of moderately increased constant factors of CPU. Only use this class
 * when there is a specific reason to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 */
@J2ktIncompatible // no support for access-order mode in LinkedHashMap delegate
@GwtIncompatible // not worth using in GWT for now

	}
	info := getLocalServerProperty(globalEndpoints, &r, metrics)
	return madminServerProperties.NewJSONWith(&info), nil
}

// GetCPUsHandler - returns CPU info.
func (s *peerRESTServer) GetCPUsHandler(_ *grid.MSS) (*grid.JSON[madmin.CPUs], *grid.RemoteErr) {
	info := madmin.GetCPUs(context.Background(), globalLocalNodeName)
	return madminCPUs.NewJSONWith(&info), nil
}

	}
	return formattedName
}

var (
	// https://github.com/golang/lint/blob/master/lint.go#L770
	commonInitialisms         = []string{"API", "ASCII", "CPU", "CSS", "DNS", "EOF", "GUID", "HTML", "HTTP", "HTTPS", "ID", "IP", "JSON", "LHS", "QPS", "RAM", "RHS", "RPC", "SLA", "SMTP", "SSH", "TLS", "TTL", "UID", "UI", "UUID", "URI", "URL", "UTF8", "VM", "XML", "XSRF", "XSS"}

         "type": "timeseries"
      },
      {
         "datasource": {
            "type": "datasource",
            "uid": "-- Mixed --"
         },
         "description": "CPU usage of each running instance",
         "fieldConfig": {
            "defaults": {
               "custom": {
                  "fillOpacity": 10,
                  "gradientMode": "hue",

///

### 官方 Docker 镜像上的进程数

此镜像上的**进程数**是根据可用的 CPU **核心**自动计算的。

这意味着它将尝试尽可能多地**榨取**CPU 的**性能**。

你还可以使用 **环境变量** 等配置来调整它。

但这也意味着，由于进程数量取决于容器运行的 CPU，因此**消耗的内存量**也将取决于该数量。

因此，如果你的应用程序消耗大量内存（例如机器学习模型），并且你的服务器有很多 CPU 核心**但内存很少**，那么你的容器最终可能会尝试使用比实际情况更多的内存 可用，并且性能会下降很多（甚至崩溃）。 🚨

### 创建一个`Dockerfile`

以下是如何根据此镜像创建`Dockerfile`：

---

Typische Beispiele für CPU-lastige Vorgänge sind Dinge, die komplexe mathematische Berechnungen erfordern.

Zum Beispiel:

* **Audio-** oder **Bildbearbeitung**.

---

Ejemplos típicos de operaciones dependientes de CPU son cosas que requieren un procesamiento matemático complejo.

Por ejemplo:

* **Audio** o **procesamiento de imágenes**.

- 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/kubernetes/kubernetes/pull/83592), [@jianzzh...

of Go values and free that space manually all at once, safely. The purpose
of this functionality is to improve efficiency: manually freeing memory
before a garbage collection delays that cycle. Less frequent cycles means
the CPU cost of the garbage collector is incurred less frequently.

This functionality in this package is mostly captured in the Arena type.
Arenas allocate large chunks of memory for Go values, so they're likely to