/// tip

I'll give you more concrete examples for doing this with containers in a future chapter: [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank}.

///

## Resource Utilization { #resource-utilization }

Your server(s) is (are) a **resource**, you can consume or **utilize**, with your programs, the computation time on the CPUs, and the RAM memory available.

## Storage usage

The selection of varying data and parity drives has a direct impact on the drive space usage. With storage class, you can optimize for high
redundancy or better drive space utilization.

To get an idea of how various combinations of data and parity drives affect the storage usage, let’s take an example of a 100 MiB file stored

     * Get current cache statistics for monitoring
     * @return formatted statistics string
     */
    public static String getCacheStatistics() {
        return String.format("BufferCache: queued=%d, max=%d, utilization=%.1f%%", queueSize.get(), MAX_BUFFERS,
                (queueSize.get() * 100.0 / MAX_BUFFERS));
    }

    /**
     * Clear all cached buffers (for testing or cleanup)
     */

				if v.N > 0 {
					di.Metrics.LastMinute[k] = v.asTimedAction()
				}
			}
			maps.Copy(di.Metrics.APICalls, info.Metrics.APICalls)
			if info.Total > 0 {
				di.Utilization = float64(info.Used / info.Total * 100)
			}
			disksInfo[index] = di
			return nil
		}, index)
	}

	g.Wait()
	return disksInfo
}

// Get an aggregated storage info across all disks.

                            + "healthChecks=%d, failed=%d, removed=%d, endpoints=%d, "
                            + "healthCheckEnabled=%s, proactiveEnabled=%s, utilization=%.2f%%, successRate=%.2f%%]",
                    activeConnections, nonPooledConnections, trackedConnections, maxPoolSize, totalHealthChecks, failedHealthChecks,

new APIs so we can get out of alpha.

 *  New: Support Java 21's virtual threads (‘OpenJDK Project Loom’). We changed OkHttp's internals
    to use `Lock` and `Condition` instead of `synchronized` for best resource utilization.

 *  New: Switch our Internationalized Domain Name (IDN) implementation to [UTS #46 Nontransitional
    Processing][uts46]. With this fix, the `ß` code point no longer maps to `ss`. OkHttp now embeds

	// in the 10 node shard would coordinate between other 9 shards to get the
	// rest of the `99*9` requests.
	//
	// This essentially splits the workload properly and also allows for network
	// utilization to be optimal, instead of blindly throttling the way we are
	// doing below. However the changes that are needed here are a bit involved,
	// further discussion advised. Remove this comment and remove the worker model

- DRA: scheduling pods is up to 16x faster, depending on the scenario. Scheduling throughput depends a lot on cluster utilization. It is higher for lightly loaded clusters with free resources and gets lower when the cluster utilization increases. ([#127277](https://github.com/kubernetes/kubernetes/pull/127277), [@pohly](https://github.com/pohly)) [SIG API Machinery, Apps, Architecture, Auth, Etcd, Instrumentation, Node, Scheduling...

   ([#123492](https://github.com/kubernetes/kubernetes/pull/123492), [@carlory](https://github.com/carlory))
- Added metric name along with the utilization information when running `kubectl get hpa`. ([#122804](https://github.com/kubernetes/kubernetes/pull/122804), [@sreeram-venkitesh](https://github.com/sreeram-venkitesh))

Si tienes una API que hace una cantidad comparable de cálculos cada vez y tienes muchos clientes, entonces la **utilización de CPU** probablemente *también sea estable* (en lugar de constantemente subir y bajar rápidamente).

### Ejemplos de Herramientas y Estrategias de Replicación