}
        message.append("]");

        return message.toString();
    }

    /**
     * 0-100, the percentage of time spent on doing the work vs time spent in gc
     */
    private int getCurrentPerformance() {
        long collectionTime = gcInfo.getCollectionTime();
        long allBuildsTime = runningStats.getAllBuildsTime();

package org.gradle.launcher.daemon.server.health.gc;

import java.lang.management.GarbageCollectorMXBean;
import java.lang.management.ManagementFactory;

public class GarbageCollectionInfo {
    /**
     * Approx. time spent in gc. See {@link GarbageCollectorMXBean}
     */
    public long getCollectionTime() {
        long garbageCollectionTime = 0;
        for (GarbageCollectorMXBean gc : ManagementFactory.getGarbageCollectorMXBeans()) {

        when:
        executer.withArguments("--parallel", "-D${DefaultWorkerLeaseService.PROJECT_LOCK_STATS_PROPERTY}")
        succeeds(":wait", ":child:blocked")

        then:
        result.assertHasPostBuildOutput("Time spent waiting on project locks")
    }

Also, the best approach was to use already existing standards.

So, before even starting to code **FastAPI**, I spent several months studying the specs for OpenAPI, JSON Schema, OAuth2, etc. Understanding their relationship, overlap, and differences.

## Design

Then I spent some time designing the developer "API" I wanted to have as a user (as a developer using FastAPI).

// IO wait, currently only network blocking event).
func computePprofIO() computePprofFunc {
	return makeComputePprofFunc(trace.GoWaiting, func(reason string) bool {
		return reason == "network"
	})
}

// computePprofBlock returns a computePprofFunc that generates blocking pprof-like profile
// (time spent blocked on synchronization primitives).

	for {
		if mp.count > 0 {
			mp.count--
			pthread_mutex_unlock(&mp.mutex)
			return 0
		}
		if ns >= 0 {
			spent := nanotime() - start
			if spent >= ns {
				pthread_mutex_unlock(&mp.mutex)
				return -1
			}
			var t timespec
			t.setNsec(ns - spent)
			err := pthread_cond_timedwait_relative_np(&mp.cond, &mp.mutex, &t)
			if err == _ETIMEDOUT {
				pthread_mutex_unlock(&mp.mutex)
				return -1

}

func init() {
	legacyregistry.MustRegister(Metrics.(*validationMetrics).RatchetingTime)
}

type validationMetrics struct {
	RatchetingTime *metrics.Histogram
}

// ObserveRatchetingTime records the time spent on ratcheting
func (m *validationMetrics) ObserveRatchetingTime(d time.Duration) {
	m.RatchetingTime.Observe(d.Seconds())
}

// Reset resets the metrics. This is meant to be used for testing. Panics

			Namespace:      namespace,
			Subsystem:      subsystem,
			Name:           "jwt_authenticator_latency_seconds",
			Help:           "Latency of jwt authentication operations in seconds. This is the time spent authenticating a token for cache miss only (i.e. when the token is not found in the cache).",
			StabilityLevel: metrics.ALPHA,
			// default histogram buckets with a 1ms starting point

// utilization without hurting throughput.
//
// Note that the bucket in the leaky bucket mechanism can never go negative,
// so the GC never gets credit for a lot of CPU time spent without the GC
// running. This is intentional, as an application that stays idle for, say,
// an entire day, could build up enough credit to fail to prevent a death

	}
	return d2
}

// DurationTracker is a simple interface for tracking functions duration,
// it is safe for concurrent use by multiple goroutines.
type DurationTracker interface {
	// Track measures time spent in the given function f and
	// aggregates measured duration using aggregateFunction.
	// if Track is invoked with f from multiple goroutines concurrently,
	// then f must be safe to be invoked concurrently by multiple goroutines.