return MetricDescription{
		Namespace: s3MetricNamespace,
		Subsystem: requestsSubsystem,
		Name:      inflightTotal,
		Help:      "Total number of S3 requests currently in flight",
		Type:      gaugeMetric,
	}
}

func getS3RequestsInQueueMD() MetricDescription {
	return MetricDescription{
		Namespace: s3MetricNamespace,
		Subsystem: requestsSubsystem,

    queueDispatcher.enqueue(MockResponse(body = "call2 response"))
    queueDispatcher.enqueue(MockResponse(body = "call1 response"))

    // We use a re-entrant dispatcher to initiate one HTTPS connection while the other is in flight.
    server.dispatcher =
      object : Dispatcher() {
        var requestCount = 0

        override fun dispatch(request: RecordedRequest): MockResponse {

fb"}.fa-eye-slash:before{content:"\f070"}.fa-facebook:before{content:"\f09a"}.fa-facebook-f:before{content:"\f39e"}.fa-facebook-messenger:before{content:"\f39f"}.fa-facebook-square:before{content:"\f082"}.fa-fan:before{content:"\f863"}.fa-fantasy-flight-games:before{content:"\f6dc"}.fa-fast-backward:before{content:"\f049"}.fa-fast-forward:before{content:"\f050"}.fa-fax:before{content:"\f1ac"}.fa-feather:before{content:"\f52d"}.fa-feather-alt:before{content:"\f56b"}.fa-fedex:before{content:"\f797...

    assertThat(data2.streamId).isEqualTo(3)
    assertArrayEquals("fghi".toByteArray(), data2.data)
  }

  /**
   * Confirm that we account for discarded data frames. It's possible that data frames are in-flight
   * just prior to us canceling a stream.
   */
  @Test fun discardedDataFramesAreCounted() {
    // Write the mocking script.
    peer.sendFrame().settings(Settings())
    peer.acceptFrame() // ACK

- Added a `Processing` condition for the `workqueue` API.
  Changed `Shutdown` for the `workqueue` API to wait until the work queue finishes processing all in-flight items. ([#101928](https://github.com/kubernetes/kubernetes/pull/101928), [@alexanderConstantinescu](https://github.com/alexanderConstantinescu))

   The `read_vs_write_current_requests` metric histogram is adjusted, in the case of using API Priority and Fairness instead of max-in-flight, to divide by the relevant limit: sum of queue capacities for waiting requests, sum of seat limits for executing requests. ([#110164](https://github.com/kubernetes/kubernetes/pull/110164), [@MikeSpreitzer](https://github.com/MikeSpreitzer))

    val call = client.newCall(Request(server.url("/a")))
    val executor = Executors.newSingleThreadExecutor()
    val result = executor.submit<Response?> { call.execute() }
    Thread.sleep(100) // wait for it to go in flight.
    call.cancel()
    assertFailsWith<IOException> {
      result.get()!!.body.bytes()
    }
    assertThat(server.requestCount).isEqualTo(1)
  }

  @Test

fishing
fit
fitjar.no
fitness
fj
fj.cn
fjaler.no
fjell.no
fl.us
fla.no
flakstad.no
flatanger.no
fldrv.com
flekkefjord.no
flesberg.no
flickr
flier.jp
flight.aero
flights
flir
flog.br
flop.jp
floppy.jp
flora.no
florence.it
floripa.br
florist
floro.no
florø.no
flowers
flt.cloud.muni.cz
flutterflow.app
fly

fishing
fit
fitjar.no
fitness
fj
fj.cn
fjaler.no
fjell.no
fl.us
fla.no
flakstad.no
flatanger.no
fldrv.com
flekkefjord.no
flesberg.no
flickr
flier.jp
flight.aero
flights
flir
flog.br
flop.jp
floppy.jp
flora.no
florence.it
floripa.br
florist
floro.no
florø.no
flowers
flt.cloud.muni.cz
flutterflow.app
fly

  After the connection closed(received GOAWAY), the client's other in-flight requests won't be affected, and the client will reconnect. 
  The flag min value is 0 (off), max is .02 (1/50 requests); .001 (1/1000) is a recommended starting point.