"interval": "1m",
          "intervalFactor": 2,
          "legendFormat": "{{bucket}}",
          "refId": "A"
        }
      ],
      "title": "Delete Markers",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "Prometheus"
      },
      "fieldConfig": {
        "defaults": {

}

// xlMetaV2DeleteMarker defines the data struct for the delete marker journal type
type xlMetaV2DeleteMarker struct {
	VersionID [16]byte          `json:"ID" msg:"ID"`                               // Version ID for delete marker
	ModTime   int64             `json:"MTime" msg:"MTime"`                         // Object delete marker modified time

				// Bucket is versioned and no version was explicitly
				// mentioned for deletes, create a delete marker instead.
				vr.ModTime = UTCNow()
				vr.Deleted = true
				// Versioning suspended means that we add a `null` version
				// delete marker, if not add a new version for this delete
				// marker.
				if versioned {
					vr.VersionID = mustGetUUID()
				}
			}
		}

Lkotlin/jvm/internal/Ref$ObjectRef;
Lkotlin/jvm/internal/Reflection;
Lkotlin/jvm/internal/ReflectionFactory;
Lkotlin/jvm/internal/TypeIntrinsics;
Lkotlin/jvm/internal/markers/KMappedMarker;
Lkotlin/jvm/internal/markers/KMutableList;
Lkotlin/random/AbstractPlatformRandom;
Lkotlin/random/FallbackThreadLocalRandom$implStorage$1;
Lkotlin/random/FallbackThreadLocalRandom;
Lkotlin/random/Random$Default;

## 🏃 🐁 ⏮️ Uvicorn 👨‍🏭

⤴️ 👆 💪 🏃 🐁 ⏮️:

<div class="termy">

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513

这将安装带有`standard`扩展包（以获得高性能）的 Uvicorn 和 Gunicorn。

## Run Gunicorn with Uvicorn Workers

接下来你可以通过以下命令运行Gunicorn:

<div class="termy">

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511

import (
	"context"
	"fmt"
	"strconv"
	"strings"
)

// markerTagVersion is the marker version.
// Should not need to be updated unless a fundamental change is made to the marker format.
const markerTagVersion = "v2"

// parseMarker will parse a marker possibly encoded with encodeMarker
func (o *listPathOptions) parseMarker() {
	s := o.Marker
	if !strings.Contains(s, "[minio_cache:"+markerTagVersion) {
		return
	}

	public final fun get (Lokhttp3/TlsVersion;Lokhttp3/CipherSuite;Ljava/util/List;Ljava/util/List;)Lokhttp3/Handshake;
}

public final class okhttp3/Headers : java/lang/Iterable, kotlin/jvm/internal/markers/KMappedMarker {
	public static final field Companion Lokhttp3/Headers$Companion;
	public final fun -deprecated_size ()I
	public final fun byteCount ()J
	public fun equals (Ljava/lang/Object;)Z

In particular, when running on **Kubernetes** you will probably **not** want to use workers and instead run **a single Uvicorn process per container**, but I'll tell you about it later in that chapter.

///

## Multiple Workers

You can start multiple workers with the `--workers` command line option:

//// tab | `fastapi`

If you use the `fastapi` command:

<div class="termy">

Dann können Sie Gunicorn ausführen mit:

<div class="termy">

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513