protected void writeFesenJson(final ZipOutputStream zos, final String id) {
        writeElastisearchJsonApi(zos, id, "cluster", "health");
        writeElastisearchJsonApi(zos, id, "cluster", "state");
        writeElastisearchJsonApi(zos, id, "cluster", "stats");
        writeElastisearchJsonApi(zos, id, "cluster", "pending_tasks");
        writeElastisearchJsonApi(zos, id, "nodes", "stats");

	}
	return nil, nil
}

// clusterOrigin defines an Origin that refers to the cluster
type clusterOrigin struct{}

func (o clusterOrigin) ClusterName() istiocluster.ID {
	return "Cluster"
}

func (o clusterOrigin) String() string {
	return ""
}

func (o clusterOrigin) FriendlyName() string {
	return "Cluster"
}

func (o clusterOrigin) Comparator() string {
	return o.FriendlyName()
}

você tiver um <abbr title="Um grupo de máquinas que são configuradas para estarem conectadas e trabalharem juntas de alguma forma">cluster</abbr> de máquinas com **Kubernetes**, Docker Swarm Mode, Nomad ou outro sistema complexo semelhante para gerenciar contêineres distribuídos em várias máquinas, então provavelmente desejará **lidar com a replicação** no **nível do cluster** em vez de usar um **gerenciador de processos** (como o Gunicorn com workers) em cada contêiner.

Um desses sistemas...

  annotations: {{- toYaml .Values.service.annotations | nindent 4 }}
  {{- end }}
spec:
  type: {{ .Values.service.type }}
  {{- if and (eq .Values.service.type "ClusterIP") .Values.service.clusterIP }}
  clusterIP: {{ .Values.service.clusterIP }}
  {{- end }}
  {{- if or (eq .Values.service.type "LoadBalancer") (eq .Values.service.type "NodePort") }}
  externalTrafficPolicy: {{ .Values.service.externalTrafficPolicy | quote }}

your deployment.

Even though this change is backward compatible we do not expect that it affects
the vast majority of deployments in any negative way.

> Will an upgrade of an existing MinIO cluster impact the SLA of the cluster or will it even cause downtime?

No, an upgrade should not cause any downtime. However, on the first startup -
since MinIO will attempt to migrate any existing IAM data - the boot process may

         "type": "row"
      },
      {
         "datasource": {
            "type": "datasource",
            "uid": "-- Mixed --"
         },
         "description": "Total requests in the cluster",
         "fieldConfig": {
            "defaults": {
               "color": {
                  "fixedColor": "blue",
                  "mode": "fixed"
               },
               "custom": {

  optional string name = 3;

  // scope represents if this refers to a cluster or namespace scoped resource.
  // This may be set to "Cluster" (default) or "Namespace".
  optional string scope = 4;

  // namespace is the namespace of the resource being referenced. This field is
  // required when scope is set to "Namespace" and must be unset when scope is set to
  // "Cluster".
  // +optional
  optional string namespace = 5;
}

If you have a <abbr title="A group of machines that are configured to be connected and work together in some way.">cluster</abbr> of machines with **Kubernetes**, Docker Swarm Mode, Nomad, or another similar complex system to manage distributed containers on multiple machines, then you will probably want to **handle replication** at the **cluster level** instead of using a **process manager** (like Uvicorn with workers) in each container.

title="Eine Gruppe von Maschinen, die so konfiguriert sind, dass sie verbunden sind und auf irgendeine Weise zusammenarbeiten.">Cluster</abbr> von Maschinen mit **Kubernetes**, Docker Swarm Mode, Nomad verwenden, oder einem anderen, ähnlich komplexen System zur Verwaltung verteilter Container auf mehreren Maschinen, möchten Sie wahrscheinlich die **Replikation auf Cluster-Ebene abwickeln**, anstatt in jedem Container einen **Prozessmanager** (wie Gunicorn mit Workern) zu verwenden.

Diese...

}

// RuntimeClass defines a class of container runtime supported in the cluster.
// The RuntimeClass is used to determine which container runtime is used to run
// all containers in a pod. RuntimeClasses are manually defined by a
// user or cluster provisioner, and referenced in the PodSpec. The Kubelet is
// responsible for resolving the RuntimeClassName reference before running the