"upstream_rq_time,upstream_cx_tx_bytes_total,upstream_cx_rx_bytes_total,upstream_cx_total"

	// example downstream metric: http.10.16.48.230_8080.downstream_rq_2xx
	// http.<pod_ip>_<port>.downstream_rq_2xx
	// This metric is collected at the inbound listener at a sidecar.
	// All the other downstream metrics at a sidecar are from the application to the local sidecar.

			},
			Labels: map[string]string{
				"app": sa,
			},
		},
		Spec: corev1.PodSpec{
			ServiceAccountName: sa,
			NodeName:           node,
		},
		Status: corev1.PodStatus{
			PodIP: ip,
			PodIPs: []corev1.PodIP{
				{
					IP: ip,
				},
			},
			Phase: corev1.PodRunning,
			Conditions: []corev1.PodCondition{
				{
					Type:               corev1.PodReady,

          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
        - name: INSTANCE_IP
          valueFrom:
            fieldRef:
              fieldPath: status.podIP
        - name: SERVICE_ACCOUNT
          valueFrom:
            fieldRef:
              fieldPath: spec.serviceAccountName
        - name: HOST_IP
          valueFrom:
            fieldRef:

                fieldPath: metadata.namespace
          - name: INSTANCE_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.podIP
          - name: HOST_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.hostIP
          - name: ISTIO_CPU_LIMIT
            valueFrom:

for more complete documentation.

### Stable

Run the following command to run the latest stable image of MinIO as a container using an ephemeral data volume:

```sh
podman run -p 9000:9000 -p 9001:9001 \
  quay.io/minio/minio server /data --console-address ":9001"
```

                fieldPath: metadata.namespace
          - name: INSTANCE_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.podIP
          - name: HOST_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.hostIP
          - name: ISTIO_CPU_LIMIT
            valueFrom:

          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
        - name: INSTANCE_IP
          valueFrom:
            fieldRef:
              fieldPath: status.podIP
        - name: SERVICE_ACCOUNT
          valueFrom:
            fieldRef:
              fieldPath: spec.serviceAccountName
        - name: HOST_IP
          valueFrom:
            fieldRef:

	ctx := context.Background()
	container := &pod.Spec.Containers[containerIndex]
	podIP := ""
	restartCount := 0
	opts, _, _ := m.runtimeHelper.GenerateRunContainerOptions(ctx, pod, container, podIP, []string{podIP})
	containerLogsPath := buildContainerLogsPath(container.Name, restartCount)
	restartCountUint32 := uint32(restartCount)

		return fmt.Errorf("expected to get 200 status code, got: %s", res.Responses[0].Code)
	}
	return nil
}

func verifyThatRequestWasTunneled(target echo.Instance, expectedSourceIPs []corev1.PodIP, expectedPath string) error {
	workloads, err := target.Workloads()
	if err != nil {
		return fmt.Errorf("failed to get workloads of %s: %s", target.ServiceName(), err)
	}
	var logs strings.Builder

    * Walidatory umożliwiają jasne i łatwe definiowanie, sprawdzanie złożonych struktur danych oraz dokumentowanie ich jako JSON Schema.
    * Możesz mieć głęboko **zagnieżdżone obiekty JSON** i wszystkie je poddać walidacji i adnotować.
* **Rozszerzalność**:
    * Pydantic umożliwia zdefiniowanie niestandardowych typów danych lub rozszerzenie walidacji o metody na modelu, na których użyty jest dekorator walidatora.