**Apache Airflow version**:  1.10.10


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): v1.15.11

KubernetesPodOperator truncates logs when container produces more than 10 lines of logs before execution of `read_pod_logs` function. Is there any reason to make 10 as default value for `tail_lines` argument ?
```python
    def read_pod_logs(self, pod: V1Pod, tail_lines: int = 10):
        """Reads log from the POD"""
        try:
            return self._client.read_namespaced_pod_log(
                name=pod.metadata.name,
                namespace=pod.metadata.namespace,
                container='base',
                follow=True,
                tail_lines=tail_lines,
                _preload_content=False
            )
        except BaseHTTPError as e:
            raise AirflowException(
                'There was an error reading the kubernetes API: {}'.format(e)
            )
```
kubernetes_tests/test_kubernetes_pod_operator.py
'image': 'apache/airflow:stress-2020.07.10-1.0.4',
                                                  'name': 'base',
                                                  'ports': [],
                                                  'resources': {'limits': {'memory': '200Mi'},
                                                                'requests': {'memory': '100Mi'}},
                                                  'volumeMounts': [{'mountPath': '/airflow/xcom',
                                                                    'name': 'xcom'}]},
                                                 {'command': ['sh',
                                                              '-c',
                                                              'trap "exit 0" INT; while true; do sleep '
                                                              '30; done;'],
                                                  'image': 'alpine',
                                                  'name': 'airflow-xcom-sidecar',
                                                  'resources': {'requests': {'cpu': '1m'}},
                                                  'volumeMounts': [{'mountPath': '/airflow/xcom',
                                                                    'name': 'xcom'}]}],
                                  'hostNetwork': False,
                                  'imagePullSecrets': [],
                                  'initContainers': [],
                                  'nodeSelector': {},
                                  'restartPolicy': 'Never',
                                  'securityContext': {},
                                  'serviceAccountName': 'default',
                                  'tolerations': [],
                                  'volumes': [{'emptyDir': {}, 'name': 'xcom'}]}}
        self.assertEqual(expected_dict, actual_pod)
    @mock.patch("airflow.kubernetes.pod_launcher.PodLauncher.start_pod")
    @mock.patch("airflow.kubernetes.pod_launcher.PodLauncher.monitor_pod")
    @mock.patch("airflow.kubernetes.kube_client.get_kube_client")
    def test_pod_priority_class_name(