code: def get_default_kubernetes_metadata_config() -> (
      metadata_store_pb2.ConnectionConfig
  ):
      """Returns the default metadata connection config for a kubernetes cluster.
  
      Returns:
        A config proto that will be serialized as JSON and passed to the running
        container so the TFX component driver is able to communicate with MLMD in
        a kubernetes cluster.
      """
      connection_config = metadata_store_pb2.ConnectionConfig()
      connection_config.mysql.host = "mysql"
      connection_config.mysql.port = 3306
      connection_config.mysql.database = "mysql"
      connection_config.mysql.user = "root"
      connection_config.mysql.password = ""
      return connection_config
  
imports: import datetime
  import json
  from typing import List, Optional, Type
  from absl import logging
  from tfx.dsl.component.experimental import container_component
  from tfx.dsl.components.base import base_node
  from tfx.orchestration import data_types
  from tfx.orchestration import metadata
  from tfx.orchestration import pipeline
  from tfx.orchestration import tfx_runner
  from tfx.orchestration.config import base_component_config
  from tfx.orchestration.config import config_utils
  from tfx.orchestration.config import pipeline_config
  from tfx.orchestration.experimental.kubernetes import kubernetes_remote_runner
  from tfx.orchestration.experimental.kubernetes import node_wrapper
  from tfx.orchestration.launcher import base_component_launcher
  from tfx.orchestration.launcher import in_process_component_launcher
  from tfx.orchestration.launcher import kubernetes_component_launcher
  from tfx.utils import json_utils
  from tfx.utils import kube_utils
  from tfx.utils import name_utils
  from google.protobuf import json_format
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 1 for calling a global function with example usage: get_default_kubernetes_metadata_config() and returns: connection_config