def run_next(self, next_job):
self.log.info('<STR_LIT>', str(next_job))<EOL>key, command, kube_executor_config = next_job<EOL>dag_id, task_id, execution_date, try_number = key<EOL>self.log.debug("<STR_LIT>", command)<EOL>self.log.debug("<STR_LIT>", self.kube_config.kube_image)<EOL>pod = self.worker_configuration.make_pod(<EOL>namespace=self.namespace, worker_uuid=self.worker_uuid,<EOL>pod_id=self._create_pod_id(dag_id, task_id),<EOL>dag_id=self._make_safe_label_value(dag_id),<EOL>task_id=self._make_safe_label_value(task_id),<EOL>try_number=try_number,<EOL>execution_date=self._datetime_to_label_safe_datestring(execution_date),<EOL>airflow_command=command, kube_executor_config=kube_executor_config<EOL>)<EOL>self.launcher.run_pod_async(pod)<EOL>self.log.debug("<STR_LIT>")<EOL>
The run_next command will check the task_queue for any un-run jobs.
It will then create a unique job-id, launch that job in the cluster,
and store relevant info in the current_jobs map so we can track the job's
status