**Description**

Currently when `ECSOperator` is run, the logs of the ECS task are fetched only when the task is done. That's not so convenient, especially when the task takes some good amount of time. In order to understand what's happening with the task, I need to go to Cloudwatch and search for the tasks logs. It would be good to have some parallel process that could fetch ECS task logs from Cloudwatch and make them visible in a realtime. 

**Are you willing to submit a PR?**

I can try, but I need to be guided.

airflow/providers/amazon/aws/operators/ecs.py
:type awslogs_region: str
    :param awslogs_stream_prefix: the stream prefix that is used for the CloudWatch logs.
        This is usually based on some custom name combined with the name of the container.
        Only required if you want logs to be shown in the Airflow UI after your job has
        finished.
    :type awslogs_stream_prefix: str
    :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle
        transient errors.
    :type quota_retry: dict
    :param reattach: If set to True, will check if the task previously launched by the task_instance
        is already running. If so, the operator will attach to it instead of starting a new task.
        This is to avoid relaunching a new task when the connection drops between Airflow and ECS while
        the task is running (when the Airflow worker is restarted for example).
    :type reattach: bool
    :param number_logs_exception: Number of lines from the last Cloudwatch logs to return in the
        AirflowException if an ECS task is stopped (to receive Airflow alerts with the logs of what
        failed in the code running in ECS).
    :type number_logs_exception: int
    """
    ui_color = '#f0ede4'
    template_fields = ('overrides',)
    template_fields_renderers = {
        "overrides": "json",
        "network_configuration": "json",
        "tags": "json",
        "quota_retry": "json",
    }
    REATTACH_XCOM_KEY = "ecs_task_arn"
    REATTACH_XCOM_TASK_ID_TEMPLATE = "{task_id}_task_arn"
    def __init__(