I couldn't find any official documentation specifying what each parameter to a `sla_miss_callback` callable are. This would be a great addition to know how to properly format the messages sent.
airflow/models/dag.py
:param mark_success: True to mark jobs as succeeded without running them
        :type mark_success: bool
        :param local: True to run the tasks using the LocalExecutor
        :type local: bool
        :param executor: The executor instance to run the tasks
        :type executor: airflow.executor.base_executor.BaseExecutor
        :param donot_pickle: True to avoid pickling DAG object and send to workers
        :type donot_pickle: bool
        :param ignore_task_deps: True to skip upstream tasks
        :type ignore_task_deps: bool
        :param ignore_first_depends_on_past: True to ignore depends_on_past
            dependencies for the first set of tasks only
        :type ignore_first_depends_on_past: bool
        :param pool: Resource pool to use
        :type pool: str
        :param delay_on_limit_secs: Time in seconds to wait before next attempt to run
            dag run when max_active_runs limit has been reached
        :type delay_on_limit_secs: float
        :param verbose: Make logging output more verbose
        :type verbose: bool
        :param conf: user defined dictionary passed from CLI
        :type conf: dict
        :param rerun_failed_tasks:
        :type: bool
        :param run_backwards:
        :type: bool
        """
        from airflow.jobs.backfill_job import BackfillJob
        if not executor and local:
            from airflow.executors.local_executor import LocalExecutor