LucasMMota

name: Run CI job on dbt Cloud
# After PR is approved, validate the modifications in dbt Cloud

on:
  pull_request_review: # triggers on PR approval
    types:
      - submitted
  pull_request: # triggers on pull requests, so we make sure this won't be skipped
    types:
      - opened

LucasMMota

from datetime import datetime, timedelta
from airflow.models import DAG
from airflow.operators.bash_operator import BashOperator

dag = DAG(
    dag_id="my_dag_to_test_sla",
    catchup=False,
    start_date=datetime(2021, 8, 28, 0, 0, 0),
    # If schedule_interval=None, SLA won't be evaluated for this DAG!
    schedule_interval="*/5 * * * *",

LucasMMota

from datetime import datetime, timedelta
from airflow.models import DAG
from airflow.operators.bash_operator import BashOperator


def my_alerting_function(dag, task_list, blocking_task_list, slas, blocking_tis):
    """Executes the user defined code (for example, post on Slack)"""

    message = (
        f":alert: *Airflow SLA Miss*\n\n"

LucasMMota

"""
:param sla: time by which the job is expected to succeed. Note that
    this represents the ``timedelta`` after the period is closed. For
    example if you set an SLA of 1 hour, the scheduler would send an email
    soon after 1:00AM on the ``2016-01-02`` if the ``2016-01-01`` instance
    has not succeeded yet.
    The scheduler pays special attention for jobs with an SLA and
    sends alert
    emails for sla misses. SLA misses are also recorded in the database
    for future reference. All tasks that share the same SLA time