diff --git a/dags/example_dag_with_taskflow_api.py b/dags/example_dag_with_taskflow_api.py
index 0bd1ba5c0..e5d3c56d3 100644
--- a/dags/example_dag_with_taskflow_api.py
+++ b/dags/example_dag_with_taskflow_api.py
@@ -1,25 +1,68 @@
-# DAG exhibiting task flow paradigm in airflow 2.0
-# https://airflow.apache.org/docs/apache-airflow/2.0.2/tutorial_taskflow_api.html
-# Modified for our use case
-
 import json
+import pendulum
+
 from airflow.decorators import dag, task
-from airflow.utils.dates import days_ago
-# These args will get passed on to each operator
-# You can override them on a per-task basis during operator initialization
+from airflow.models import Variable
+from airflow.hooks.base_hook import BaseHook
+from airflow.providers.slack.operators.slack_webhook import SlackWebhookOperator
+
+
+def task_failure_slack_alert(context):
+    print(f"Task has failed, task_instance_key_str: {context['task_instance_key_str']}")
+
+    environment = Variable.get("airflow_environment", default_var="local")
+    if environment not in ["dev", "prod"] :
+        print(f"{environment} mode - skip sending alerts.")
+        return
+
+    ti = context['ti'] # to get the Task Instance
+    TASK_STATE = ti.state
+    TASK_ID = context.get('task_instance').task_id
+    DAG_ID = context.get('task_instance').dag_id
+    EXECUTION_TIME = context.get('execution_date')
+    LOG_URL = context.get('task_instance').log_url
+
+    slack_msg = f"""
+        :red_circle: Task Failed.
+        *Dag*: {DAG_ID}
+        *Task*: {TASK_ID}
+        *Task State*: {TASK_STATE}
+        *Execution Time*: {EXECUTION_TIME}
+        *Log URL*: <{LOG_URL}|*Logs*>
+    """
+
+    SLACK_FAILURE_ALERT_CONN_ID = "slack_data_alerts"
+    CHANNEL = BaseHook.get_connection(SLACK_FAILURE_ALERT_CONN_ID).login
+
+    slack_alert = SlackWebhookOperator(
+        task_id=TASK_ID,
+        slack_webhook_conn_id = SLACK_FAILURE_ALERT_CONN_ID,
+        message=slack_msg,
+        channel=CHANNEL,
+        username='airflow'
+    )
+
+    return slack_alert.execute(context=context)
+
 default_args = {
-    'owner': 'airflow',
+    'owner':'data platform',
+    'retries': 0,
+    'start_date': pendulum.datetime(2021, 1, 1, tz="UTC")
 }
-@dag(default_args=default_args, schedule_interval="@daily", start_date=days_ago(2), tags=['example'])
-def dag_with_taskflow_api():
-    """
-    ### TaskFlow API Tutorial Documentation
-    This is a simple ETL data pipeline example which demonstrates the use of
-    the TaskFlow API using three simple tasks for Extract, Transform, and Load.
-    Documentation that goes along with the Airflow TaskFlow API tutorial is
-    located
-    [here](https://airflow.apache.org/docs/stable/tutorial_taskflow_api.html)
-    """
+
+@dag(
+    dag_id="example_taskflow_api",
+    description="Taskflow api example",
+    schedule=None,
+    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
+    default_args = default_args,
+    catchup=False,
+    on_success_callback=None,
+    on_failure_callback=task_failure_slack_alert,
+    tags=["example"],
+)
+
+def tutorial_taskflow_api():
     @task()
     def extract():
         """
@@ -32,6 +75,7 @@ def extract():
 
         order_data_dict = json.loads(data_string)
         return order_data_dict
+
     @task(multiple_outputs=True)
     def transform(order_data_dict: dict):
         """
@@ -45,6 +89,7 @@ def transform(order_data_dict: dict):
             total_order_value += value
 
         return {"total_order_value": total_order_value}
+
     @task()
     def load(total_order_value: float):
         """
@@ -53,8 +98,10 @@ def load(total_order_value: float):
         instead of saving it to end user review, just prints it out.
         """
 
-        print("Total order value is: %.2f" % total_order_value)
+        print(f"Total order value is: {total_order_value:.2f}")
+
     order_data = extract()
     order_summary = transform(order_data)
     load(order_summary["total_order_value"])
-dag_with_taskflow_api = dag_with_taskflow_api()
+
+tutorial_taskflow_api()
diff --git a/docker/config/.env.localrunner b/docker/config/.env.localrunner
index 04859fb09..a6b705046 100644
--- a/docker/config/.env.localrunner
+++ b/docker/config/.env.localrunner
@@ -2,10 +2,24 @@
 # Example environment variables using temporary security credentials
 # AWS_ACCESS_KEY_ID=XXXXXXXXXX
 # AWS_SECRET_ACCESS_KEY=YYYYYYYYYYYY
-# AWS_SESSION_TOKEN=ZZZZZZZZZZ 
+# AWS_SESSION_TOKEN=ZZZZZZZZZZ
 
 # to change default password you'll need to delete the db-data folder (when running locally)
 DEFAULT_PASSWORD="test"
 S3_DAGS_PATH=""
 S3_PLUGINS_PATH=""
 S3_REQUIREMENTS_PATH=""
+ENVIRONMENT="local"
+
+# Airflow webserver instance name
+AIRFLOW__WEBSERVER__INSTANCE_NAME="DAGs (Local)"
+
+# Airflow variables
+# Example: "AIRFLOW_VAR_{}"
+AIRFLOW_VAR_AIRFLOW_ENVIRONMENT="local"
+
+# Example of JSON format variable
+# AIRFLOW_VAR_SLACK_DMS_MONITOR='{"key":"","value":""}'
+
+# Airflow connections
+# Example: "AIRFLOW_CONN_{}"
diff --git a/requirements/requirements.txt b/requirements/requirements.txt
index 90a2f9902..49eef0d26 100644
--- a/requirements/requirements.txt
+++ b/requirements/requirements.txt
@@ -4,3 +4,4 @@ apache-airflow-providers-snowflake==5.2.1
 apache-airflow-providers-mysql==5.5.1
 apache-airflow-providers-slack==8.5.1
 boto3==1.33.13
+astronomer-cosmos==1.3.2