SLA misses and notifications in Apache Airflow - Mini Project: Build & Apply

SLA Misses and Notifications in Airflow

📖 Scenario: You are managing data pipelines using Apache Airflow. You want to track when tasks miss their Service Level Agreement (SLA) deadlines and send notifications to the team.This helps ensure timely data processing and quick response to delays.

🎯 Goal: Build an Airflow DAG that defines tasks with SLAs and configures an SLA miss callback function to send notifications.You will create the DAG, set SLA times, define the notification function, and verify the SLA miss handling.

📋 What You'll Learn

Create an Airflow DAG with at least two tasks

Set SLA times for the tasks using sla parameter

Define a function called sla_miss_callback that accepts dag, task_list, blocking_task_list, slas, session parameters

Configure the DAG to use sla_miss_callback for SLA miss notifications

Print a message inside sla_miss_callback showing which tasks missed SLA

Trigger the DAG run and observe SLA miss notification output

💡 Why This Matters

🌍 Real World

In real data engineering teams, monitoring SLAs ensures pipelines run on time. SLA miss notifications help quickly fix delays to keep data fresh.

💼 Career

Understanding SLA misses and notifications is important for DevOps and data engineering roles managing workflow reliability and alerting.

1

Create the Airflow DAG and tasks

Create an Airflow DAG called sla_notification_dag with start_date set to datetime(2024, 1, 1) and schedule_interval set to timedelta(days=1). Inside the DAG, create two PythonOperator tasks named task_a and task_b that run simple Python functions printing 'Task A executed' and 'Task B executed' respectively.

Apache Airflow

from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime, timedelta

# Create the DAG and tasks below
# Your code here

Hint

Use DAG to create the DAG and PythonOperator for tasks. Define simple functions for python_callable.

2

Add SLA times to the tasks

Add an SLA of 10 minutes to task_a and 15 minutes to task_b by setting the sla parameter with timedelta(minutes=10) and timedelta(minutes=15) respectively in their PythonOperator definitions.

Apache Airflow

from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime, timedelta

def task_a_func():
    print('Task A executed')

def task_b_func():
    print('Task B executed')

sla_notification_dag = DAG(
    'sla_notification_dag',
    start_date=datetime(2024, 1, 1),
    schedule_interval=timedelta(days=1)
)

# Add sla parameter to task_a and task_b below
# Your code here

Hint

Add the sla argument inside the PythonOperator constructor for each task.

3

Define the SLA miss callback function

Define a function called sla_miss_callback that accepts parameters dag, task_list, blocking_task_list, slas, and session. Inside the function, print a message: "SLA missed for tasks: {task_list}" using an f-string.

Apache Airflow

from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime, timedelta

# Define sla_miss_callback function below
# Your code here

Hint

Define the function with the exact name and parameters. Use an f-string to print the task list.

4

Configure the DAG to use the SLA miss callback and print output

Add the sla_miss_callback function to the sla_notification_dag by setting the sla_miss_callback parameter in the DAG constructor. Then, write a print statement outside the DAG that prints "SLA miss notification setup complete".

Apache Airflow

from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime, timedelta

# Add sla_miss_callback to DAG and print confirmation below
# Your code here

Hint

Pass sla_miss_callback=sla_miss_callback when creating the DAG. Use print() to show the confirmation message.

Practice

1. What does setting an sla parameter on an Airflow task do?

easy

A. It defines a time limit; if the task runs longer, it triggers an SLA miss.

B. It sets the maximum retries for the task.

C. It schedules the task to run at a specific time.

D. It disables the task from running automatically.

Solution

1. Step 1: Understand the purpose of sla in Airflow tasks

   The sla parameter sets a time limit for task execution.

2. Step 2: Identify what happens when the limit is exceeded

   If the task runs longer than the sla time, Airflow marks it as an SLA miss.

3. Final Answer:

   It defines a time limit; if the task runs longer, it triggers an SLA miss. -> Option A

4. Quick Check:

   sla sets time limit = C [OK]

Hint: Remember SLA means max allowed time for task [OK]

Common Mistakes:

• Confusing SLA with retry count
• Thinking SLA schedules task start time
• Assuming SLA disables tasks

2. Which of the following is the correct way to define an SLA of 30 minutes on a task in Airflow?

easy

A. sla='30 minutes'

B. sla=30

C. sla=timedelta(minutes=30)

D. sla='00:30:00'

Solution

1. Step 1: Recall the correct data type for sla

   The sla parameter expects a datetime.timedelta object.

2. Step 2: Identify the correct syntax for 30 minutes timedelta

   timedelta(minutes=30) correctly creates a 30-minute duration.

3. Final Answer:

   sla=timedelta(minutes=30) -> Option C

4. Quick Check:

   sla uses timedelta object = B [OK]

Hint: Use timedelta for time durations in Airflow [OK]

Common Mistakes:

• Using string instead of timedelta
• Passing integer without timedelta
• Using incorrect string format

3. Given this DAG snippet, what will happen if task1 runs longer than 10 minutes?

from datetime import timedelta
from airflow import DAG
from airflow.operators.dummy import DummyOperator
from airflow.utils.dates import days_ago

def sla_miss_callback(dag, task_list, blocking_task_list, slas, session=None):
    print('SLA missed!')

dag = DAG('sla_example', start_date=days_ago(1))

task1 = DummyOperator(
    task_id='task1',
    dag=dag,
    sla=timedelta(minutes=10)
)

dag.sla_miss_callback = sla_miss_callback

medium

A. The sla_miss_callback function will print 'SLA missed!' when the SLA is missed.

B. Nothing happens because DummyOperator ignores SLA.

C. The task will automatically retry until it finishes within 10 minutes.

D. Airflow will fail the DAG immediately.

Solution

1. Step 1: Understand SLA miss callback usage

   The DAG-level sla_miss_callback is called when any task misses its SLA.

2. Step 2: Identify what the callback does

   The callback prints 'SLA missed!' when triggered by a task exceeding its SLA.

3. Final Answer:

   The sla_miss_callback function will print 'SLA missed!' when the SLA is missed. -> Option A

4. Quick Check:

   SLA miss triggers callback print = A [OK]

Hint: SLA miss triggers callback, not retries or failure [OK]

Common Mistakes:

• Thinking SLA causes retries automatically
• Assuming DummyOperator ignores SLA
• Believing DAG fails immediately on SLA miss

4. You wrote this code to notify on SLA misses but no notification happens:

def notify_sla_miss(dag, task_list, blocking_task_list, slas, session=None):
    send_email('[e-mail]', 'SLA Missed')

dag = DAG('sla_notify', start_date=days_ago(1), sla_miss_callback=notify_sla_miss)

task = DummyOperator(task_id='task', dag=dag, sla=timedelta(minutes=5))

What is the likely reason notifications are not sent?

medium

A. DummyOperator does not support SLA misses.

B. SLA miss callback must be set on the task, not the DAG.

C. The SLA time must be set in seconds, not minutes.

D. The send_email function is not defined or imported.

Solution

1. Step 1: Check the callback function implementation

   The callback calls send_email but no import or definition is shown.

2. Step 2: Understand Airflow's email sending

   Airflow requires proper email function or operator; undefined send_email causes failure silently.

3. Final Answer:

   The send_email function is not defined or imported. -> Option D

4. Quick Check:

   Undefined email function blocks notification = D [OK]

Hint: Ensure email functions are imported or use Airflow email operators [OK]

Common Mistakes:

• Setting callback on DAG instead of task (both valid but DAG preferred)
• Wrong SLA time units
• Assuming DummyOperator ignores SLA

5. You want to send a custom Slack message when any task misses its SLA in your DAG. Which approach correctly implements this?

hard

A. Set sla on tasks and add a SlackOperator as a downstream task to notify SLA misses.

B. Define a sla_miss_callback function that uses Slack API and assign it to the DAG's sla_miss_callback parameter.

C. Use on_failure_callback on tasks to send Slack messages when SLA is missed.

D. Configure Airflow to send Slack notifications by setting sla to the Slack channel name.

Solution

1. Step 1: Understand how SLA miss notifications work

   SLA misses trigger the sla_miss_callback function assigned to the DAG or task.

2. Step 2: Identify correct way to send Slack message on SLA miss

   Implement a callback function that calls Slack API and assign it to DAG's sla_miss_callback.

3. Final Answer:

   Define a sla_miss_callback function that uses Slack API and assign it to the DAG's sla_miss_callback parameter. -> Option B

4. Quick Check:

   SLA miss callback with Slack API = A [OK]

Hint: Use sla_miss_callback with Slack API for notifications [OK]

Common Mistakes:

• Using on_failure_callback instead of sla_miss_callback
• Trying to notify via downstream tasks
• Misconfiguring sla parameter as Slack channel