Debugging with Airflow CLI - Practice Problems & Coding Challenges

Challenge - 5 Problems

💻 Command Output

intermediate

Check DAG Run Status

You run the command airflow dags state example_dag 2023-06-01T00:00:00+00:00. What is the expected output if the DAG run succeeded?

A success

B failed

C running

D queued

💡 Hint

The command shows the state of a specific DAG run at the given execution date.

The airflow dags state command returns the state of the DAG run. If it succeeded, the output is exactly 'success'.

💻 Command Output

intermediate

Task Instance Log Retrieval

What output do you get when running airflow tasks logs example_dag example_task 2023-06-01T00:00:00+00:00 if the log file for that task instance does not exist?

A Task instance logs displayed successfully

B No logs found for task instance example_task on 2023-06-01T00:00:00+00:00

C FileNotFoundError: [Errno 2] No such file or directory

D Permission denied error

💡 Hint

Airflow CLI handles missing logs gracefully with a message.

If the log file is missing, Airflow CLI prints a friendly message indicating no logs found rather than a Python error.

🔀 Workflow

advanced

Order of Commands to Debug a Failed Task

Arrange the following Airflow CLI commands in the correct order to debug a failed task instance:

A 3,1,4,2

B 4,3,1,2

C 3,4,1,2

D 1,2,3,4

💡 Hint

Start by confirming the DAG exists, then list tasks, check task state, then view logs.

First list DAGs to confirm the DAG exists (3), then list tasks in the DAG (4), check the task state (1), and finally view logs for details (2).

❓ Troubleshoot

advanced

Identifying Cause of CLI Connection Error

You run airflow dags list but get the error: ConnectionRefusedError: [Errno 111] Connection refused. What is the most likely cause?

A Airflow webserver is not running

B Airflow scheduler is not running

C Airflow CLI is outdated

D Airflow metadata database is down

💡 Hint

The CLI connects to the metadata database to list DAGs.

The CLI needs to connect to the metadata database. If the database is down or unreachable, it raises ConnectionRefusedError.

✅ Best Practice

expert

Best Practice for Debugging Task Failures Using Airflow CLI

Which of the following is the best practice when using Airflow CLI to debug a task failure in production?

A Check the task instance state, then review logs before deciding to clear or rerun

B Directly clear the failed task instance using <code>airflow tasks clear</code> without checking logs

C Restart the entire Airflow scheduler to fix task failures

D Ignore CLI and only use the Airflow web UI for debugging

💡 Hint

Good debugging means understanding the failure before acting.

The best practice is to first check the task state and logs to understand the failure cause before clearing or rerunning tasks.