Airflow UI overview - Commands & Configuration

Introduction

Airflow UI helps you see and control your workflows easily. It shows what tasks are running, finished, or failed, so you can fix problems fast.

When you want to check if your scheduled tasks ran successfully today.

When you need to restart a failed task without running the whole workflow again.

When you want to see the order and timing of tasks in your workflow.

When you want to pause or resume a workflow temporarily.

When you want to view logs to understand why a task failed.

Commands

Starts the Airflow webserver on port 8080 so you can open the UI in your browser.

Terminal

airflow webserver --port 8080

Expected Output

[2024-06-01 12:00:00,000] {webserver.py:123} INFO - Starting Airflow webserver on port 8080

[2024-06-01 12:00:00,500] {webserver.py:130} INFO - Airflow webserver running

→

--port 8080 - Sets the port number where the UI will be accessible

Opens the Airflow UI in your default web browser to interact with your workflows visually.

Terminal

open http://localhost:8080

Expected Output

No output (command runs silently)

Lists all the workflows (DAGs) Airflow knows about, so you can see what is available to run or monitor.

Terminal

airflow dags list

Expected Output

example_dag

my_data_pipeline

send_reports

Shows all tasks inside the example_dag workflow, helping you understand its steps.

Terminal

airflow tasks list example_dag

Expected Output

task_1

task_2

task_3

Key Concept

If you remember nothing else from this pattern, remember: The Airflow UI is your control center to watch, manage, and troubleshoot your workflows easily.

Common Mistakes

Trying to open the UI before starting the webserver

The UI won't load because the webserver that serves it is not running.

Always start the Airflow webserver first with 'airflow webserver --port 8080' before opening the UI.

Not checking task logs when a task fails

Without logs, you won't know why the task failed and can't fix the issue.

Use the UI to open task logs and read error messages to troubleshoot.

Summary

Start the Airflow webserver to access the UI on a web browser.

Use the UI to view workflows (DAGs) and their tasks visually.

Check task status and logs in the UI to monitor and troubleshoot workflows.

Practice

1. What is the primary purpose of the Airflow UI?

easy

A. To store data files for workflows

B. To write Python code for tasks

C. To monitor and manage workflows visually

D. To configure network settings

Solution

1. Step 1: Understand Airflow UI role

   The Airflow UI is designed as a web interface to help users see and control workflows easily.

2. Step 2: Identify main function

   It shows task status, logs, and workflow structure, making monitoring and management simple.

3. Final Answer:

   To monitor and manage workflows visually -> Option C

4. Quick Check:

   Airflow UI = Monitor & Manage Workflows [OK]

Hint: Airflow UI is for watching workflows, not coding [OK]

Common Mistakes:

• Confusing UI with coding environment
• Thinking UI stores data files
• Assuming UI manages network

2. Which section in the Airflow UI shows the status of each task in a workflow?

easy

A. Admin panel

B. DAGs tab

C. Logs tab

D. Graph view

Solution

1. Step 1: Identify UI sections

   The Graph view in Airflow UI visually displays tasks and their statuses in a workflow.

2. Step 2: Compare other options

   DAGs tab lists workflows, Logs tab shows task logs, Admin panel manages users/settings.

3. Final Answer:

   Graph view -> Option D

4. Quick Check:

   Task status = Graph view [OK]

Hint: Task status is shown in Graph view, not Logs [OK]

Common Mistakes:

• Confusing Logs tab with task status
• Thinking DAGs tab shows task details
• Assuming Admin panel shows task status

3. If a task in Airflow UI shows a red color in the Graph view, what does it mean?

medium

A. Task failed

B. Task is running

C. Task succeeded

D. Task is skipped

Solution

1. Step 1: Understand color codes in Graph view

   In Airflow UI, red color indicates a failed task.

2. Step 2: Recall other colors meaning

   Green means success, yellow means running, grey means skipped.

3. Final Answer:

   Task failed -> Option A

4. Quick Check:

   Red = Failed task [OK]

Hint: Red means failure in Airflow UI Graph view [OK]

Common Mistakes:

• Mixing red with running or success
• Confusing skipped with failed
• Ignoring color legend in UI

4. You notice that the Logs tab in Airflow UI shows no logs for a task that ran. What is the likely cause?

medium

A. Task never started or failed before logging

B. Logs tab is broken and needs UI restart

C. Task succeeded without logs

D. Logs are stored in a different UI section

Solution

1. Step 1: Analyze missing logs scenario

   If no logs appear, usually the task did not start or failed before producing logs.

2. Step 2: Eliminate other options

   Logs tab usually works; success tasks still have logs; logs are not in other UI sections.

3. Final Answer:

   Task never started or failed before logging -> Option A

4. Quick Check:

   No logs = Task not started or early failure [OK]

Hint: No logs usually means task didn't start properly [OK]

Common Mistakes:

• Assuming UI bug without checking task status
• Thinking success tasks have no logs
• Looking for logs in wrong UI tabs

5. You want to quickly check the order of tasks and their dependencies in a DAG using the Airflow UI. Which view should you use and why?

hard

A. Tree view, because it shows tasks in a timeline with dependencies

B. Graph view, because it visually displays tasks and their dependencies

C. Calendar view, because it shows task schedules

D. Code view, because it shows the Python code defining tasks

Solution

1. Step 1: Identify views for task order and dependencies

   The Graph view visually shows tasks as nodes connected by arrows representing dependencies.

2. Step 2: Compare other views

   Tree view shows task runs over time, Code view shows code but not visual dependencies, Calendar shows schedules.

3. Final Answer:

   Graph view, because it visually displays tasks and their dependencies -> Option B

4. Quick Check:

   Task order & dependencies = Graph view [OK]

Hint: Use Graph view to see task dependencies clearly [OK]

Common Mistakes:

• Confusing Tree view with dependency graph
• Looking at code instead of visual graph
• Using Calendar view for dependencies