Airflow comes with a powerful Web UI that allows you to monitor, manage, and debug your workflows. The UI provides visibility into your DAGs, the ability to explore logs, and visualizations such as the Graph View and Tree View.

In this lesson, you’ll learn how to navigate the Airflow Web UI and use it to monitor your pipelines effectively.

Learning Objectives

By the end of this lesson, you will be able to:

  • Navigate the Airflow Web UI dashboard.

  • Enable, pause, and trigger DAGs from the UI.

  • Access task logs for debugging.

  • Use Graph View and Tree View to understand workflow dependencies.

1. Overview of the Airflow Web UI

  • The Web UI is the control center of Airflow.

  • It typically runs at: http://localhost:8080 (if running locally).

  • Main dashboard features:

    • 📂 List of all DAGs.

    • ▶️ Buttons to trigger or pause DAGs.

    • 🟢/🔴 Indicators showing DAG status (active/inactive).

2. DAG Management in the UI

  • Trigger DAG: Run a DAG immediately by clicking the ▶️ button.

  • Pause/Unpause: Temporarily disable a DAG from running on its schedule.

  • DAG Details: Clicking on a DAG name opens detailed views (Graph, Tree, Code, etc.).

3. Logs in the Web UI

  • Logs are essential for debugging tasks.

  • To view logs:

    1. Go to your DAG.

    2. Select a specific task run.

    3. Click Logs to see execution details.

  • Logs show:

    • Success or failure messages.

    • Python print outputs.

    • Errors and stack traces.

💡 Tip: Logs are stored locally or in remote storage (e.g., S3, GCS, Elasticsearch) depending on configuration.

4. Graph View

  • Graph View displays the DAG structure visually.

  • Boxes = tasks, Arrows = dependencies.

  • Colors indicate task state:

    • 🟢 Green → Success

    • 🔴 Red → Failed

    • 🟡 Yellow → Running

    • ⚪ White → Not yet run

Example:

 Extract → Transform → Load

👉 Graph View is useful for understanding workflow dependencies at a glance.

5. Tree View

  • Tree View shows DAG runs over time in a calendar-like format.

  • Each column = a DAG run.

  • Each row = a task in the DAG.

  • Colors show the status of each task per run.

👉 Tree View is excellent for spotting recurring failures or trends across multiple runs.

Lesson Summary

  • The Airflow Web UI is the main tool for managing and monitoring DAGs.

  • Use the dashboard to trigger, pause, and monitor DAGs.

  • Logs provide detailed task execution information.

  • Graph View shows dependencies; Tree View shows historical runs.

  • Together, these tools make it easier to monitor workflows and troubleshoot issues.

PreviousNext