UI / Screenshots¶
The Airflow UI makes it easy to monitor and troubleshoot your data pipelines. Here’s a quick overview of some of the features and visualizations you can find in the Airflow UI.
DAGs View¶
List of the DAGs in your environment, and a set of shortcuts to useful pages. You can see exactly how many tasks succeeded, failed, or are currently running at a glance. To hide completed tasks set show_recent_stats_for_completed_runs = False
In order to filter DAGs (e.g by team), you can add tags in each dag. The filter is saved in a cookie and can be reset by the reset button. For example:
dag = DAG("dag", tags=["team1", "sql"])
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Grid View¶
A bar chart and grid representation of the DAG that spans across time. The top row is a chart of DAG Runs by duration, and below, task instances. If a pipeline is late, you can quickly see where the different steps are and identify the blocking ones.
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The details panel will update when selecting a DAG Run by clicking on a duration bar:
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Or selecting a Task Instance by clicking on a status box:
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Manual runs are indicated by a play icon (just like the Trigger DAG button):
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Task groups are indicated by a caret and can be opened or closed:
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Mapped Tasks are indicated by a square brackets and will show a table of each mapped task instance in the details panel:
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Graph View¶
The graph view is perhaps the most comprehensive. Visualize your DAG’s dependencies and their current status for a specific run.
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Calendar View¶
The calendar view gives you an overview of your entire DAG’s history over months, or even years. Letting you quickly see trends of the overall success/failure rate of runs over time.
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Variable View¶
The variable view allows you to list, create, edit or delete the key-value pair of a variable used during jobs. Value of a variable will be hidden if the key contains any words in (‘password’, ‘secret’, ‘passwd’, ‘authorization’, ‘api_key’, ‘apikey’, ‘access_token’) by default, but can be configured to show in clear-text. See Masking sensitive data.
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Gantt Chart¶
The Gantt chart lets you analyse task duration and overlap. You can quickly identify bottlenecks and where the bulk of the time is spent for specific DAG runs.
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Task Duration¶
The duration of your different tasks over the past N runs. This view lets you find outliers and quickly understand where the time is spent in your DAG over many runs.
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Code View¶
Transparency is everything. While the code for your pipeline is in source control, this is a quick way to get to the code that generates the DAG and provide yet more context.
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