Airflow Extension for Visual Studio Code
✅ Now works with Airflow 3.0
🤖 Chat with Airflow
A Visual Studio Code extension to interact with Apache Airflow (v2.x & v3.x) directly from your editor.
Trigger DAGs, pause/unpause, explore DAG runs, view logs, browse code, and more—no browser required.
🔑 Features
DAG List
- Browse all available DAGs in a tree view.
- Filter DAGs by name, owner, active/paused status, tags
- Add your favorite DAGs to favorites to quickly access them
- Add multiple Airflow Servers and switch between them
DAG Actions
- Trigger a DAG with optional config and date
- Pause, or unpause any DAG with a single click
- View source code running on Airflow
DAG Run Explorer
- View past & current DAG runs
- View logs
- See task instances, execution durations, and statuses
DAG Runs View
- Browse all DAG runs across all DAGs for a specific date
- Filter by status (success, failed, running, queued) and specific DAG ID
- See execution details: start date, duration, config, and notes
- Click on any DAG run to open detailed DagView for analysis
New Design & Experience
- Modern UI: Completely refreshed design for Admin and Report views with consistent theming
- Smart Log View: Enhanced log viewer integrated with AI for instant analysis
- Smart Controls: Context-aware Trigger/Cancel buttons that appear based on DAG state
- Navigation: Jump to any view using
@airflow commands
AI Airflow Assistant
- Get AI-powered assistance for analyzing DAG logs and troubleshooting issues
- Click "Ask AI" in the DagView to open the AI chat interface
- In the Chat, use
@airflow to ask questions and execute commands like triggering DAGs, pausing/unpausing, checking failed runs, and more
- AI analyzes DAG code and logs to provide insights and recommendations
- Integrated with VS Code's native chat interface for seamless interaction
- 24 language model tools for intelligent DAG control and monitoring: trigger runs, pause/unpause DAGs, check failed runs, analyze latest DAG execution, view run history, stop running DAGs, get source code, navigation, and more
- Use
@airflow in the chat to access all AI-powered tools
- Airflow Skills are available as a bundled set to help the assistant respond with consistent, task-focused guidance. Installing them improves accuracy and keeps responses aligned with Airflow best practices and this extension's workflows. You will see a prompt to install skills when you ask an AI question if you haven't installed them yet.
The extension provides 24 language model tools that integrate with VS Code's AI chat. Use @airflow in the chat to access these tools.
Trigger DAG Run
- Purpose: Execute a DAG with optional configuration
- Sample Prompts:
@airflow trigger data_pipeline_dag@airflow trigger etl_job_dag with config {"max_workers": 10}@airflow run my_dag on 2025-12-03
Pause DAG
- Purpose: Stop new DAG runs from being scheduled
- Sample Prompts:
@airflow pause data_pipeline_dag@airflow disable staging_etl_dag@airflow pause all failing dags
Unpause DAG
- Purpose: Enable scheduling for a paused DAG
- Sample Prompts:
@airflow unpause data_pipeline_dag@airflow activate my_dag@airflow resume production_job
Stop DAG Run
- Purpose: Terminate a currently running DAG execution
- Sample Prompts:
@airflow stop data_pipeline_dag run@airflow cancel current run of my_dag@airflow kill the running data_ingestion_dag
Get DAG Runs
- Purpose: View execution history for a specific DAG with optional date filter
- Sample Prompts:
@airflow get dag runs for api_data_ingestion_dag@airflow show runs of data_pipeline_dag on 2025-12-03@airflow list runs for etl_job_dag from last week
Get DAG History
- Purpose: View DAG run history on a specific date with status, duration, and notes
- Sample Prompts:
@airflow get dag history of api_data_ingestion_dag@airflow show history for data_pipeline_dag on 2025-12-02@airflow view past runs of my_dag today
Get Failed Runs
- Purpose: Identify and analyze failed DAG runs across the system
- Sample Prompts:
@airflow get failed runs@airflow show failed dags from last 24 hours@airflow which dags failed in the last 48 hours
List Active DAGs
- Purpose: View all currently enabled DAGs
- Sample Prompts:
@airflow list active dags@airflow show all running dags@airflow get enabled dags
List Paused DAGs
- Purpose: View all currently disabled DAGs
- Sample Prompts:
@airflow list paused dags@airflow show disabled dags@airflow get all paused dags
Get Running DAGs
- Purpose: List all DAGs that currently have running or queued tasks
- Sample Prompts:
@airflow get running dags@airflow get active runs@airflow what is running now?
Analyse DAG Latest Run
- Purpose: Comprehensive diagnostic report of the latest DAG execution including tasks, logs, and source code
- Sample Prompts:
@airflow analyze api_data_ingestion_dag@airflow get full diagnostics for data_pipeline_dag@airflow show latest execution details and logs for etl_job_dag@airflow what went wrong with my_dag last run
Get DAG Run Detail
- Purpose: Deep dive analysis of a specific DAG run ID
- Sample Prompts:
@airflow analyze run <run_id> of <dag_id>@airflow get run details for dag_id=my_dag run_id=manual__2023...
Get DAG Source Code
- Purpose: Retrieve and view the Python source code of a DAG
- Sample Prompts:
@airflow review source code for data_pipeline_dag@airflow show source code for data_pipeline_dag@airflow get code for my_etl_dag@airflow let me see the implementation of api_ingestion_dag
AI Chat Analysis
- Purpose: Get AI-powered insights and recommendations using all available tools
- Sample Prompts:
@airflow why is data_pipeline_dag failing? Analyze and show me the logs@airflow give me a summary of failed runs and recommend fixes@airflow check if my dags are healthy and pause any that keep failing
Open Views
- Purpose: Quickly navigate to any part of the extension using natural language
- Sample Prompts:
@airflow open log view for my_dag@airflow show me variables@airflow go to connections@airflow open provider list@airflow show server health
📷 Screenshots
| Daily Dag Runs |
Dag Run History |
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⚙️ Configuration
After installing the extension, you need to configure the extension to connect to your Airflow Server.
- Click 🔌 Connect to Airflow Server at the top of the extension sidebar.
- Enter your Airflow Server API Url
- Exp Airflow 2: http://localhost:8080/api/v1
- Exp Airflow 3: http://localhost:8080/api/v2
- Enter your Airflow username
- Enter your Airflow password
You can also add multiple Airflow Servers to connect to.
- Use [+] button to add a new Airflow Server
- Use [-] button to remove an Airflow Server
- Use [🔌] to switch between servers
ℹ️ To be able to connect an Airflow Server, you should enable Airflow Rest Api.
You can take a look the link below on how to do it.
https://airflow.apache.org/docs/apache-airflow/stable/security/api.html
🪲 Bug & New Feature Report
If you have an issue or new feature request, please click link below to add a new issue.
https://github.com/necatiarslan/airflow-vscode-extension/issues/new
💻 Local Airflow via Astronomer
Use Astro provided by the team who build Airflow
https://docs.astronomer.io/astro/cli/overview
To spin up a local Airflow instance for testing:
brew install astro #install cli tool from homebrew
astro dev init #init the local env
astro dev start #start airflow as a docker container
#Then you can connect your local airflow using the extension.
#airflow 2 url http://localhost:8080/api/v1
#airflow 3 url http://localhost:8080/api/v2
#user/pass admin/admin
📊 Telemetry & Privacy
This extension collects anonymous usage telemetry to help improve reliability and features.
Telemetry control
Telemetry is collected only if VS Code telemetry is enabled.
You can disable telemetry via: Settings → Telemetry → Telemetry Level
📝 Roadmap
Coming Soon
- Task View
- Instance Details
- Rendered Template
- Test Connection language model tool
- MCP for other Vscode Forks
- Integrate new Tree View API
- Add folders and notes to dags
- Add trigger config files
If you find this extension useful, please consider:
📬 Stay in Touch
Enjoy! 🚀
