# Learn documentation

> Learn Apache Airflow.

This documentation is also queryable through an MCP server at https://astronomer.io/docs/mcp, and any page is available as plain Markdown by appending .md to its URL.

## Versions

- [Learn Airflow 2](https://astronomer.io/docs/learn/2.x/llms.txt): 121 pages.

## Airflow 3 (current)

- [Learn Airflow 3](https://astronomer.io/docs/learn/overview.md): Use tutorials and concepts to learn everything you need to know about Apache Airflow® 3 and Astro
- [Introduction to data pipelines](https://astronomer.io/docs/learn/intro-to-data-pipelines.md): Learn what data pipelines are, how they work, and why they matter. Covers pipeline components, types, and best practices for building reliable data workflows.
- [Introduction to Apache Airflow®: A Technical Overview for Beginners](https://astronomer.io/docs/learn/intro-to-airflow.md): Start learning Apache Airflow with this comprehensive guide. Covers Dags, tasks, scheduling, and all core concepts. Includes code examples and links to relevant tutorials.
- [Apache Airflow® ETL Quickstart](https://astronomer.io/docs/learn/airflow-quickstart-etl.md): Build and run an ETL pipeline with Apache Airflow® and the Astro CLI in 15 minutes.
- [Apache Airflow® GenAI Quickstart](https://astronomer.io/docs/learn/airflow-quickstart-genai.md): Build and run a GenAI pipeline with Apache Airflow® and the Airflow AI SDK in 15 minutes.
- [Intro to Airflow tutorial: Get started and run your first pipeline](https://astronomer.io/docs/learn/get-started-with-airflow.md): A hands-on Airflow tutorial to help you run your first data pipeline. Learn core concepts and build ETL workflows with Apache Airflow in minutes.
- [Upgrade from Apache Airflow® 2 to 3](https://astronomer.io/docs/learn/airflow-upgrade-2-3.md): Learn how upgrade your Airflow 2 environment to Airflow 3.
- [Data engineering with AI](https://astronomer.io/docs/learn/local-data-engineering-with-ai-overview.md): Learn how to do local Airflow data engineering with AI tools.
- [Run Apache Airflow® locally](https://astronomer.io/docs/learn/run-airflow-locally.md): Run Apache Airflow® on your local computer with the Astro CLI.
- [Set up your IDE for data engineering](https://astronomer.io/docs/learn/set-up-your-ide-for-data-engineering.md): Set up your IDE for local Airflow data engineering with AI tools.
- [AI context for data engineering](https://astronomer.io/docs/learn/ai-context-for-data-engineering.md): Give AI tools the context they need to assist with Airflow data engineering.
- [Develop Apache Airflow® Dags with AI](https://astronomer.io/docs/learn/develop-dags-with-ai.md): Develop Apache Airflow® Dags locally with the help of AI agents.
- [Debug Apache Airflow® Dags with AI](https://astronomer.io/docs/learn/debug-dags-with-ai.md): Debug Apache Airflow® Dags locally with the help of AI agents.
- [An introduction to the Airflow UI](https://astronomer.io/docs/learn/airflow-ui.md): Explore the Airflow UI, which helps you monitor and troubleshoot your data pipelines. Learn about some of its key features and visualizations.
- [Basic asset-based scheduling in Apache Airflow®](https://astronomer.io/docs/learn/airflow-datasets.md): Using assets to schedule Dags based on successful completion of tasks.
- [Using the BashOperator](https://astronomer.io/docs/learn/bashoperator.md): Learn how to use the BashOperator to run bash commands and bash scripts. Review examples of how to run scripts in languages other than Python.
- [Manage connections in Apache Airflow](https://astronomer.io/docs/learn/connections.md): Learn how to set up, manage, and maintain different types of connections in Apache Airflow. Use example connection configurations as the basis for your own connections.
- [Introduction to Apache Airflow® Dags](https://astronomer.io/docs/learn/dags.md): Learn how to write Dags and get tips on how to define an Apache Airflow® Dag in Python. Learn all about Dag parameters and their settings.
- [Using Airflow to Execute SQL](https://astronomer.io/docs/learn/airflow-sql.md): Learn the best practices for executing SQL from your DAG. Get to know Airflow’s SQL-related operators and see how to use Airflow for common SQL use cases.
- [Airflow hooks](https://astronomer.io/docs/learn/what-is-a-hook.md): Learn about hooks and how they should be used in Apache Airflow. See an example of implementing two different hooks in a DAG.
- [Manage Airflow code](https://astronomer.io/docs/learn/managing-airflow-code.md): Learn best practices for Airflow project organization, such as when to separate out DAGs into multiple projects and how to manage code used across different projects.
- [Airflow operators](https://astronomer.io/docs/learn/what-is-an-operator.md): Learn the basics of operators, which are the building blocks of Airflow DAGs.
- [Schedule DAGs in Apache Airflow®](https://astronomer.io/docs/learn/scheduling-in-airflow.md): Get to know Airflow scheduling concepts and different ways to schedule a DAG.
- [Airflow sensors](https://astronomer.io/docs/learn/what-is-a-sensor.md): Get an overview of Airflow sensors and learn best practices for implementing sensors in production.
- [Manage task and task group dependencies in Airflow](https://astronomer.io/docs/learn/managing-dependencies.md): Learn how to manage dependencies between tasks and TaskGroups in Apache Airflow, including how to set dynamic dependencies.
- [Apache Airflow® trigger rules](https://astronomer.io/docs/learn/airflow-trigger-rules.md): Learn about available trigger rules and how to use them.
- [Use Airflow variables](https://astronomer.io/docs/learn/airflow-variables.md): Create and use Airflow variables.
- [Access the Apache Airflow context](https://astronomer.io/docs/learn/airflow-context.md): Access the Airflow context in your tasks.
- [Introduction to the TaskFlow API and Airflow decorators](https://astronomer.io/docs/learn/airflow-decorators.md): An overview of Airflow decorators and how they can improve the DAG authoring experience.
- [Manage Apache Airflow® Dag notifications](https://astronomer.io/docs/learn/error-notifications-in-airflow.md): Master the basics of Apache Airflow® notifications. Learn how to set up automatic email and Slack notifications to be alerted of events in your Dags.
- [Create and use params in Airflow](https://astronomer.io/docs/learn/airflow-params.md): Create and use DAG and task-level params in Airflow.
- [Branching in Airflow](https://astronomer.io/docs/learn/airflow-branch-operator.md): Learn about Airflow's multiple options for building conditional logic and branching within DAGs, including the BranchPythonOperator and ShortCircuitOperator.
- [Cross-DAG dependencies](https://astronomer.io/docs/learn/cross-dag-dependencies.md): How to implement dependencies between your Airflow DAGs.
- [Custom hooks and operators](https://astronomer.io/docs/learn/airflow-importing-custom-hooks-operators.md): How to correctly import custom hooks and operators.
- [DAG writing best practices in Apache Airflow](https://astronomer.io/docs/learn/dag-best-practices.md): Keep up to date with the best practices for developing efficient, secure, and scalable DAGs using Airflow. Learn about DAG design and data orchestration.
- [DAG-level parameters in Airflow](https://astronomer.io/docs/learn/airflow-dag-parameters.md): Learn about all important DAG-level parameters in Airflow.
- [Dag Versioning and Dag Bundles](https://astronomer.io/docs/learn/airflow-dag-versioning.md): Learn how the Dag versioning feature functions and how to configure a versioned Dag bundle.
- [Debug DAGs](https://astronomer.io/docs/learn/debugging-dags.md): Troubleshoot Airflow DAGs
- [Create dynamic Airflow tasks](https://astronomer.io/docs/learn/dynamic-tasks.md): How to dynamically create tasks at runtime in your Airflow DAGs.
- [Use Airflow templates](https://astronomer.io/docs/learn/templating.md): Learn about Jinja templating in Apache Airflow and see examples of how to pass dynamic information into task instances at runtime.
- [Pass data between tasks](https://astronomer.io/docs/learn/airflow-passing-data-between-tasks.md): Learn more about the most common methods to implement data sharing between your Airflow tasks, including an in-depth explanation of XCom.
- [Rerun Airflow Dags and tasks](https://astronomer.io/docs/learn/rerunning-dags.md): How to configure retries, catchup, backfill, and clear task instances in Airflow.
- [Airflow task groups](https://astronomer.io/docs/learn/task-groups.md): Follow Astronomer’s step-by-step guide to use task groups for organizing tasks within the grid view of the Airflow user interface.
- [Apache Airflow® components](https://astronomer.io/docs/learn/airflow-components.md): Understand the core components of Apache Airflow®. Review their functions and find out which components to run for specific use cases.
- [Understanding the Airflow metadata database](https://astronomer.io/docs/learn/airflow-database.md): Learn about everything you need to use the Apache Airflow metadata database.
- [Apache Airflow® Executors](https://astronomer.io/docs/learn/airflow-executors-explained.md): An introduction to Apache Airflow® Executors
- [Scaling Airflow to optimize performance](https://astronomer.io/docs/learn/airflow-scaling-workers.md): See which parameters to modify when scaling up data pipelines to make the most of Airflow. Learn about the environment, DAG, and task-level settings.
- [Airflow cluster policies](https://astronomer.io/docs/learn/airflow-advanced-cluster-policies.md): Learn about everything you need to use the Apache Airflow cluster policies.
- [Best practices for orchestrating MLOps pipelines with Airflow](https://astronomer.io/docs/learn/airflow-mlops.md): Learn how to use Airflow to run machine learning in production.
- [Airflow plugins](https://astronomer.io/docs/learn/using-airflow-plugins.md): How to use Airflow plugins.
- [Airflow pools](https://astronomer.io/docs/learn/airflow-pools.md): Use pools to control Airflow task parallelism.
- [Advanced asset-based scheduling in Apache Airflow®](https://astronomer.io/docs/learn/airflow-advanced-asset-scheduling.md): Using assets to implement DAG dependencies and scheduling in Airflow.
- [@asset syntax in Apache Airflow®](https://astronomer.io/docs/learn/airflow-asset-decorator.md): Using the @asset decorator to create a Dag with one task that updates an asset.
- [Running asynchronous processes in Apache Airflow®](https://astronomer.io/docs/learn/deferrable-operators.md): Run asynchronous Python in Airflow tasks and use deferrable operators to free up worker resources.
- [Strategies for custom XCom backends in Airflow](https://astronomer.io/docs/learn/custom-xcom-backend-strategies.md): Use this guide to learn about different ways you can set up custom XCom backends.
- [Event-driven scheduling](https://astronomer.io/docs/learn/airflow-event-driven-scheduling.md): Learn how schedule DAGs based on messages in a message queue.
- [Human-in-the-loop workflows with Airflow](https://astronomer.io/docs/learn/airflow-human-in-the-loop.md): Learn how include humans in your Dags with the human-in-the-loop feature.
- [Run tasks in an isolated environment in Apache Airflow](https://astronomer.io/docs/learn/airflow-isolated-environments.md): Learn how to run an Airflow task in an isolated environment.
- [Use the KubernetesPodOperator](https://astronomer.io/docs/learn/kubepod-operator.md): Use the KubernetesPodOperator in Airflow to run tasks in Kubernetes Pods
- [Airflow logging](https://astronomer.io/docs/learn/logging.md): An introduction to Airflow logging.
- [Run Airflow tasks in other languages](https://astronomer.io/docs/learn/airflow-multilanguage.md): Learn how to run Airflow tasks in languages other than Python.
- [Partitioned Dag runs and asset events in Apache Airflow®](https://astronomer.io/docs/learn/airflow-partitioned-runs.md): Partition Dag runs and asset events in Airflow.
- [Dynamically generate DAGs in Airflow](https://astronomer.io/docs/learn/dynamically-generating-dags.md): Get to know the best ways to dynamically generate DAGs in Apache Airflow. Use examples to generate DAGs using single- and multiple-file methods.
- [Use setup and teardown tasks in Airflow](https://astronomer.io/docs/learn/airflow-setup-teardown.md): Learn how to use setup and teardown tasks to manage task resources in Airflow.
- [How to share code between multiple Airflow projects](https://astronomer.io/docs/learn/sharing-code-multiple-projects.md): A description of the various ways to reuse and share code between multiple projects, with pros and cons of each solution.
- [Synchronous Dag execution](https://astronomer.io/docs/learn/airflow-synchronous-dag-execution.md): Learn about synchronous Dag execution in Airflow.
- [Task state store in Apache Airflow®](https://astronomer.io/docs/learn/airflow-task-state-store.md): Learn how to save information persisting between task retries in Airflow.
- [Test Airflow DAGs](https://astronomer.io/docs/learn/testing-airflow.md): Learn about testing Airflow DAGs and gain insight into various types of tests — validation testing, unit testing, and data and pipeline integrity testing.
- [Set up a custom XCom backend using object storage](https://astronomer.io/docs/learn/custom-xcom-backends-tutorial.md): Use this tutorial to learn how to set up a custom XCom backend with object storage.
- [Set up Remote Execution Agents on Astro](https://astronomer.io/docs/learn/astro-remote-execution.md): Learn how to set up Remote Execution on Astro.
- [Clean up the Airflow metadata database using Dags](https://astronomer.io/docs/learn/cleanup-dag-tutorial.md): Learn how to remove unnecessary data from the Airflow metadata database by calling an Airflow Plugin from a Dag.
- [Use a listener to send a Slack notification when a dataset is updated](https://astronomer.io/docs/learn/airflow-listeners.md): Learn how to use Airflow listeners.
- [Airflow otto rca auto fix](https://astronomer.io/docs/learn/airflow-otto-rca-auto-fix.md)
- [Microsoft Teams notifications](https://astronomer.io/docs/learn/example-ms-teams-callback.md): Configure notifications in Microsoft teams for DAG runs and tasks using Airflow callbacks.
- [Use Airflow object storage to interact with cloud storage in an ML pipeline](https://astronomer.io/docs/learn/airflow-object-storage-tutorial.md): Learn how to use Airflow object storage.
- [Blueprint: A Dag writing abstraction with a no-code interface in the Astro IDE](https://astronomer.io/docs/learn/blueprint-overview.md): Learn about blueprint, a template-based system for composing Apache Airflow Dags from reusable Python templates and YAML configuration.
- [How to use blueprint on Astro to write Apache Airflow® Dags in a no-code interface](https://astronomer.io/docs/learn/blueprint-user-tutorial.md): Learn how to build data pipelines from pre-built templates using the Blueprint visual builder in the Astro IDE.
- [How to write blueprint templates](https://astronomer.io/docs/learn/blueprint-writer-tutorial.md): Learn how to define reusable blueprint templates in Python and compose them into Apache Airflow Dags using YAML.
- [Create DAG documentation in Apache Airflow](https://astronomer.io/docs/learn/custom-airflow-ui-docs-tutorial.md): Use Apache Airflow's built-in documentation features to generate documentation for your DAGs in the Airflow UI.
- [Use DAG Factory to create dags](https://astronomer.io/docs/learn/dag-factory.md): Learn how to dynamically convert YAML files into Apache Airflow® dags with DAG Factory, an open source project that makes creating dags easy.
- [Run data quality checks using SQL check operators](https://astronomer.io/docs/learn/airflow-sql-data-quality.md): Learn how to use the SQLColumnCheckOperator, SQLTableCheckOperator and SQLCheckOperator.
- [Orchestrate Ray jobs on Anyscale with Apache Airflow®](https://astronomer.io/docs/learn/airflow-anyscale.md): Learn how to use the Anyscale provider package to orchestrate Ray jobs on Anyscale with Apache Airflow®.
- [Create an Azure Blob Storage connection in Airflow](https://astronomer.io/docs/learn/connections/azure-blob-storage.md): Learn how to create an Azure Blob Storage connection in Airflow.
- [Run a task in Azure Container Instances with Airflow](https://astronomer.io/docs/learn/airflow-azure-container-instances.md): Learn how to orchestrate containers with Azure Container Instances from your Airflow DAGs.
- [Run Azure Data Factory pipelines with Airflow](https://astronomer.io/docs/learn/airflow-azure-data-factory-integration.md): Learn how to orchestrate remote jobs in Azure Data Factory with your Apache Airflow DAGs.
- [Create a BigQuery connection in Airflow](https://astronomer.io/docs/learn/connections/bigquery.md): Learn how to create a BigQuery connection in Airflow.
- [Orchestrate Cohere LLMs with Apache Airflow](https://astronomer.io/docs/learn/airflow-cohere.md): Learn how to integrate Cohere and Airflow.
- [Orchestrate AI tasks with Apache Airflow® and the Common AI provider](https://astronomer.io/docs/learn/airflow-common-ai-provider.md): Use the Common AI provider to add AI-based tasks to your Dags, including AI agents with access to Airflow-based tools.
- [Create a Databricks connection in Airflow](https://astronomer.io/docs/learn/connections/databricks.md): Learn how to create a Databricks connection in Airflow.
- [Tutorial: How to Orchestrate Databricks Jobs with Airflow](https://astronomer.io/docs/learn/airflow-databricks.md): Step-by-step guide to orchestrating Databricks with Airflow. Learn to trigger notebooks, run jobs, and build data pipelines. Includes example Dag code.
- [Orchestrate dbt Core projects with Airflow and Cosmos](https://astronomer.io/docs/learn/airflow-dbt.md): Learn how to use Cosmos to orchestrate dbt Core projects with Airflow.
- [Create a dbt Cloud connection in Airflow](https://astronomer.io/docs/learn/connections/dbt-cloud.md): Learn how to create a dbt Cloud connection in Airflow.
- [Orchestrate dbt Cloud jobs with Airflow](https://astronomer.io/docs/learn/airflow-dbt-cloud.md): Learn how to use the dbt Cloud Provider to orchestrate dbt Cloud jobs with Airflow.
- [Use DuckDB with Apache Airflow](https://astronomer.io/docs/learn/airflow-duckdb.md): Learn how to use DuckDB with Airflow.
- [Create a Microsoft Entra Workload ID connection in Airflow](https://astronomer.io/docs/learn/connections/entra-workload-identity.md): Learn how to create an Azure Workload Identity connection in Airflow.
- [Execute a Jupyter notebook with Airflow](https://astronomer.io/docs/learn/execute-notebooks.md): Run a parameterized Jupyter notebook using Airflow and the Astro CLI.
- [Use Fivetran with Apache Airflow](https://astronomer.io/docs/learn/airflow-fivetran.md): Learn how to orchestrate Fivetran syncs using Airflow
- [Orchestrate Great Expectations with Airflow](https://astronomer.io/docs/learn/airflow-great-expectations.md): Orchestrate Great Expectations data quality checks with your Airflow Dags.
- [Use Apache Kafka with Apache Airflow](https://astronomer.io/docs/learn/airflow-kafka.md): How to produce to and consume from Kafka topics using the Kafka Airflow provider
- [Integrate OpenLineage and Airflow with Marquez](https://astronomer.io/docs/learn/marquez.md): Use OpenLineage and Marquez to get lineage metadata locally from your Airflow DAGs.
- [Orchestrate MongoDB operations with Apache Airflow](https://astronomer.io/docs/learn/airflow-mongodb.md): Learn how to load vector embeddings into MongoDB with Apache Airflow.
- [Create a Microsoft SQL Server connection in Airflow](https://astronomer.io/docs/learn/connections/ms-sqlserver.md): Learn how to create a Microsoft SQL Server connection in Airflow.
- [Orchestrate OpenAI operations with Apache Airflow](https://astronomer.io/docs/learn/airflow-openai.md): Learn how to integrate OpenAI and Airflow.
- [Orchestrate OpenSearch operations with Apache Airflow](https://astronomer.io/docs/learn/airflow-opensearch.md): Learn how to integrate OpenSearch and Airflow.
- [Orchestrate pgvector operations with Apache Airflow](https://astronomer.io/docs/learn/airflow-pgvector.md): Learn how to integrate pgvector and Airflow.
- [Orchestrate Pinecone operations with Apache Airflow](https://astronomer.io/docs/learn/airflow-pinecone.md): Learn how to integrate Pinecone and Airflow.
- [Create a PostgreSQL connection in Airflow](https://astronomer.io/docs/learn/connections/postgres.md): Learn how to create a PostgreSQL connection in Airflow.
- [Orchestrate semantic querying in Qdrant with Airflow](https://astronomer.io/docs/learn/airflow-qdrant.md): Learn how to integrate Qdrant and Airflow.
- [Orchestrate Ray jobs with Apache Airflow®](https://astronomer.io/docs/learn/airflow-ray.md): Learn how to use the Ray provider package to orchestrate Ray jobs with Apache Airflow®.
- [Create a Redshift connection in Airflow](https://astronomer.io/docs/learn/connections/redshift.md): Learn how to create a Redshift connection in Airflow.
- [Orchestrate Redshift operations with Airflow](https://astronomer.io/docs/learn/airflow-redshift.md): Orchestrate Redshift queries from your Airflow DAGs.
- [Train a machine learning model with SageMaker and Airflow](https://astronomer.io/docs/learn/airflow-sagemaker.md): Follow a step-by-step tutorial for using Airflow to orchestrate the training and testing of a SageMaker model.
- [Create a Snowflake Connection in Airflow](https://astronomer.io/docs/learn/connections/snowflake.md): Learn how to create a Snowflake connection in Airflow.
- [Orchestrate Snowflake Queries with Airflow](https://astronomer.io/docs/learn/airflow-snowflake.md): Get enhanced observability and compute savings while orchestrating Snowflake jobs from your Airflow DAGs.
- [Orchestrate Snowpark Machine Learning Workflows with Apache Airflow](https://astronomer.io/docs/learn/airflow-snowpark.md): Learn how to integrate Snowpark and Airflow.
- [Run Soda Core checks with Airflow](https://astronomer.io/docs/learn/soda-data-quality.md): Learn how to orchestrate Soda Core data quality checks with your Airflow DAGs.
- [Orchestrate Weaviate operations with Apache Airflow](https://astronomer.io/docs/learn/airflow-weaviate.md): Learn how to integrate Weaviate and Airflow.
- [Manage your ML models with Weights and Biases and Airflow](https://astronomer.io/docs/learn/airflow-weights-and-biases.md): Learn how to use Airflow and Weights and Biases to manage and visualize your ML model lifecycle.
- [ELT with BigQuery, dbt, and Apache Airflow® for eCommerce](https://astronomer.io/docs/learn/reference-architecture-elt-bigquery-dbt.md): Learn how to build an end-to-end ELT pipeline with Apache Airflow®, BigQuery, and dbt Core.
- [ELT with Snowflake and Apache Airflow® for eCommerce](https://astronomer.io/docs/learn/reference-architecture-elt-snowflake.md): Learn how to build an end-to-end ELT pipeline with Apache Airflow® and Snowflake.
- [ETL with DuckDB and Apache Airflow® for travel analytics](https://astronomer.io/docs/learn/reference-architecture-etl-duckdb.md): Learn how to build an ETL pipeline with Apache Airflow®, DuckDB, and built-in data quality gates.
- [ELT with Apache Airflow® and Databricks](https://astronomer.io/docs/learn/use-case-airflow-databricks.md): Use Airflow to orchestrate data loading and transformation in Databricks.
- [Integration patterns for Apache Kafka® and Apache Airflow®](https://astronomer.io/docs/learn/reference-architecture-kafka.md): Learn how to integrate Apache Kafka® with Apache Airflow® for real-time event processing using event-driven scheduling and the Airflow Kafka provider.
- [Context graphs for self-improving AI Agents with Apache Airflow®](https://astronomer.io/docs/learn/reference-architecture-context-graph.md): Learn how to build a context graph architecture that captures business decision traces and makes them available to AI agents as institutional memory.
- [Hybrid Search for eCommerce reference architecture](https://astronomer.io/docs/learn/reference-architecture-hybrid-search.md): Learn how to build a hybrid search application with Apache Airflow® and Weaviate.
- [Batch inference for product insights with Apache Airflow®](https://astronomer.io/docs/learn/reference-architecture-product-insights.md): Learn how to build a batch inference pipeline with Apache Airflow® and OpenAI.
- [Processing User Feedback: an LLM-fine-tuning reference architecture with Ray on Anyscale](https://astronomer.io/docs/learn/reference-architecture-fine-tuning-anyscale.md): Learn how to fine-tune an LLM to process and categorize user feedback with Airflow and Ray on Anyscale.
- [AI-powered education operations with Apache Airflow®](https://astronomer.io/docs/learn/reference-architecture-ai-education-operations.md): Learn how to build an event-driven, multi-agent AI system that automates ticket processing, customer reporting, and conversational data queries using Apache Airflow.
- [SnowPatrol: Snowflake Usage Anomaly Detection & Alerting System](https://astronomer.io/docs/learn/reference-architecture-snowpatrol.md): Learn how to build an anomaly detection system for Snowflake with Apache Airflow®.
- [Get started with Astro Observe](https://astronomer.io/docs/learn/astro-observe-quickstart.md): Learn how to get started with Astro Observe
- [How data products translate pipelines into business value](https://astronomer.io/docs/learn/data-products.md): Understand data products and how observability transforms invisible data work into measurable business value.
- [Data quality and Airflow](https://astronomer.io/docs/learn/data-quality.md): Check the quality of your data using Airflow, Astro Observe, and third-party frameworks.
- [Integrate OpenLineage and Airflow](https://astronomer.io/docs/learn/airflow-openlineage.md): Learn about OpenLineage concepts and benefits of integrating with Airflow.
- [Implementing proactive alerting](https://astronomer.io/docs/learn/proactive-alerting.md): Learn about implementing proactive alerting as part of your observability solution.
- [Leverage SLAs for enhanced data quality monitoring](https://astronomer.io/docs/learn/using-slas.md): Learn about use cases and best practices for SLAs.
- [Glossary](https://astronomer.io/docs/learn/glossary.md): A list of key Apache Airflow, observability, and other data terms and definitions that can help you learn important concepts.