Apache Airflow Best Practices equips data professionals with the skills to master Airflow, from foundational concepts to advanced deployment strategies. This course is essential for those wanting to build scalable data pipelines, optimize workflows, and leverage Airflow in cloud environments.
Apache Airflow Best Practices
Apache Airflow Best Practices
Instructor: Packt - Course Instructors
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Explore the new features and improvements in Apache Airflow 2.0
Design and build scalable data pipelines using DAGs
Implement ETL pipelines, ML workflows, and advanced orchestration strategies
Skills you'll gain
- MLOps (Machine Learning Operations)
- Business Workflow Analysis
- System Monitoring
- Data Pipelines
- Configuration Management
- Apache Airflow
- Multi-Tenant Cloud Environments
- DevOps
- Python Programming
- Devops Tools
- CI/CD
- Workflow Management
- Cloud Deployment
- Scalability
- Performance Tuning
- Continuous Deployment
- Skills section collapsed. Showing 8 of 16 skills.
Details to know
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Assessments
13 assignments
Taught in English
Recently updated!
December 2025
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There are 13 modules in this course
In this section, we explore data orchestration fundamentals, Airflow 2.0 features, and best practices for building scalable pipeline solutions.
What's included
2 videos2 readings1 assignment
In this section, we explore Apache Airflow's core concepts, including DAGs, task groups, and triggers, and how to implement them for efficient workflow automation and optimization.
What's included
1 video4 readings1 assignment
In this section, we explore Airflow components, their roles, and how to select and optimize executors for efficient workflow orchestration and scalability.
What's included
1 video4 readings1 assignment
In this section, we explore Airflow DAG authoring for API data extraction, focusing on task design with operators and workflow optimization for efficient data pipelines.
What's included
1 video4 readings1 assignment
In this section, we explore connecting Apache Airflow to external sources, designing DAGs with failure alerts, and managing secrets securely for efficient workflow automation.
What's included
1 video4 readings1 assignment
In this section, we cover creating Airflow UI plugins for custom workflow monitoring using Flask blueprints and metrics dashboards.
What's included
1 video1 reading1 assignment
In this section, we explore creating and distributing custom Airflow providers, focusing on structured packaging, testing, and reusable code for scalable workflow automation.
What's included
1 video3 readings1 assignment
In this section, we explore orchestrating machine learning workflows, focusing on DAG design, implementation, and MLOps practices for operational model deployment and performance analysis.
What's included
1 video2 readings1 assignment
In this section, we explore abstracting Airflow workflows to enable non-technical users to create and manage tasks. Key concepts include templated DAGs, workflow scheduling, and simplified orchestration for improved collaboration.
What's included
1 video2 readings1 assignment
In this section, we explore Airflow deployment strategies, DAG delivery patterns, and secure configuration management to optimize workflow efficiency and reliability.
What's included
1 video4 readings1 assignment
In this section, we explore monitoring strategies for Airflow systems and DAGs, focusing on core component health, DAG performance metrics, and alerting mechanisms for efficient workflow management.
What's included
1 video2 readings1 assignment
In this section, we explore strategies for implementing multi-tenancy in Airflow, focusing on isolation, operational requirements, and secure shared infrastructure management.
What's included
1 video1 reading1 assignment
In this section, we explore planning migration activities, implementing technical strategies, and executing pipeline changes with minimal downtime to ensure smooth Airflow transitions.
What's included
1 video1 reading1 assignment
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