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Duration 21 hours
Course Outline
Refresher on Apache Airflow Fundamentals
- Key principles: DAGs, operators, and execution logic
- Structural overview of Airflow and its core components
- Analysis of complex use cases and workflow patterns
Building Custom Operators
- Deconstructing the structure of an Airflow operator
- Coding custom operators for specialized tasks
- Validating and troubleshooting custom operator implementations
Developing Custom Hooks and Sensors
- Creating hooks to facilitate external system connectivity
- Constructing sensors to track external triggers
- Improving workflow responsiveness through custom sensor logic
Building Airflow Plugins
- Examining the underlying plugin architecture
- Structuring plugins to augment Airflow’s native features
- Adopting best practices for plugin management and deployment
Connecting Airflow to External Ecosystems
- Linking Airflow with databases, API endpoints, and cloud platforms
- Utilizing Airflow for ETL processes and real-time data handling
- Handling dependencies between Airflow and third-party systems
Sophisticated Debugging and Monitoring
- Leveraging Airflow logs and performance metrics for issue resolution
- Setting up alerts and notifications for workflow anomalies
- Incorporating external monitoring solutions with Airflow
Enhancing Performance and Scalability
- Expanding Airflow capacity using Celery and Kubernetes Executors
- Improving resource efficiency in complex workflow environments
- Implementing strategies for high availability and fault resilience
Real-World Scenarios and Applications
- Investigating advanced applications in data engineering and DevOps
- Case study: Implementing custom operators for large-scale ETL pipelines
- Establishing best practices for enterprise-grade workflow management
Conclusions and Future Directions
Requirements
- A solid grasp of foundational Apache Airflow concepts, such as DAGs, operators, and execution architecture
- Advanced proficiency in Python programming
- Practical experience in data system integration and workflow orchestration
Target Audience
- Data engineers
- DevOps engineers
- Software architects
Testimonials (1)
The instructor adapted the training to the participants’ level and responded to all questions. He was very communicative, and it was easy to interact with him. I really appreciated the format of the training, which included many practical exercises. Overall, it was a very engaging and well-organized session.
