Airflow serves as a powerful platform for programmatically designing, scheduling, and overseeing workflows. Anchored in principles of dynamism, extensibility, elegance, and scalability, Airflow offers robust functionalities crucial for efficient workflow management. These include capabilities for task retries, managing dependencies between tasks, enforcing SLAs with error notifications, tracking metrics on completion times and failure rates, and providing comprehensive logging and visibility. Our Airflow training program is meticulously crafted to impart these foundational principles through a hands-on approach. Participants engage in interactive sessions featuring demonstrations, mini-projects, and practical use-case scenarios, enabling them to grasp industry best practices effectively. Moreover, the training can be tailored for corporate environments, ensuring alignment with specific client needs.
What Will You Learn?
- Workflow Automation: Understand how to automate the creation, scheduling, and monitoring of workflows using Apache Airflow, enhancing operational efficiency.
- ETL Management: Learn to manage Extract, Transform, Load (ETL) processes effectively with Airflow, essential for handling large volumes of data in various formats.
- Programmatic Workflow Authoring: Gain proficiency in programmatically defining workflows using Python-based DAGs (Directed Acyclic Graphs), which Airflow uses to represent workflows.
- Scheduling: Explore Airflow's scheduling capabilities to orchestrate workflows at specific times or intervals, ensuring timely execution of data pipelines.
- Monitoring and Alerting: Learn how to monitor workflow progress, track task statuses, and set up alerts for failures or delays, ensuring robust workflow management.
- Course Content: Access theoretical concepts and practical video tutorials that cover everything from Airflow basics to advanced features, enabling comprehensive learning and application of the platform.
Course Curriculum
Module 1: Introduction to Apache Airflow
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1.1 Understanding Workflow Orchestration
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:: What is Workflow Orchestration?
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:: The Role of Orchestration in Data Engineering
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:: Common Orchestration Tools: Apache Airflow vs. Others
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1.2 Introduction to Apache Airflow
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:: What is Apache Airflow?
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:: Key Features of Airflow
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:: Real-world Use Cases of Airflow in Data Engineering
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1.3 Installing and Setting Up Airflow
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:: System Requirements and Dependencies
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:: Installing Airflow Locally (Linux, Windows, MacOS)
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:: Setting Up Airflow with Docker and Docker Compose
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:: Overview of Managed Airflow Services (AWS MWAA, Google Cloud Composer)
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1.4 Airflow UI and Core Concepts
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:: Navigating the Airflow Web UI
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:: DAGs, Tasks, and Operators
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:: Task Instances, DAG Runs, and Schedulers
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:: Understanding Airflow’s Directed Acyclic Graph (DAG)