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Course Outline

Advanced Apache Airflow Deployment Strategies

  • Implementing Apache Airflow on major cloud providers (AWS, Azure, GCP)
  • Containerizing Airflow instances using Docker and Kubernetes
  • Configuring Airflow for high availability and resilience against failures

Integrating CI/CD Pipelines with Apache Airflow

  • Automating the testing and deployment of DAGs
  • Connecting Airflow with CI/CD platforms (e.g., Jenkins, GitHub Actions)
  • Overseeing workflow versioning and iterative updates

Comprehensive Monitoring and Logging

  • Establishing effective logging standards for workflow execution
  • Leveraging tools such as Prometheus and Grafana for system observability
  • Configuring alerting systems for failure detection and response

Performance Tuning and Scaling

  • Optimizing Airflow parameters for peak efficiency
  • Scaling Airflow deployments utilizing Celery executors
  • Managing large-scale workflow orchestration challenges

Security Frameworks and Access Control

  • Enforcing role-based access control (RBAC) within Airflow
  • Safeguarding Airflow environments and associated workflows
  • Applying best practices for the secure handling of sensitive data

Case Studies and Practical Scenarios

  • Examining real-world applications of Airflow in DevOps automation
  • Practical exercise: Implementing Airflow alongside CI/CD and monitoring stacks
  • Exploring challenges and solutions in DevOps workflow orchestration

Conclusion and Future Directions

Requirements

  • Proficiency with Apache Airflow fundamentals, including DAG construction and task oversight
  • Understanding of CI/CD pipelines and broader DevOps methodologies
  • Working knowledge of cloud environments and containerization technologies (e.g., Docker, Kubernetes)

Target Audience

  • DevOps engineers
  • Infrastructure managers
  • Cloud specialists
 21 Hours

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