Get in Touch

Course Outline

Advanced Apache Airflow Deployment Strategies

  • Deploying Apache Airflow on major cloud platforms (AWS, Azure, GCP)
  • Encapsulating Airflow services using Docker and Kubernetes
  • Configuring Airflow for high availability and resilience against failures

Implementing CI/CD Pipelines for Apache Airflow

  • Automating the testing and deployment lifecycle of DAGs
  • Connecting Airflow with CI/CD platforms (e.g., Jenkins, GitHub Actions)
  • Overseeing workflow version control and update management

Monitoring and Logging Frameworks

  • Establishing rigorous logging standards for workflow execution
  • Leveraging tools such as Prometheus and Grafana for system observability
  • Configuring alerting systems to address failure scenarios

Performance Tuning and Scalability

  • Fine-tuning Airflow configurations for peak efficiency
  • Scaling Airflow instances utilizing Celery executors
  • Managing large-scale workflow orchestration effectively

Security and Access Governance

  • Enforcing role-based access control (RBAC) within Airflow
  • Hardening Airflow environments and secure workflow execution
  • Best practices for handling sensitive data within workflows

Case Studies and Practical Implementation

  • Examining real-world applications of Airflow in DevOps automation
  • Practical exercise: Deploying Airflow integrated with CI/CD and monitoring stacks
  • Reviewing common challenges and effective solutions in DevOps workflow orchestration

Summary and Future Directions

Requirements

  • Foundational experience with Apache Airflow, encompassing DAG creation and task management
  • Understanding of CI/CD pipelines and core DevOps methodologies
  • Proficiency with cloud environments and containerization technologies (such as Docker and Kubernetes)

Target Audience

  • DevOps Engineers
  • Infrastructure Managers
  • Cloud Specialists
 21 Hours

Number of participants


Price per participant

Testimonials (1)

Upcoming Courses

Related Categories