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Course Outline
Advanced Deployment of Apache Airflow
- Deploying Apache Airflow across major cloud infrastructure providers, including AWS, Azure, and GCP
- Implementing containerized deployments using Docker and Kubernetes for standardized management
- Configuring Airflow architectures to ensure high availability and fault tolerance for government operations
CI/CD Pipelines for Apache Airflow
- Automating the testing and deployment of Directed Acyclic Graphs (DAGs)
- Integrating Airflow with continuous integration and continuous deployment tools, such as Jenkins and GitHub Actions
- Managing version control and updates for workflow definitions to maintain system integrity
Monitoring and Logging
- Establishing comprehensive logging standards for all workflow executions
- Leveraging monitoring platforms such as Prometheus and Grafana to track system health
- Configuring automated alerting systems to address failure scenarios promptly
Performance Optimization and Scaling
- Tuning Airflow configuration parameters to maximize operational efficiency
- Scaling Airflow infrastructure through the implementation of Celery executors for government workloads
- Managing orchestration requirements for large-scale workflow processing
Security and Access Control
- Enforcing role-based access control (RBAC) within Airflow environments
- Strengthening security protocols for Airflow instances and associated workflows
- Adhering to best practices for the protection of sensitive data during workflow execution
Case Studies and Practical Applications
- Analyzing real-world implementations of Airflow in DevOps automation contexts
- Conducting practical exercises involving the deployment of Airflow with integrated CI/CD and monitoring tools
- Evaluating common challenges and effective solutions in government workflow orchestration
Summary and Next Steps
Requirements
- Proficiency in fundamental Apache Airflow operations, encompassing Directed Acyclic Graph (DAG) development and task orchestration
- Understanding of continuous integration and continuous deployment (CI/CD) workflows alongside established DevOps methodologies
- Competence in utilizing cloud-based infrastructure and containerization technologies, such as Docker and Kubernetes
Audience
- DevOps engineers
- Infrastructure managers
- Cloud specialists
This curriculum is designed for government professionals seeking to enhance technical capabilities in modern data engineering and infrastructure management.
21 Hours
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.
