Apache Airflow: Building and Managing Data Pipelines Training Course

Introduction to Apache Airflow for Government

• Understanding workflow orchestration
• Key features and benefits of Apache Airflow for government operations
• Overview of Airflow 2.x improvements and ecosystem enhancements

Architecture and Core Concepts for Government

• Scheduler, web server, and worker processes in a public sector context
• Directed Acyclic Graphs (DAGs), tasks, and operators tailored for government workflows
• Executors and backends (Local, Celery, Kubernetes) suitable for government IT environments

Installation and Setup for Government

• Installing Airflow in local and cloud environments to meet government standards
• Configuring Airflow with different executors for optimal performance in government systems
• Setting up metadata databases and connections to ensure compliance and security

Navigating the Airflow UI and CLI for Government

• Exploring the Airflow web interface to manage government workflows
• Monitoring DAG runs, tasks, and logs for enhanced transparency and accountability
• Using the Airflow CLI for administration in government IT environments

Authoring and Managing DAGs for Government

• Creating DAGs with the TaskFlow API to streamline public sector processes
• Utilizing operators, sensors, and hooks to integrate government data sources
• Managing dependencies and scheduling intervals to align with government timelines

Integrating Airflow with Data and Cloud Services for Government

• Connecting to databases, APIs, and message queues to support government data needs
• Running ETL pipelines with Airflow to enhance data governance
• Cloud integrations: AWS, GCP, Azure operators for secure and scalable government operations

Monitoring and Observability for Government

• Task logs and real-time monitoring to ensure operational transparency
• Metrics with Prometheus and Grafana to support performance reporting
• Alerting and notifications with email or Slack to maintain timely communication

Securing Apache Airflow for Government

• Role-based access control (RBAC) to enforce data security policies
• Authentication with LDAP, OAuth, and SSO to ensure secure user access
• Secrets management with Vault and cloud secret stores for enhanced data protection

Scaling Apache Airflow for Government

• Parallelism, concurrency, and task queues to optimize government operations
• Using CeleryExecutor and KubernetesExecutor for scalable workflows
• Deploying Airflow on Kubernetes with Helm to support robust government IT infrastructure

Best Practices for Production in Government

• Version control and CI/CD for DAGs to ensure continuous improvement
• Testing and debugging DAGs to maintain high standards of reliability
• Maintaining reliability and performance at scale to meet government service demands

Troubleshooting and Optimization for Government

• Debugging failed DAGs and tasks to resolve issues efficiently
• Optimizing DAG performance to enhance operational efficiency
• Common pitfalls and strategies to avoid them in government workflows

Summary and Next Steps for Government