Apache Airflow Training in Belgrade

This instructor-led live training in Belgrade (available online or on-site) is designed for advanced participants aiming to deploy Apache Airflow in cloud environments, establish CI/CD pipelines, and implement strong monitoring and logging practices.

By the conclusion of this training, participants will be able to:

• Deploy Apache Airflow in cloud and containerized environments.
• Set up CI/CD pipelines to automate DAG testing and deployment.
• Integrate monitoring and logging tools to enhance system reliability.
• Optimize Airflow configurations for performance and scalability.
• Implement security best practices for managing workflows and environments.

This instructor-led, live training in Belgrade (online or onsite) is aimed at intermediate-level participants who wish to automate and manage machine learning workflows, including model training, validation, and deployment using Apache Airflow.

By the end of this training, participants will be able to:

• Set up Apache Airflow for machine learning workflow orchestration.
• Automate data preprocessing, model training, and validation tasks.
• Integrate Airflow with machine learning frameworks and tools.
• Deploy machine learning models using automated pipelines.
• Monitor and optimize machine learning workflows in production.

This instructor-led, live training in Belgrade (online or onsite) targets advanced-level participants aiming to build custom operators, sensors, and plugins within Apache Airflow, and to integrate these components with existing data systems for sophisticated automation and monitoring.

Upon completion of this training, participants will be able to:

• Develop custom operators, hooks, and sensors specifically tailored to particular workflows.
• Design and implement Airflow plugins to expand functionality.
• Integrate Airflow workflows with external systems and services.
• Optimize and monitor workflows utilizing advanced debugging tools.
• Apply best practices for managing large-scale Airflow deployments.

This instructor-led, live training in Belgrade (online or onsite) targets intermediate-level participants who aim to optimize workflow performance, manage complex dependencies, and scale Apache Airflow deployments for larger datasets and enterprise use cases.

By the end of this training, participants will be able to:

• Optimize Apache Airflow workflows to enhance performance and reliability.
• Manage and troubleshoot complex workflow dependencies.
• Leverage advanced Airflow features, including custom operators and sensors.
• Scale Apache Airflow to handle larger data sets and distributed systems.
• Implement best practices for monitoring, logging, and security in Airflow environments.

Apache Airflow serves as an open-source platform for creating, scheduling, and monitoring workflows. With the release of Airflow 2.x, organizations can orchestrate data pipelines at scale, integrate with cloud services, and ensure robust observability and security in production environments.

This instructor-led, live training (available online or onsite) targets beginner to intermediate data and DevOps professionals who wish to leverage Apache Airflow to build, automate, and scale end-to-end data pipelines.

Upon completion of this training, participants will be able to:

• Install and configure Apache Airflow across various environments.
• Author, schedule, and monitor Directed Acyclic Graphs (DAGs) using the TaskFlow API.
• Integrate Airflow with data sources, cloud services, and machine learning workflows.
• Manage ETL pipelines and ensure data reliability.
• Secure and scale Airflow using executors, queues, and Kubernetes.
• Apply observability and best practices for production deployments.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical activities.
• Hands-on implementation within a live lab environment.

Customization Options

• For customized training options, please contact us to arrange.