Apache Airflow Training in Nantes

This instructor-led live training in Nantes (online or onsite) is aimed at advanced-level participants who wish to deploy Apache Airflow in cloud environments, set up CI/CD pipelines, and implement robust monitoring and logging practices.

By the end 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, held in Nantes (online or onsite), is designed for 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 Nantes (online or onsite) is targeted at advanced participants seeking to build custom operators, sensors, and plugins within Apache Airflow, and to integrate these components with existing data systems for enhanced automation and monitoring capabilities.

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

• Develop custom operators, hooks, and sensors tailored to specific workflows.
• Design and implement Airflow plugins to extend functionality.
• Integrate Airflow workflows with external systems and services.
• Optimize and monitor workflows using advanced debugging tools.
• Leverage best practices for managing large-scale Airflow deployments.

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

Upon completion 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 is an open-source platform designed for creating, scheduling, and overseeing workflows. With the release of Airflow 2.x, organizations can orchestrate large-scale data pipelines, integrate with cloud services, and ensure robust observability and security in production settings.

This instructor-led live training (available online or on-site) is tailored for data and DevOps professionals ranging from beginner to intermediate levels who aim to leverage Apache Airflow to build, automate, and scale end-to-end data pipelines.

Upon completion of this training, participants will be capable of:

• Installing and configuring Apache Airflow across various environments.
• Creating, scheduling, and monitoring DAGs using the TaskFlow API.
• Integrating Airflow with data sources, cloud services, and ML workflows.
• Managing ETL pipelines and ensuring data reliability.
• Securing and scaling Airflow using executors, queues, and Kubernetes.
• Applying observability and best practices for production deployments.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• For personalized training requests, please contact us to arrange.