Apache Airflow Training in Christchurch

This instructor-led, live training in Christchurch (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 containerised environments.
• Set up CI/CD pipelines to automate DAG testing and deployment.
• Integrate monitoring and logging tools to enhance system reliability.
• Optimise Airflow configurations for performance and scalability.
• Implement security best practices for managing workflows and environments.

This instructor-led, live training in Christchurch (online or on-site) 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 optimise machine learning workflows in production.

This instructor-led, live training in Christchurch (online or onsite) is aimed at advanced-level participants who wish to create custom operators, sensors, and plugins in Apache Airflow, and integrate these with existing data systems for advanced automation and monitoring.

By the end 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.
• Optimise and monitor workflows using advanced debugging tools.
• Leverage best practices for managing large-scale Airflow deployments.

This instructor-led, live training in Christchurch (online or onsite) is aimed at intermediate-level participants who wish to optimise 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:

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

Apache Airflow is an open-source platform designed for authoring, scheduling, and monitoring workflows. With Airflow 2.x, organisations can orchestrate data pipelines at scale, integrate seamlessly with cloud services, and ensure robust observability and security in production environments.

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

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

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

Course Format

• Interactive lectures and discussions.
• Extensive exercises and hands-on practice.
• Real-world implementation in a live-lab environment.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.