Apache Airflow on AWS EKS: The Hands-On Guide

🚀 Course Title: Apache Airflow on AWS EKS: The Hands-On Guide

🎓 Course Headline: Master the Art of Setting Up Apache Airflow on AWS EKS with Kubernetes Executor for a Production-Ready Environment!

Why You Should Take This Course 🌟:

Are you facing challenges while setting up Apache Airflow on AWS EKS with the Kubernetes Executor? You're not alone. With over 15,000 students, we've heard the struggles firsthand. But now, you have the chance to learn everything you need to create a robust, scalable, and production-ready architecture for Apache Airflow on AWS EKS.

Course Description:

This course is your step-by-step guide to navigating the complexities of deploying Airflow on Kubernetes within the AWS ecosystem. Marc Lamberti, with a wealth of experience, will lead you through the process, ensuring that by the end of this course, you'll have a deep understanding of setting up Apache Airflow in a real-world scenario.

What You Will Learn:

🎉 Key Steps for a Real-World Architecture:

1. Configuring EKS Cluster: Set up your EKS cluster following best practices to lay a solid foundation.

2. GitOps Deployments: Automatically manage changes and deployments using GitOps workflows.

3. Helm Configuration: Utilize Helm to configure and deploy Airflow on Kubernetes with ease.

4. Kubernetes Executor Setup: Configure the official Helm chart of Airflow to leverage the Kubernetes Executor, along with its various features.

5. DAG Deployment with Git-Sync & AWS EFS: Learn to deploy your DAGs using Git-Sync and AWS Elastic File System (EFS) for seamless integration.

6. CI/CD with AWS CodePipeline: Implement continuous deployment of DAGs through AWS CodePipeline.

7. Automated Testing of DAGs: Automatically test your DAGs to ensure reliability and functionality.

8. Secure Credentials & Sensitive Data: Secure your credentials and sensitive data using a Secret Backend for enhanced security.

9. Remote Logging with AWS S3: Enable remote logging with AWS S3 for effective monitoring of your Airflow instances.

10. Creating Environments (Dev/Staging & Prod): Set up three distinct environments to manage your development, staging, and production workloads effectively.

11. Scalable and Highly Available Production Environment: Design a production environment that is both scalable and highly available to handle large-scale data processing needs.

🚫 Important Notes:

• Assumed Knowledge: This course presumes you are already familiar with Airflow basics. It's not designed for beginners in Airflow.

• Kubernetes/Docker/AWS Experience: While knowledge of Kubernetes, Docker, and AWS is beneficial, Marc will cover the essentials to ensure everyone can follow along.

• AWS Services Usage: This course focuses on designing an architecture for Airflow on AWS EKS, not writing DAGs. You won't be learning how to interact with AWS services within your DAGs.

• Course Cost: Please note that this course is not free-tier eligible as we will be utilizing a multitude of AWS services to set up a real-world architecture.

Join Marc Lamberti in This Comprehensive Guide to Apache Airflow on AWS EKS! 🚀✨

Enroll now and take your first step towards mastering Apache Airflow on AWS EKS with the Kubernetes Executor, and build a production-ready architecture that stands the test of time. Let's embark on this journey together!