A.B.C.D Apache Airflow 2.x on AWS - EKS | Minikube | Helm

🚀 Course Headline:

Unlock the Power of Airflow with Confidence on AWS! 🌩️ Whether you're setting up for local development or ready to scale with production deployment on Amazon EKS or Minikube, this course simplifies the process for you. Get ready to deploy Airflow effortlessly with Helm and master cloud-native solutions on AWS with ease!

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Course Instructor: Faizan Qazic
🎓 About the Instructor: Faizan is an expert in cloud solutions and a seasoned DevOps Engineer with hands-on experience deploying Apache Airflow at scale. His expertise will guide you through every step of this course.

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🧭 What You'll Learn

In this comprehensive course, you'll dive into the world of Apache Airflow and AWS cloud services to deploy a robust and scalable Airflow setup:

• Local Development Setup: Craft a script for hassle-free local Airflow deployment. 🏠
• Helm Chart Creation: Develop your own Helm chart tailored for Airflow. 🚀
• Script & YAML Template Mastery: Perfect your skills in templating scripts and YAML files for seamless configurations.
• EKS Cluster Configuration: Configure a scalable EKS cluster using eksctl. 🌐
• Ingress Controller Setup: Deploy an Application Load Balancer (ALB) Ingress Controller to balance load and access the Airflow UI smoothly. 🌍
• EFS Integration: Mount Elastic File System (EFS) for persistent logging of Kubernetes Executor logs. 🗂️
• AWS CodePipeline Deployment: Automate your deployment process with AWS CodePipeline. 🤖

📚 Prerequisites

Before diving into this course, ensure you have a grasp of:

• Basic Knowledge of Airflow Components: Familiarity with the fundamentals of Apache Airflow. 🛠️
• Kubernetes Basics: Understanding of Kubernetes concepts and terminology. 🐘
• AWS Fundamentals: Basic knowledge about AWS services and how they work. 🌟
• IDE Experience: Comfortable working within an Integrated Development Environment (IDE). 💻

🔗 Dependencies

To make the most of this course, you will need:

• Operating System: Linux or Windows. 🏬
• AWS Account: Necessary for non-local deployments. 🛫

📚 Course Content

This course aligns with the Production Guide of Apache Airflow and adheres to the official AWS documentation, ensuring you are always up-to-date and can access detailed information whenever needed.

👥 Who This Course Is For

This course is tailored for professionals who:

• DevOps Engineers: Looking to understand the technicalities behind deploying Airflow with EFS, using a Kubernetes Executor, and more.
• Data Engineers: Aiming to use Airflow effectively for development without the hassle of setup.
• Full Stack Engineers: Eager to explore frameworks and integrations like Helm, AWS EKS, and others.
• Developers Focused on Development: Desiring a straightforward approach to set up Airflow, so you can concentrate on what truly matters - your projects.

🚫 Who This Course Isn't For

If your focus is on understanding the fundamentals of Airflow, creating DAGs, or developing pipelines from scratch, this course may not be the right fit for you at this time.

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❗️ Note

Please be aware that some AWS resources used in this course, such as EKS, are not eligible for the free tier and may incur costs. Ensure you understand your cloud usage and manage your resources accordingly to avoid unexpected charges.

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Embark on your journey to mastering Airflow deployments on AWS with this insightful and practical course. 🌟 Let's turn complex setup processes into child's play and focus on what we love - creating and managing data workflows with Airflow! Sign up now and transform the way you deploy, manage, and scale your data processing workloads.

🌟 Overall Course Review 🌟

The course on deploying Apache Airflow on Amazon Elastic Kubernetes Service (EKS) has received an overwhelmingly positive response from recent students, with a global course rating of 4.95 out of 5. The reviews consistently highlight the course's comprehensive content and the instructor's clear and expert guidance.

Pros:

• Comprehensive Framework: The course provides an excellent framework for creating deployment automations that can be applied broadly if fully understood, particularly for those with development operations (DevOps) and AWS experience.

• Expert Instructor: The instructor's explanations are described as superb, with a clear accent that doesn't hinder understanding. Additionally, the instructor is highly responsive to student inquiries, offering one-on-one support to help solve any issues encountered during the course.

• Updated Content: The course content is up-to-date, reflecting the latest versions of Airflow and EKS. This ensures that students are learning the most current practices.

• Step-by-Step Instructions: Clear, step-by-step instructions are provided throughout the course, making it easy to follow along and implement what is taught.

• Invaluable for Data Engineers: The course is beneficial for data engineers who seek insights and tools for deploying Airflow, offering valuable knowledge for their professional work.

• Supportive Learning Environment: There is a strong emphasis on support, with the instructor going above and beyond to assist students through Q&A sessions and direct communication.

Cons:

• Experience Required: Some prior experience with DevOps and AWS is recommended to fully benefit from the course, as it assumes a certain level of familiarity with these technologies.

In conclusion, this course stands out for its up-to-date content, clear instruction, and responsive instructor support. It is highly recommended for professionals looking to deploy Apache Airflow on EKS, especially those with some DevOps and AWS background. The positive reviews from recent students underscore the course's effectiveness and the high quality of education it offers.