Apache Airflow DAG: Idempotent Workflows
Feb 12 · 11 min read · Why Traditional Airflow DAG Patterns Fail at Scale Many data engineers approach Airflow DAG design with patterns borrowed from traditional ETL tools or batch processing frameworks that assume linear, one-time execution. These patterns break down cata...
Join discussionApache Airflow: A Birds-Eye View
Jan 8 · 3 min read · Definition Apache Airflow is a workflow scheduler. It defines what should run, when it should run, and in what order — but it does not perform the work itself. Core Building Blocks DAG (Directed Acyclic Graph) A DAG is a workflow definition, written ...
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Building High Throughput Systems
Dec 29, 2025 · 31 min read · High throughput isn't achieved by throwing more servers at the problem, it's earned through architectural decisions that align with how data is actually accessed and used. In this exploration, we'll dissect four systems that handle massive scale: Ama...
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Installing Apache Airflow on AWS EC2 (Ubuntu)
Nov 14, 2025 · 4 min read · Apache Airflow is one of the most powerful workflow automation tools used in data engineering and ETL pipelines. But for beginners, setting it up on an AWS EC2 instance for the first time can feel confusing. This guide explains EVERY step, from serve...
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Ingesting YouTube Data with Apache Airflow 3.x
Nov 3, 2025 · 3 min read · Here’s the deal: you want to pull YouTube video data—title, description, transcript, the works—into DuckDB using Airflow. Most tutorials overcomplicate this. Let’s cut the fluff and get you a pipeline that actually works, is secure, and doesn’t break...
Join discussionHow to Create a Simple ETL Pipeline in Airflow: Moving Data from Excel to a Database
Oct 26, 2025 · 5 min read · Automating Bank Transaction Processing with Python, Airflow, and PostgreSQL In this guide, I’ll show you how I built a complete ETL (Extract, Transform, Load) pipeline that reads raw bank transaction data from an Excel file, cleans and enriches it, a...
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From Cron Jobs to MLOps: A Complete Guide to Building ML Pipelines with Apache Airflow
Oct 18, 2025 · 7 min read · If you're in data science or machine learning, you're familiar with this story: you've built a fantastic model in a Jupyter Notebook. It works perfectly. Now... how do you run it every night? How do you fetch new data, re-train it, validate the resul...
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🚀 Apache Airflow for MLOps: Orchestrating Machine Learning Pipelines Like a Pro
Oct 12, 2025 · 5 min read · Machine Learning models don’t live in Jupyter notebooks forever. Once trained, they need automated pipelines — to fetch new data, retrain, evaluate, and deploy models seamlessly. That’s where Apache Airflow becomes a game-changer. In this blog, you’l...
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