We can define Airflow as a popular open-source platform for creating, scheduling and monitoring workflows. It can be used for building ML models, transferring data, handling infrastructure and many other tasks. To work with it, you only need to know Python, as Airflow pipelines are defined in this language. It is free to install, can be used by anyone who wants it, and has a strong, active community. These are only some of its many advantages. As we use Apache Airflow on a daily basis in our projects, we’ve come up with many tips that we would like to share with other users and our customers. If you can’t find answers to your questions in the Airflow docs, we are happy to help you solve your problems or get additional information. On our blog, you will find a comparison of an old version of Airflow and Airflow 2.0 and articles on Airflow functionalities and performance. Read our articles here.