Airflow Apache On Google Cloud

Airflow Apache is a sophisticated tool for scheduling and dependency graphing. It employs a Directed Acyclic Graph (DAG) to arrange and relate many tasks for your workflows

What are the various configuration options for Airflow Apache on Google Cloud? Making the incorrect decision could result in lower availability or more expenses

It will examine three methods for using Airflow Apache on Google Cloud in this post and go over the benefits and drawbacks of each

Installing and using Airflow directly on a Compute Engine virtual machine instance is a popular method for using Airflow on Google Cloud

Using Google Kubernetes Engine (GKE), Google’s managed Kubernetes service, running Airflow Apache on Google Cloud is made extremely simple

Additionally, you have the option to operate in GKE Autopilot mode, which will automatically scale your cluster according to your demands and assist you avoid running out of compute resources

Cloud Composer simplifies the Airflow installation process, relieving you of the burden of maintaining the Airflow infrastructure. But it offers fewer choices