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