Abstract: At H&M Group, we are increasingly adopting machine learning algorithms and rapidly developing successful use cases, one of the applications is a dynamic resources allocation (memory and cpu) using data driven analysis and ML to decrease the cost of infrastructure. The objective of this talk is to show how one of H&M use cases adopted ML workflow using airflow, kubernetes and docker and how to solve the provisioning problem with ML approach. For more details: https://pretalx.com/pycon-sweden-2021/talk/9NEFHA/ Speakers: Amira DINARI Jialun Song