Do anyone have structure and crisp comparison between benefits of performing MLOps using below ways and what are the strong areas of each platform:
a) Standalone Databricks where all pipelines and orchestration done on Databricks and external third party tools.
b) Databricks on AWS where Databricks solely used for Data engineering activities and AWS Sagamaker/other AWS services used for all MLOps activities.
c) Databricks on Azure where Databricks solely for Data engineering activities and Azure ML/other Azure services used for all MLOps activities.
d) Databricks on AWS where Databricks used for Data engineering and ML pipeline activities, and AWS services used for quick deployment etc.
e) Databricks on Azure where Databricks used for Data engineering and ML pipeline activities, and Azure services used for quick deployment etc.
