Azure Databricks ETL architecture comparison showing migration from always-on shared clusters to ephemeral job clusters orchestrated by Azure Data Factory and Databricks Workflows. The AS-IS design uses sequential notebook activities on a persistent All-Purpose Cluster connected to ADLS Gen2 and Snowflake, incurring continuous compute costs. The TO-BE architecture replaces this with Databricks Job Triggers and Workflow Jobs that auto-create Job Clusters per run, reducing idle time and infrastructure spend. This shift demonstrates best practices for cost-efficient data pipelines while maintaining audit logging through dedicated Audit Start and Audit End notebooks. Fork and customize this diagram on Diagrams.so to align with your organization's migration roadmap and cluster sizing strategy.