For most of the last fifteen years, "move it to the cloud" was the answer to almost every data infrastructure question. Storage was cheap, compute was elastic, and nobody had to rack a server again. But for the past 18 months, a lot has happened to the data world — and the bills caught up with them.
Walk into almost any engineering org running a modern data stack today and you'll hear some version of the same complaint: the Snowflake or Databricks invoice keeps climbing, nobody can fully explain why, and finance is starting to ask uncomfortable questions in planning meetings. This isn't a hypothetical problem anymore. It's the reason "cloud repatriation" has gone from a niche blog post topic to a boardroom conversation.
How we got there
The pitch behind cloud data platforms was simple: pay for what you use, scale up when you're busy, scale down when you're not. In practice, a few things went wrong.
Nobody scales down. Warehouses get provisioned for peak load and then just... stay there. Auto-suspend settings get ignored. Dashboards refresh every five minutes when once a day would do. The elasticity that was supposed to save money quietly turns into a fixed cost nobody revisits.
