From Recommendation to Action: Scaling Autonomous Databricks Optimization in the Enterprise
Every Databricks optimization platform can tell you what should change. The harder question is: when should a system be trusted to make that change on its own? This session follows the journey of an Unravel customer as we moved from surfacing Databricks platform optimization recommendations to safely applying them in production. Prajakta will talk about the engineering decisions, the guardrails, and the trust model that made autonomous optimization possible in an environment where every change carries operational risk.