This talk presents research on a new generation of autonomous tuning agents that optimize more parts of a database in less time and at lower costs than previous methods. We will describe our automated methods for tuning nearly every possible option available in PostgreSQL: system/table/index knobs, index selection, and query plan hints. As part of this talk, we will also discuss our successes and failures in using LLMs to accelerate database tuning, as well as our road map towards achieving a true self-driving database system.
