Lessons learned from auto-tuning PostgreSQL

We’ll explore the intricate world of postgreSQL parameter tuning, where the database management system reveals a multitude of configurable parameters that govern its runtime behavior. As the system evolves, the increasing number, the non-linear relationship and the complexity of these parameters highlight the importance of their correct configuration in optimizing application performance and cloud resource utilization.

This talk delves into various tuning approaches. We’ll start with the traditional, meticulous method of manual tuning, relying on expert analysis of metrics like query response time and resource usage. We’ll then explore heuristic-based tools like PGTune and PostgreSQL Configurator, offering one-size-fits-all solutions. Finally, we’ll set our sights on the future: auto-tuning with machine learning. We’ll showcase how these more sophisticated methods can be customized to a specific workload and machine resources.

We will share the lessons learned from developing DBtune, a framework for automating PostgreSQL tuning. We will highlight the challenges and the fundamental advantages of transforming PostgreSQL into a more self-driving database management system. Machine learning is not the sole solution, but an observation-based approach to parameter tuning holds the promise of enhanced database performance, reduced cloud costs, and a smaller environmental impact. In particular, we will establish a clear quantitative connection between database tuning and these three important objectives.

Speaker:
Dr. Luigi Nardi is the founder and CEO of DBtune (www.dbtune.com), a leading company driving advancements in AI, database systems, and cloud computing. Previously an associate professor of machine learning at Lund University and a research staff at Stanford University, Luigi's expertise centers around black-box optimization theory and practice. Luigi's journey includes a post-doctoral position at Imperial College London and a role as a software engineer at Murex S.A.S., following his Ph.D. program in applied mathematics and computer science at Université Pierre et Marie Curie in Paris in 2011.

Closed:
Registrations are now closed